Associate Professor from Saveetha School of Engineering, SIMATS, India

R. Mahesh Muthulakshmi is a proactive and goal-oriented academic professional with over 12 years of rich experience in the field of Computer Science and Engineering. He has consistently demonstrated exceptional time management, problem-solving skills, and a capacity for rapid learning and adaptability. His expertise lies in data security, cloud computing, artificial intelligence, and machine learning, with a particular focus on developing robust security solutions for cloud-based environments. He has published several high-quality research papers in SCI and Scopus-indexed journals and has actively contributed to international and national conferences. In addition to his research, he has played a significant role in organizing technical events, workshops, and international conferences, enhancing his leadership and collaborative abilities. His dedication to continuous learning is reflected in his regular participation in Faculty Development Programs (FDPs) and workshops, further sharpening his technical competencies. Known for his sense of responsibility and reliability, he is committed to contributing positively to his academic community and research field. His profile is characterized by a solid balance of teaching, research, and active engagement in professional bodies, showcasing his well-rounded commitment to academia and research excellence.

Professional Profile

Google Scholar

Education

R. Mahesh Muthulakshmi has pursued a strong academic path in the domain of Computer Science and Engineering. He is currently undertaking his doctoral studies (Ph.D.) in Computer Science Engineering at Saveetha School of Engineering, SIMATS University, Chennai, with an expected completion in April 2025. His Ph.D. research focuses on advanced security models and encryption algorithms for industrial and cloud-based applications, indicating his dedication to solving critical challenges in modern computing environments. He holds a Master of Engineering (M.E.) in Computer Science Engineering from VLB Janakiammal College of Engineering and Technology, Coimbatore, affiliated with Anna University, which he completed in May 2009 with first-class honors. His undergraduate journey began with a Bachelor of Engineering (B.E.) in Computer Science Engineering from Kamaraj College of Engineering & Technology, Virudhunagar, also under Anna University, Chennai, which he successfully completed in May 2007 with first-class distinction. His academic trajectory reflects both depth and continuity in his specialized area, forming a strong foundation for his research pursuits. Throughout his education, Mahesh has been focused on practical and innovative problem-solving, which is now evident in his research and professional activities.

Professional Experience

R. Mahesh Muthulakshmi possesses over 12 years of comprehensive teaching and research experience, demonstrating versatility and leadership across reputable academic institutions. He began his career as an Assistant Professor in the Department of Computer Science and Engineering at Nehru College of Engineering and Research Center, Kerala, where he served from January 2009 to June 2010. His teaching career progressed to Sri Raaja Raajan College of Engineering and Technology, Karaikudi, where he worked as an Assistant Professor from June 2010 to December 2010. The most significant phase of his professional journey was at Indira Gandhi College of Engineering and Technology for Women, Chengalpattu, where he contributed as an Assistant Professor from May 2011 to November 2021. During this tenure, he not only imparted technical knowledge but also mentored students, organized conferences, and contributed to the academic community’s growth. His experience spans curriculum development, student counseling, technical event management, and hands-on research, highlighting his ability to balance academic responsibilities with impactful research work. Throughout his career, Mahesh has been recognized for his reliability, adaptability, and passion for delivering quality education while contributing actively to advancing knowledge in his field.

Research Interest

R. Mahesh Muthulakshmi’s research interests are centered around data security, cloud computing, artificial intelligence, machine learning, and optimization algorithms. His primary focus lies in developing secure and efficient encryption models that protect sensitive data in cloud environments, which is crucial in the era of digital transformation. His work addresses emerging threats such as Distributed Denial-of-Service (DDoS) attacks and data breaches, aiming to create robust systems that can withstand security vulnerabilities. Mahesh is also deeply interested in integrating machine learning and AI-based techniques to enhance cybersecurity frameworks and improve the performance of encryption protocols. His research spans topics such as dual generative hyperbolic graph adversarial networks, particle swarm optimization, and cloud data security using advanced cryptographic methods. Additionally, he explores the applications of neural networks for securing data storage and transfer, contributing to the broader field of secure cloud architecture. His dedication to researching the intersection of AI, cloud computing, and data security showcases his commitment to providing cutting-edge solutions to real-world industrial and technological challenges, positioning him as an emerging leader in the cybersecurity and cloud computing domains.

Research Skills

R. Mahesh Muthulakshmi has developed strong and diverse research skills throughout his academic and professional journey, particularly in the areas of data security management, encryption algorithms, and cloud computing systems. He is proficient in designing and implementing advanced cryptographic techniques to secure data in both public and private cloud environments. His research acumen extends to developing machine learning models and integrating artificial intelligence into security protocols to detect and prevent cyber threats such as DDoS attacks. Mahesh has also demonstrated the ability to use optimization algorithms like particle swarm optimization to enhance system performance and security robustness. His practical research skills include data analysis, cloud-based system architecture design, and coding across multiple programming languages, making him technically versatile. Additionally, Mahesh is adept at preparing high-quality research papers, presenting at international conferences, and collaborating with multidisciplinary teams to achieve research objectives. His involvement in workshops and faculty development programs further illustrates his continuous upskilling in emerging technologies such as blockchain, IoT, and generative AI. These research capabilities collectively showcase his ability to contribute meaningful innovations to the fields of cloud computing, data security, and artificial intelligence.

Awards and Honors

R. Mahesh Muthulakshmi has received several awards and recognitions that reflect his excellence in academic and research contributions. Notably, he was honored with the Excellence Award in 2024 by Educators Empowering India, which is a significant acknowledgment of his dedication and impactful work in the educational sector. He also received the Best Poster Award at the Star Submit organized by SIMATS School of Engineering in 2024, further validating his research proficiency and presentation skills. His active participation in numerous national and international Faculty Development Programs (FDPs), workshops, and seminars underscores his commitment to continuous learning and academic excellence. Mahesh’s accolades are complemented by his leadership roles in organizing key events such as the International Conference on Computational Intelligence, Fog Computing, and Cybernetics Systems (ICCIFS-2024) and the International Conference on Communication Engineering and Technology (2018). Additionally, his memberships in prestigious organizations like the International Association of Engineers (IAENG) and the International Association of Computer Science and Information Technology (IACSIT) reflect his strong integration within the global academic and professional community. These honors collectively demonstrate his sustained contributions and dedication to research and education.

Conclusion

R. Mahesh Muthulakshmi exemplifies the qualities of a dedicated researcher and academic professional, with his career reflecting a perfect blend of teaching excellence, innovative research, and active participation in scholarly activities. His focus on data security and cloud computing addresses some of the most pressing technological challenges of the modern era, and his research outputs in SCI and Scopus-indexed journals reinforce the quality and relevance of his work. His proactive approach in participating in faculty development programs, organizing international conferences, and collaborating with peers shows his commitment to continuous growth and academic leadership. Furthermore, his recognition through various awards and active memberships in professional bodies positions him as a respected figure in his field. While expanding international collaborations and increasing his publication footprint in top-tier journals could further elevate his profile, his current contributions already mark him as a valuable asset to the research community. Overall, Mahesh stands out as a deserving candidate for prestigious recognitions such as the Best Researcher Award, with strong potential to continue making meaningful advancements in computer science and engineering.

Publications Top Notes

1. A Robust Approach to Cloud Data Security Using an Amalgamation of AES and Code-Based Cryptography

Authors: R.M. Muthulakshmi, T.P. Anithaashri
Year: 2024
Citations: 2

2. Novel Weight-Improved Particle Swarm Optimization to Enhance Data Security in Cloud

Authors: M.M. R
Year: 2023
Citations: 2

3. An Optimized Dual Generative Hyperbolic Graph Adversarial Network With Multi‐Factor Random Permutation Pseudo Algorithm Based Encryption for Secured Industrial Healthcare Data

Authors: R.M. Muthulakshmi, T.P. Anithaashri
Year: 2025

4. Enhancing Data Security in Cloud Using Artificial Neural Network with Backward Propagation

Authors: R.M. Muthulakshmi, T.P. Anithaashri, C. Nataraj, V.S.N. Talasila
Year: 2024

5. Data Security in Cloud Computing Using Maritime Search and Rescue Algorithm

Authors: A. Mahesh Muthulakshmi
Year: 2024

6. Enhancing the Detection of DDoS Attacks in Cloud Using Linear Discriminant Algorithm

Authors: M.M. R, A. T.P.
Year: 2023

7. The Security in Online Data Sharing on the Public Server Using Secure Key-Aggregate Cryptosystems with Broadcast Aggregate Keys

Authors: R.M. Muthulakshmi
Year: 2018

8. Data Access Control in Public Cloud Storage System Using “CP-ABE” Technique

Authors: S.K. R. Mahesh Muthulakshmi, Karthiga E., Ramani K.
Year: 2018

9. The Darwinism of Big Data Security Through Hadoop Augmentation Security Model

Authors: R. Mahesh Muthulakshmi, M.S.M. Sivam, D. Anitha
Year: 2016

Shivam Kumar | Computer Science | Best Researcher Award

Posted on 09/06/202509/06/2025 by Shen Awards

Mr. Shivam Kumar | Computer Science | Best Researcher Award

Techno International New Town, India

Shivam Kumar is an ambitious and driven undergraduate student specializing in Artificial Intelligence and Machine Learning. Currently pursuing his B.Tech at Techno International New Town under MAKAUT, West Bengal, he maintains a strong academic record with a CGPA of 8.39 as of the 7th semester. Shivam is passionate about applying his analytical and technical skills toward solving real-world problems, particularly in the healthcare and computer vision domains. He has demonstrated a proactive approach to research by publishing papers in both journals and conferences, reflecting his commitment to academic growth and knowledge dissemination. Shivam’s project portfolio showcases his ability to develop end-to-end machine learning pipelines and apply classical algorithms in programming languages such as C++ and Python. In addition to his technical expertise, he has proven teamwork and problem-solving capabilities through active participation in events like the Smart India Hackathon, where his team achieved third place. His goal is to build a career in an innovative and growth-oriented organization, where continuous learning and impactful contributions are valued.

Professional Profile

Education

Shivam Kumar is currently enrolled in a Bachelor of Technology program with a specialization in Artificial Intelligence and Machine Learning at Techno International New Town, affiliated with MAKAUT, West Bengal. Expected to graduate in July 2025, he has maintained a commendable CGPA of 8.39 through rigorous coursework that includes data structures, algorithms, DBMS, computer networks, operating systems, and software engineering. Prior to his undergraduate studies, Shivam completed his higher secondary education (AISSCE) from Jasidih Public School, Jharkhand, with an aggregate score of 72.2%. His foundational schooling was completed at G.D. D.A.V Public School, Jharkhand, where he scored 86.33% in the Class X AISSE examination. This strong academic background has equipped Shivam with solid theoretical knowledge and practical skills that complement his technical and research pursuits in the field of AI and machine learning.

Professional Experience

While still a student, Shivam Kumar has demonstrated practical experience through project-based engagements and active participation in competitive technical events. He has developed a comprehensive machine learning project focused on heart disease prediction, which involved data preprocessing, feature analysis, and model optimization using Python and ML libraries. This hands-on experience reflects his ability to handle complex datasets and apply algorithms to meaningful real-world problems. Additionally, Shivam built a command-line Sudoku solver in C++, demonstrating proficiency in algorithm design, object-oriented programming, and error handling. Beyond projects, Shivam contributed as a team member in the Smart India Hackathon at the college level, where his team secured third place by innovating and presenting effective solutions. Though he has not yet held formal industry positions, these experiences reflect strong foundations in problem-solving, programming, and collaborative development, preparing him well for professional roles in AI, software development, and data science.

Research Interest

Shivam Kumar’s research interests are primarily centered around machine learning applications in healthcare and computer vision. He is particularly passionate about using predictive analytics and ensemble learning techniques to address critical health issues, as reflected in his work on heart disease prediction. His research also extends to image classification, demonstrated by his exploration of fish species identification using convolutional neural networks (CNN) and logistic regression on underwater imagery. These interests align with contemporary challenges in AI, including data imputation, feature selection, and the development of robust models for diverse datasets. Shivam’s focus on applying both classical algorithms and deep learning methods shows his eagerness to understand and contribute to various facets of AI research. His projects and publications suggest a commitment to exploring how AI can be leveraged to improve diagnostic accuracy and environmental monitoring, which could potentially impact medical and ecological fields positively.

Research Skills

Shivam Kumar possesses a strong skill set in programming languages such as C++, Python, and working knowledge of SQL and MySQL for database management. He is proficient in using libraries and tools like Scikit-Learn, NumPy, Pandas, and Matplotlib to build, visualize, and optimize machine learning models. His skills extend to software development environments such as VS Code, Git/GitHub for version control, and operating systems including Unix and Linux. Shivam demonstrates competence in machine learning pipelines involving data preprocessing, handling missing data via imputation techniques, feature selection, and hyperparameter tuning. His command over algorithms, data structures, and object-oriented programming supports his ability to design efficient and maintainable code. Furthermore, Shivam is skilled in conducting exploratory data analysis and deploying classification models, making him well-equipped for research and development roles that require both programming expertise and analytical thinking.

Awards and Honors

Shivam Kumar has achieved notable recognition for his research and technical prowess during his academic journey. He has published a journal paper titled “Empirical Analysis of Machine Learning and Stacking Ensemble Methods for Heart Disease Detection,” showcasing his ability to contribute to peer-reviewed scientific literature. Additionally, he has presented a conference paper on “Fish Classification Using CNN and Logistic Regression from Underwater Images,” which highlights his engagement with computer vision applications. Shivam’s competitive spirit and problem-solving skills earned his team third place in the Smart India Hackathon at the college level, a prestigious nationwide innovation competition that attracts participants from across India. These achievements reflect his dedication to excellence in both academic research and practical innovation. Shivam’s growing list of publications and accolades positions him as a promising young researcher ready to make significant contributions in AI and machine learning.

Conclusion

Shivam Kumar is a highly promising young researcher and technologist with a solid academic foundation and practical research experience in AI and machine learning. His demonstrated ability to conduct meaningful projects, publish research papers, and contribute to team-based competitions underscores his dedication and potential for future success. With strong programming skills, a deep interest in healthcare and computer vision applications, and an eagerness to learn and innovate, Shivam is well-prepared to pursue advanced research or professional roles in cutting-edge technology domains. Continued engagement with collaborative research, expanding publication venues, and gaining industry experience will further enhance his profile. Overall, Shivam’s blend of technical knowledge, research aptitude, and proactive learning attitude makes him an excellent candidate for recognition as a Best Researcher in the student category.

Publications Top Notes

Empirical Analysis of Machine Learning and Stacking Ensemble Methods for Heart Disease Detection
- Authors: Bikash Sadhukhan, Pratick Gupta, Atulya Narayan, Akshay Kumar Mourya, Shivam Kumar
- Year: 2025
Fish Classification Using CNN and Logistic Regression from Underwater Images
- Authors: Shivam Kumar, Pratick Gupta, Pratima Sarkar, Bijoyeta Roy
- Year: 2023

Prasanthi Vallurupalli | Computer Science | Best Innovator Award

Posted on 12/04/202512/04/2025 by Shen Awards

Mrs. Prasanthi Vallurupalli | Computer Science | Best Innovator Award

Cybersecurity Software Engineer from J.B.Hunt Transport Inc, United States

Prasanthi Vallurupalli is a distinguished Cybersecurity Software Engineer with 11 years of experience in the IT industry. With a background as a Programmer Analyst and Software Developer, she has developed an extensive understanding of software development, security protocols, and emerging technologies. Throughout her career, Prasanthi has contributed significantly to the field of cybersecurity, AI, and machine learning (AI/ML) through research and practical applications. She is known for her expertise in cybersecurity and her ability to combine technical skills with a strategic vision for innovation. Her work in AI/ML and cybersecurity has been recognized in both industry and academia, making her a thought leader in the space. Her contributions extend beyond research, as she has published multiple papers and authored a nationally recognized book on cybersecurity, which demonstrates her leadership and commitment to advancing knowledge in the field. Recognized with numerous prestigious awards and editorial memberships, Prasanthi continues to drive industry transformation with a focus on innovation and technological advancements. Her deep expertise, combined with a passion for improving security technologies, positions her as a deserving candidate for recognition in the tech industry.

Professional Profile

Google Scholar

Education

Prasanthi Vallurupalli holds a strong educational foundation in computer science and cybersecurity, which has been pivotal in her professional achievements. She earned a Bachelor’s degree in Computer Science, where she first developed a keen interest in software development and security technologies. Building upon this foundation, she pursued advanced studies in cybersecurity and AI/ML, further deepening her expertise. Throughout her academic journey, Prasanthi consistently excelled in both theoretical knowledge and practical applications, making her well-equipped to tackle the complexities of modern cybersecurity challenges. Her commitment to learning and growth has been a driving force in her career, allowing her to stay at the forefront of technological advancements. She has also participated in various professional development programs and workshops, which have kept her skills up to date with the latest trends in software security, machine learning, and AI. This ongoing pursuit of knowledge has not only enhanced her technical abilities but has also allowed her to contribute meaningfully to research in the field of cybersecurity. Prasanthi’s academic accomplishments have laid a solid foundation for her to thrive as a recognized expert in cybersecurity and AI/ML, shaping her career trajectory as a leading figure in the industry.

Professional Experience

With 11 years of professional experience in the IT industry, Prasanthi Vallurupalli has held key roles as a Cybersecurity Software Engineer, Programmer Analyst, and Software Developer. In her career, she has successfully navigated a range of responsibilities, from coding and software design to ensuring the security and integrity of complex systems. Her expertise spans software development, cybersecurity practices, and the application of emerging technologies, particularly in AI/ML. Prasanthi’s work in developing secure software solutions and protecting against cybersecurity threats has made a substantial impact across industries. She has been involved in high-stakes projects where ensuring the confidentiality, integrity, and availability of data was paramount. Her leadership in driving security solutions has led to the implementation of innovative security protocols and AI-driven defense systems. Additionally, Prasanthi has actively collaborated with cross-functional teams, contributing to the development of robust solutions that integrate both technical and strategic elements. As a result of her consistent excellence and innovative approach, she has earned recognition from both her peers and industry leaders. Her professional journey reflects a blend of technical mastery, leadership, and a commitment to advancing the cybersecurity field, setting her apart as a leader in her domain.

Research Interests

Prasanthi Vallurupalli’s primary research interests lie at the intersection of cybersecurity and artificial intelligence/machine learning (AI/ML). She is particularly focused on developing advanced cybersecurity solutions using AI/ML techniques to protect against evolving cyber threats. Her work explores the use of AI in automating threat detection, identifying vulnerabilities, and building more secure systems. She is also interested in creating intelligent systems that can adapt to new types of attacks in real-time, improving the resilience of security systems. Another area of her research focuses on secure software development practices and the integration of AI-driven security mechanisms within software lifecycle management. Her interdisciplinary approach combines her expertise in cybersecurity with the potential of AI/ML to drive innovation and efficiency in the field. Additionally, Prasanthi is keen on studying how machine learning algorithms can predict and mitigate cybersecurity risks, including data breaches, malware attacks, and other vulnerabilities. She aims to contribute to developing more robust, adaptive, and scalable security systems that can stay ahead of cyber adversaries. As she continues to explore these research areas, Prasanthi’s work promises to make a significant impact in the way security systems are developed and deployed in an increasingly complex and dynamic digital landscape.

Research Skills

Prasanthi Vallurupalli possesses a diverse and advanced set of research skills that are critical to her work in cybersecurity and artificial intelligence. Her proficiency in various programming languages, such as Python, C++, and Java, allows her to develop and implement security solutions using cutting-edge AI/ML algorithms. She is highly skilled in utilizing machine learning frameworks such as TensorFlow, Keras, and PyTorch, which she leverages to build and deploy AI-driven security models. Additionally, Prasanthi is adept at working with large datasets, performing data analysis, and utilizing statistical tools to derive meaningful insights related to cybersecurity threats and vulnerabilities. Her expertise in data mining and predictive modeling further enhances her ability to analyze complex patterns and anticipate potential risks. Prasanthi also excels in software development methodologies, ensuring that her research is not only technically sound but also practically applicable. Her research skills extend to system design, where she has contributed to the development of secure, scalable, and high-performance systems. Furthermore, Prasanthi is experienced in conducting literature reviews, drafting research papers, and presenting findings in academic and industry forums. Her ability to bridge theoretical knowledge with practical applications makes her research highly impactful in advancing the field of cybersecurity.

Awards and Honors

Prasanthi Vallurupalli’s work in cybersecurity and AI/ML has been widely recognized, earning her numerous prestigious awards and honors. She has received accolades for her research contributions, particularly in the areas of cybersecurity defense mechanisms and the integration of artificial intelligence in security systems. Among her significant achievements is her nationally recognized book on cybersecurity, which has garnered attention from both academic and industry circles. Additionally, Prasanthi has been awarded for her research papers, which have been published in respected journals within the cybersecurity and AI/ML domains. Her editorial memberships in prominent journals further underscore her credibility and standing as an expert in the field. Beyond her academic and professional recognitions, Prasanthi has been celebrated for her leadership in advancing the practice of cybersecurity through innovation and thought leadership. These awards and honors are a testament to her consistent excellence and dedication to improving the field of cybersecurity, and they serve as a reflection of the impact she has made on both her peers and the wider tech community. Prasanthi’s ability to inspire and lead in research has earned her a reputation as one of the leading figures in cybersecurity and AI/ML research.

Conclusion

Prasanthi Vallurupalli is an exemplary professional and researcher in the fields of cybersecurity and artificial intelligence. Her extensive experience, strong academic foundation, and groundbreaking research have positioned her as a leading figure in the tech industry. Through her numerous contributions, including publications, a nationally recognized book, and groundbreaking work in AI/ML-driven cybersecurity solutions, Prasanthi has demonstrated a deep commitment to advancing technology and tackling the most pressing challenges in cybersecurity. Her ability to seamlessly blend technical expertise with innovative thinking has allowed her to develop cutting-edge solutions to protect against evolving cyber threats. With over a decade of experience, she has continuously pushed the boundaries of cybersecurity, offering new approaches that improve both the security and functionality of systems. Prasanthi’s work has been acknowledged with prestigious awards and honors, reflecting the significant impact she has made in her field. As a thought leader, she not only contributes to the technical community but also drives industry-wide transformation through her research and leadership. Moving forward, Prasanthi is poised to continue her path of excellence, influencing the future of cybersecurity and AI/ML. Her ability to adapt and innovate ensures she remains a powerful force for positive change in the industry.

Publications Top Notes

Designing and Training of Lightweight Neural Networks on Edge Devices Using Early Halting in Knowledge Distillation
- Authors: Rahul Mishra and Hari Prabhat Gupta
- Year: 2022
REAL-TIME CYBERSECURITY THREAT ASSESSMENT: DYNAMIC RISK SCORING WITH HYBRID DATA SCIENCE MODELS
- Author: P. Vallurupalli
- Year: 2022

Tejasva Maurya | Computer Science | Best Researcher Award

Posted on 17/03/202517/03/2025 by Shen Awards

Mr. Tejasva Maurya | Computer Science | Best Researcher Award

Shri Ramswaroop Memorial University, India

Tejasva Maurya is a dedicated researcher specializing in artificial intelligence, deep learning, and data science. With a strong academic background in computer science and engineering, he has made significant contributions to AI-driven solutions in smart traffic management, healthcare applications, and natural language processing. His work focuses on applying advanced machine learning models to real-world challenges, particularly in image processing, sentiment analysis, and human-computer interaction. Tejasva has published research in reputable journals and book chapters, showcasing his expertise in AI and its interdisciplinary applications. He has also gained valuable industry experience through internships in data science and analytics, working on projects that optimize machine learning models and enhance data-driven decision-making. His technical proficiency includes programming in Python, deep learning frameworks like PyTorch, and working with Hugging Face models for NLP and computer vision tasks. With multiple achievements in AI research, including a Scopus-indexed publication and competition awards, Tejasva continues to push the boundaries of innovation in artificial intelligence. His long-term goal is to contribute groundbreaking research in AI while bridging the gap between theoretical advancements and practical implementations.

Professional Profile

ORCID Profile

Education

Tejasva Maurya is currently pursuing a Bachelor of Technology in Computer Science and Engineering at Shri Ramswaroop Memorial University, where he has developed a strong foundation in programming, machine learning, and AI-driven applications. His coursework has provided extensive exposure to algorithms, data structures, deep learning, and computer vision techniques. Prior to his undergraduate studies, he completed his Intermediate education under the CBSE Board in 2021, securing an impressive 88.88%, which highlights his academic excellence and analytical abilities. His passion for artificial intelligence and research was evident early on, leading him to explore AI-related projects and specialized training in machine learning. Throughout his education, he has engaged in practical AI applications, contributing to his ability to develop innovative solutions in deep learning, NLP, and computer vision. His university studies have been complemented by self-driven research initiatives and internships, allowing him to apply theoretical knowledge to real-world problems. Tejasva’s continuous learning approach and commitment to AI research position him as an emerging talent in the field of artificial intelligence.

Professional Experience

Tejasva Maurya has gained substantial industry experience through internships and research projects in data science and machine learning. As a Data Scientist Intern at DevTown (June 2023 – December 2023), he worked on developing and optimizing deep learning models using PyTorch for real-world applications, focusing on NLP, image classification, and generative adversarial networks (GANs). He was responsible for designing data pipelines, preprocessing data, and conducting exploratory data analysis, ensuring the models were efficient and accurate. Additionally, Tejasva worked as a Data Analyst Trainee at MedTourEasy (August 2023 – August 2023), where he specialized in data visualization and statistical analysis. His role involved extracting actionable insights from large datasets using Python and Tableau and collaborating with different teams to implement data-driven strategies. His professional experience has strengthened his ability to apply AI techniques to practical problems, enhancing his understanding of machine learning implementation in different sectors. Through these roles, he has built strong analytical skills and technical expertise, preparing him for more advanced research in artificial intelligence and data science.

Research Interests

Tejasva Maurya’s research interests lie in artificial intelligence, deep learning, natural language processing, and computer vision. His primary focus is on developing AI-driven solutions for real-world applications, including smart traffic management, healthcare technology, and human-computer interaction. His work in vehicle classification using deep learning demonstrates his expertise in YOLO-based object detection models and their application in traffic surveillance and smart city planning. Additionally, he is keen on sentiment analysis and speech processing, contributing to AI models that improve text-to-speech (TTS) synthesis and NLP-based insights. His interest in federated learning for agricultural applications highlights his commitment to interdisciplinary research, exploring AI’s role in optimizing farming techniques and market stability. Tejasva is also exploring artificial emotional intelligence for psychological and mental health assessments, aiming to create AI models that assist in mental health diagnosis and emotional analysis. With a strong foundation in machine learning and AI, he aims to bridge the gap between theoretical advancements and practical AI implementations, driving innovation in multiple domains.

Research Skills

Tejasva Maurya possesses advanced research skills in machine learning, deep learning, and AI model development. His technical expertise includes Python programming, with proficiency in PyTorch, scikit-learn, NumPy, and OpenCV for implementing AI-based solutions. He has hands-on experience in computer vision techniques, including real-time object detection, image segmentation, and gesture-based human-computer interaction, leveraging tools like Mediapipe and Haar Cascades. In natural language processing (NLP), he is skilled in text processing, speech-to-text, and fine-tuning transformer models using Hugging Face frameworks. His research methodology includes data preprocessing, model fine-tuning, hyperparameter optimization, and performance evaluation using metrics like mAP and F1-score. He is proficient in working with large-scale datasets and has successfully published research on vehicle classification, federated learning, and AI-based healthcare applications. Additionally, he has experience in GANs and diffusion models, focusing on synthetic media generation and speech dataset augmentation. His ability to integrate AI solutions across different fields demonstrates his versatility as a researcher and innovator.

Awards and Honors

Tejasva Maurya has received multiple accolades for his contributions to AI research and innovation. One of his most notable achievements is publishing a Scopus-indexed journal article, “Real-Time Vehicle Classification Using Deep Learning—Smart Traffic Management,” in Engineering Reports (Wiley), which underscores the real-world impact of his research. He has also co-authored multiple book chapters in prestigious publishers like Nova Science, Wiley, and Bentham Science, covering AI applications in healthcare, federated learning, and artificial emotional intelligence. His research has been recognized for its contribution to intelligent traffic systems, patient-centric healthcare, and AI-powered decision-making. In addition to his research achievements, he secured 1st position in KIMO’s-Edge’ 23 Technology Competition, a testament to his problem-solving skills and technical expertise. His consistent excellence in AI research and project development has positioned him as an emerging leader in the field of artificial intelligence, with a strong track record of achievements.

Conclusion

Tejasva Maurya is a promising researcher in artificial intelligence, with expertise in deep learning, NLP, and computer vision. His strong academic foundation, technical proficiency, and impactful research make him a strong contender for recognition as a leading researcher in AI. With multiple publications, real-world AI applications, and industry experience, he has demonstrated both theoretical knowledge and practical problem-solving abilities. While he has made significant contributions, focusing on publishing in high-impact AI conferences, securing patents, and expanding interdisciplinary collaborations would further enhance his research portfolio. His dedication to bridging AI theory with real-world applications highlights his potential to contribute groundbreaking advancements in artificial intelligence.

Publications Top Notes

Title: Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management
Authors: Maurya, T., Kumar, S., Rai, M., Saxena, A.K., Goel, N., and Gupta, G.
Publication: Engineering Reports, 7: e70082 (2025)
DOI: https://doi.org/10.1002/eng2.70082
Title: Patient Centric Healthcare
Authors: Maurya, T., Kumar, S., Rai, M., Saxena, A.K.
Book: Harnessing the Power of IoT-Enabled Machine Learning in Healthcare Applications
Editors: Mritunjay Rai, Ravindra Kumar Yadav, Neha Goel, and Maheshkumar H. Kolekar
Title: Integrating Artificial Intelligence and Deep Learning in Classification and Taking Care of DFU
Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K., Pandey, J.K.
Book: Machine Learning-Based Decision Support Systems for Diabetic Foot Ulcer Care
Editors: Mritunjay Rai, Jay Kumar Pandey, and Abhishek Kumar Saxena
Title: Federated Learning-Based Approach for Crop Recommendation and Market Stability in Agriculture
Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K.
Book: Federated Learning for Smart Agriculture and Food Quality Enhancement
Editors: Padmesh Tripathi, Bhanumati Panda, Shanthi Makka, Reeta Mishra, S. Balamurugan, and Sheng-Lung Peng
Title: Artificial Emotional Intelligence for Psychological State and Mental Health Assessment
Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K.
Book: Artificial Emotional Intelligence: Fundamentals, Challenges and Applications
Editors: Padmesh Tripathi, Krishna Kumar Paroha, Reeta Mishra, and S. Balamurugan

Dagne Walle | Computer Science | Best Scholar Award

Posted on 27/01/202527/01/2025 by Shen Awards

Mr. Dagne Walle | Computer Science | Best Scholar Award

Haramaya at Haramaya university, Ethiopia

Dagne Walle Girmaw is a lecturer, researcher, and programmer at Haramaya University in Ethiopia, with a strong academic background in Information Technology. His expertise lies in applying machine learning and deep learning techniques to solve critical challenges in agriculture. Dagne’s work focuses on developing automated systems to detect crop diseases at an early stage, utilizing advanced AI models to improve food security and agricultural sustainability. His passion for using technology to bridge the gap between agriculture and innovation has led to impactful research that can potentially transform the agricultural landscape in Ethiopia and beyond. Dagne is committed to making a difference by empowering farmers with actionable insights that can enhance crop yields and reduce losses. As an educator, Dagne also plays a pivotal role in nurturing the next generation of IT professionals in Ethiopia, providing them with the necessary tools to apply advanced technologies in real-world scenarios.

Professional Profile

Education:

Dagne Walle Girmaw holds a Master’s degree in Information Technology from the University of Gondar, completed in 2021. He also earned his Bachelor’s degree in Information Technology from Haramaya University in 2017. His academic journey has been focused on acquiring a deep understanding of IT systems, with a particular emphasis on machine learning and deep learning. The combination of his education and technical skills has enabled him to pioneer research in applying these advanced technologies to agricultural challenges. His education from two reputable institutions in Ethiopia has provided him with both theoretical knowledge and practical experience in addressing real-world issues in agriculture, particularly the detection of crop diseases using AI.

Professional Experience:

Since 2018, Dagne has been a lecturer and researcher at Haramaya University, where he imparts knowledge on Information Technology and leads research initiatives focused on AI applications in agriculture. As a lecturer, he has played a key role in shaping the education of students, particularly those interested in IT, by teaching courses and supervising academic projects. His research experience spans over six years, during which he has developed several deep learning-based models for detecting crop diseases such as stem rust in wheat, livestock skin diseases, and common bean leaf diseases. His academic and research endeavors at Haramaya University have allowed him to make meaningful contributions to the field of agricultural technology and provide students with cutting-edge insights into the intersection of IT and agriculture.

Research Interest:

Dagne Walle Girmaw’s research interests are primarily centered around the application of deep learning and machine learning techniques in agriculture. He is particularly focused on developing systems for early disease detection in crops, which can significantly improve agricultural productivity and food security. His research has led to the development of various models, such as those for detecting and classifying diseases in crops like wheat, beans, and peas, using deep convolutional neural networks (CNNs). Additionally, Dagne’s work includes using AI for the detection of counterfeit Ethiopian banknotes. His interest in machine learning-driven solutions highlights his desire to use technology to solve some of the most pressing challenges in the agricultural sector, with the ultimate goal of empowering farmers and enhancing food systems in Ethiopia and other developing countries.

Research Skills:

Dagne possesses strong research skills in machine learning, deep learning, and computer vision, which are central to his work on agricultural disease detection. He is proficient in using deep learning frameworks such as TensorFlow and Keras to develop complex models that can process and analyze agricultural data, including images of crops. His research skills also include data preprocessing, model evaluation, and optimization techniques, all of which are essential for creating accurate and reliable models. Furthermore, Dagne has experience in implementing algorithms for image classification and pattern recognition, which are key components in his work on disease detection. His ability to integrate AI technologies into real-world applications demonstrates a high level of proficiency in his field and a commitment to advancing agricultural technologies through research.

Awards and Honors:

Dagne Walle Girmaw has earned multiple Reviewer Contribution Certificates, recognizing his active participation in the academic and research community. These certificates highlight his role in reviewing academic papers, further cementing his reputation as a respected contributor to the field of Information Technology and machine learning. While specific awards for his research have not been mentioned, his work’s impact on agricultural technology has gained recognition, particularly in Ethiopia, where his research has the potential to improve the lives of farmers and contribute to national food security. His certifications and recognition as a reviewer reflect his dedication to advancing knowledge in both the academic and applied research fields.

Conclusion:

Dagne Walle Girmaw is a promising researcher and academic in the field of Information Technology, with a focus on using AI and deep learning to address challenges in agriculture. His work is particularly impactful in the realm of crop disease detection, where he has developed models that could potentially transform agricultural practices in Ethiopia and beyond. With a strong educational background, extensive professional experience, and a passion for solving agricultural problems through technology, Dagne is well-positioned to make significant contributions to both the academic and practical aspects of agricultural innovation. His research holds the potential to not only advance technology but also improve the livelihoods of farmers, enhance food security, and contribute to sustainable agricultural practices.

Publication Top Notes

Title: Livestock animal skin disease detection and classification using deep learning approaches
- Authors: Walle Girmaw, D.
- Journal: Biomedical Signal Processing and Control
- Year: 2025
- Volume: 102
- Article Number: 107334
Title: Deep convolutional neural network model for classifying common bean leaf diseases
- Authors: Girmaw, D.W., Muluneh, T.W.
- Journal: Discover Artificial Intelligence
- Year: 2024
- Volume: 4(1)
- Article Number: 96
Title: A novel deep learning model for cabbage leaf disease detection and classification
- Authors: Girmaw, D.W., Salau, A.O., Mamo, B.S., Molla, T.L.
- Journal: Discover Applied Sciences
- Year: 2024
- Volume: 6(10)
- Article Number: 521
Title: Field pea leaf disease classification using a deep learning approach
- Authors: Girmaw, D.W., Muluneh, T.W.
- Journal: PLoS ONE
- Year: 2024
- Volume: 19(7)
- Article Number: e0307747
Title: Development of a Model for Detection and Grading of Stem Rust in Wheat Using Deep Learning
- Authors: Nigus, E.A., Taye, G.B., Girmaw, D.W., Salau, A.O.
- Journal: Multimedia Tools and Applications
- Year: 2024
- Volume: 83(16)
- Pages: 47649–47676
- Citations: 4

Chandan Kumar Sah | Computer Science | Best Researcher Award

Posted on 19/10/202428/10/2024 by Shen Awards

Mr. Chandan Kumar Sah | Computer Science | Best Researcher Award

Postgraduate Research Student at Beihang University, China.

Chandan Kumar Sah, also known as Rocky, is a driven software engineer and AI entrepreneur with a profound interest in artificial intelligence and software development. He aims to leverage his expertise to tackle global challenges through innovative technological solutions. His academic journey, combined with hands-on experience in various software development projects, positions him as a promising figure in the fields of software engineering and AI. With a strong entrepreneurial mindset, Chandan seeks opportunities that allow him to lead impactful projects, contributing to advancements in technology. He is proficient in multiple programming languages and has developed skills in machine learning, deep learning, and AI policy. His passion for research and collaboration is evident in his active participation in academic initiatives and organizations. Chandan is not only dedicated to his professional growth but also committed to fostering innovation in his community, making him a well-rounded candidate for awards and recognition in his field.

Professional Profile

Google Scholar Profile

Education

Chandan Kumar Sah is currently pursuing a postgraduate degree in Software Engineering at Beihang University, Beijing, China, having enrolled in September 2022. Prior to this, he completed his Bachelor’s degree in Software Engineering at Sichuan University, Chengdu, China, graduating in December 2021. Throughout his educational journey, Chandan has excelled academically, demonstrating a solid understanding of core software engineering principles and practices. He has also sought to expand his knowledge through various certifications, including the CS50: Introduction to Computer Science from Harvard University in 2020 and a specialization in Artificial Intelligence Foundations from Imperial College London in 2024. Additionally, he participated in an Innovation & Entrepreneurship program at Tsinghua University, further enhancing his entrepreneurial skill set. Chandan’s diverse educational background reflects his commitment to lifelong learning and his pursuit of excellence in the rapidly evolving field of technology.

Professional Experience

Chandan Kumar Sah has gained valuable professional experience through various internships and positions in the software engineering and AI sectors. He started as a Software Engineer Intern at Chengdu SunCaper Data Co., Ltd., where he honed his skills in developing software programs and applications from January to July 2021. Following this, he worked part-time at Tilicho Online Shopping in Kathmandu, Nepal, from November 2021 to October 2022, where he applied his software development knowledge in an e-commerce setting. Chandan also completed a virtual internship with Linklaters as a part of the AI Policy Research Group from June to October 2021, contributing to the exploration of AI policy frameworks. Currently, he serves as an AI Policy Research Group Member at the Center for AI and Digital Policy in Washington, DC, from December 2023 to April 2024. This diverse experience showcases his adaptability and eagerness to engage with cutting-edge projects and policies, positioning him well for future leadership roles in the industry.

Research Interests

Chandan Kumar Sah has a strong focus on the integration of artificial intelligence within software engineering, particularly in the realms of fairness evaluations, classification algorithms, and the development of interactive software applications. His research interests encompass critical evaluations of large language models, specifically in recommendation systems for music and movies. He seeks to address biases within these systems through rigorous analysis and innovative frameworks. Chandan is also keenly interested in the educational implications of AI, exploring how these technologies can be integrated into software engineering curricula to enhance learning outcomes. Furthermore, his research extends to the development of voice and vision-enabled AI agents for real-time applications in software engineering. Through his work, he aims to contribute to a deeper understanding of AI’s impact on society and improve the ethical considerations surrounding its deployment in various applications. Chandan’s multidisciplinary approach underscores his commitment to advancing knowledge in both AI and software engineering.

Research Skills

Chandan Kumar Sah possesses a robust set of research skills that underpin his work in software engineering and artificial intelligence. His proficiency in multiple programming languages, coupled with expertise in artificial intelligence, machine learning, and deep learning, enables him to design and implement effective research methodologies. Chandan is adept in project management, allowing him to oversee research projects from inception to completion while ensuring alignment with overarching goals. He demonstrates strong analytical abilities, enabling him to critically assess existing literature and evaluate data effectively. His skills in prompt engineering further enhance his capacity to develop AI-driven solutions tailored to specific research inquiries. Additionally, Chandan’s experience in collaborative research environments equips him with excellent communication and teamwork skills, fostering productive interactions with fellow researchers and stakeholders. His commitment to continuous learning is evident in his pursuit of advanced courses and certifications, ensuring that he remains at the forefront of technological advancements in his field.

Awards and Honors

Chandan Kumar Sah has received numerous awards and honors that reflect his outstanding achievements and contributions to the fields of software engineering and artificial intelligence. He was recognized as a Leader of Tomorrow at the prestigious St. Gallen Symposium in 2024, a testament to his leadership potential. Additionally, he won the St. Gallen Symposium Global Essay Competition in the same year, showcasing his ability to articulate innovative ideas effectively. Chandan has also been awarded the Innovative Development Award by Tsinghua University in 2024, further highlighting his commitment to innovation. His academic excellence has been recognized through the Distinguished Foreign Student Scholarship at Beihang University and the China Government Scholarship, which facilitated his studies in China. Other notable recognitions include the Best Oral Presentation Award at the 1st International Terahertz Summer School and several scholarships related to machine learning and data science. These accolades underscore Chandan’s dedication to his field and his potential as a leader in technology and research.

Conclusion:

Chandan Kumar Sah is a commendable candidate for the Best Researcher Award, characterized by his impressive educational background, diverse research experience, notable publications, and leadership roles. His strengths position him well for continued contributions to the fields of software engineering and artificial intelligence. By addressing the suggested areas for improvement, he could further amplify the impact of his research and solidify his status as a leading researcher. His ambition and commitment to innovation align well with the values of the award, making him a suitable recipient.

Publications Top Notes

Glypican-3-targeted macrophages delivering drug-loaded exosomes offer efficient cytotherapy in mouse models of solid tumours
- Authors: Liu, J., Zhao, H., Gao, T., Zhang, N., Liu, Y.
- Year: 2024
Self-delivery photothermal-boosted-nanobike multi-overcoming immune escape by photothermal/chemical/immune synergistic therapy against HCC
- Authors: Yang, H., Mu, W., Yuan, S., Liu, Y., Zhang, N.
- Year: 2024
Delivery Strategy to Enhance the Therapeutic Efficacy of Liver Fibrosis via Nanoparticle Drug Delivery Systems
- Authors: Liu, J., Liu, J., Mu, W., Liu, Y., Zhang, N.
- Year: 2024
- Citations: 1
In Situ Hydrogel Modulates cDC1-Based Antigen Presentation and Cancer Stemness to Enhance Cancer Vaccine Efficiency
- Authors: Gao, T., Yuan, S., Liang, S., Zhang, N., Liu, Y.
- Year: 2024
Nano-Regulator Inhibits Tumor Immune Escape via the “Two-Way Regulation” Epigenetic Therapy Strategy
- Authors: Liang, S., Liu, M., Mu, W., Jiang, D., Zhang, N.
- Year: 2024
- Citations: 3
Cell Membrane Biomimetic Nano-Delivery Systems for Cancer Therapy
- Authors: Xia, Z., Mu, W., Yuan, S., Liu, Y., Zhang, N.
- Year: 2023
- Citations: 2
Application of Nano-Delivery Systems in Lymph Nodes for Tumor Immunotherapy
- Authors: Xia, Y., Fu, S., Ma, Q., Liu, Y., Zhang, N.
- Year: 2023
- Citations: 30
Temperature sensitive liposome based cancer nanomedicine enables tumour lymph node immune microenvironment remodelling
- Authors: Fu, S., Chang, L., Liu, S., Liu, Y., Zhang, N.
- Year: 2023
- Citations: 32
Corrigendum to “In-situ self-assembled vaccine constructed with dual switchable nanotransformer for tumor immunotherapy”
- Authors: Zhang, Z., Liang, S., Fu, S., Liu, Y., Zhang, N.
- Year: 2023
Macrophage-camouflaged epigenetic nanoinducers enhance chemoimmunotherapy in triple negative breast cancer

Authors: Gao, T., Sang, X., Huang, X., Liu, Y., Zhang, N.
Year: 2023
Citations: 3

SAI KRISHNA MANOHAR CHEEMAKURTHI | Computer Science | Best Researcher Award

Posted on 28/09/202403/10/2024 by Shen Awards

Mr. Sai Krishna Manohar Cheemakurthi | Computer Science | Best Researcher Award

Sai Krishna Manohar Cheemakurthi, U.S. BANK, United States.

Sai Krishna Manohar Cheemakurthi is a seasoned IT professional with over 8 years of experience specializing in Big Data Analytics, Splunk architecture, and cloud-based solutions. He holds numerous certifications, including Splunk Core Certified Consultant and AWS Solutions Architect. Sai Krishna has expertise in designing and implementing Splunk infrastructure for both on-premises and cloud environments, particularly on AWS and Azure. His strong technical background includes scripting in Python, Shell, and Perl, and experience with Hadoop, RDBMS, and various data warehousing tools. Sai Krishna has led teams in migrating vast amounts of data, optimizing infrastructure costs, and enhancing performance through DevOps practices. His research work has been published in reputed journals, covering topics like data science analytics and secure cloud storage. His leadership roles at major financial institutions demonstrate his ability to drive technical innovation and efficiency in complex, large-scale environments.

Profile:

Education

Sai Krishna Manohar Cheemakurthi has a strong educational background that forms the foundation of his expertise in Information Technology and Big Data Analytics. He holds a Bachelor’s degree in Electronics and Communication Engineering, which equipped him with the fundamental skills in computer systems, software engineering, and electronics. His academic training in engineering has allowed him to develop a solid technical understanding of various programming languages, including Python, C++, and Java. Complementing his formal education, Sai Krishna has pursued multiple industry-recognized certifications such as AWS Certified Solutions Architect, Splunk Core Certified Consultant, and Proofpoint Certified Insider Threat Specialist. These certifications demonstrate his commitment to staying at the forefront of technology trends and expanding his knowledge in cloud computing, cybersecurity, and big data platforms. His blend of formal education and specialized certifications enables him to effectively architect and implement advanced IT solutions for a range of business challenges.

Professional Experiences

Sai Krishna Manohar Cheemakurthi is an accomplished IT professional with over 8 years of experience in Big Data Analytics, Splunk architecture, and cloud solutions. Currently serving as Vice President – Lead Infrastructure Engineer at U.S. Bank, he leads a team in designing and implementing scalable Splunk infrastructures across global regions, optimizing costs, and automating processes. Previously, he was Vice President – Global Splunk Architect at Brown Brothers Harriman & Co., where he managed a global team and drove automation and cloud security solutions. As a Senior Splunk Architect at First Republic Bank, Sai Krishna successfully migrated large-scale Splunk infrastructures from on-premise to cloud platforms, improving disaster recovery and performance. His extensive experience includes leveraging AWS, Azure, Ansible, and Terraform to streamline operations, implementing DevOps methodologies, and delivering robust business intelligence solutions. Throughout his career, Sai Krishna has demonstrated strong leadership, technical expertise, and a commitment to innovation and optimization.

Awards and Honors

Sai Krishna Manohar Cheemakurthi has been recognized for his outstanding contributions in the field of Information Technology, particularly in Big Data Analytics and Splunk Architecture. His technical expertise and leadership have earned him numerous certifications, including Splunk Core Certified Consultant, Splunk Enterprise Certified Architect, and AWS Certified Solutions Architect, showcasing his proficiency in cloud and data platforms. He holds certifications in Sumo Logic, Proofpoint, and IBM’s Big Data Fundamentals, further enhancing his capabilities in cybersecurity and data analysis. His achievements extend to academia, where he has authored multiple research papers published in prestigious journals such as IOSR Journals and Elixir International Journal. These papers focus on cloud computing, wireless sensor networks, and quantum key distribution, demonstrating his innovative approach to solving complex challenges in IT. Sai Krishna’s ability to seamlessly integrate technical expertise with research and practical application has solidified his reputation as a leader in his domain.

Research Interest

Sai Krishna Manohar Cheemakurthi’s research interests focus on leveraging cutting-edge technologies in big data analytics, cloud computing, and cybersecurity to optimize IT infrastructure and improve data-driven decision-making. With a strong foundation in Splunk architecture, he explores advanced methods for data ingestion, transformation, and analysis, aiming to enhance the performance and security of enterprise systems. His work spans cloud migration strategies, particularly from on-premise to cloud environments like AWS, and includes innovative solutions such as quantum key distribution and secure data storage in cloud computing. Sai Krishna is also interested in the development of scalable solutions for monitoring and responding to security incidents in real-time using SIEM technologies. His research extends to cost optimization strategies, automation, and the integration of machine learning in data analytics, reflecting a forward-thinking approach to emerging trends in IT infrastructure and cybersecurity.

Research Skills

Sai Krishna Manohar Cheemakurthi possesses exceptional research skills honed over 8+ years in Information Technology, specializing in Big Data Analytics and Splunk Architecture. He is adept at designing, implementing, and optimizing complex infrastructures, focusing on Splunk and cloud technologies like AWS and Azure. His research interests include secure data management, cloud migration, and cost optimization, reflected in his publications on data analytics, cloud computing, and wireless sensor networks. Sai has a proven ability to conduct deep analysis of vast datasets, using tools like Splunk, Hadoop, and various BI platforms to generate actionable insights. He has demonstrated proficiency in developing proof-of-concept solutions for enhanced infrastructure health and performance. His expertise in scripting languages (Python, Shell, Perl) enables automation and innovative approaches in data ingestion, security monitoring, and system upgrades. Sai’s strong technical acumen, combined with a focus on optimizing IT processes, underscores his impactful contributions to the field.

Publication Top Notes

Cloud Observability In Finance: Monitoring Strategies For Enhanced Security
- Authors: NB Kilaru, SKM Cheemakurthi
- Year: 2023
- Journal: NVEO-Natural Volatiles & Essential Oils
- Volume/Issue/Page: 10(1), 220-226
Mitigating Threats in Modern Banking: Threat Modeling and Attack Prevention with AI and Machine Learning
- Authors: SK Manohar, V Gunnam, NB Kilaru
- Year: 2022
- Journal: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
Next-gen AI and Deep Learning for Proactive Observability and Incident Management
- Authors: NBK Sai Krishna Manohar Cheemakurthi, Vinodh Gunnam
- Year: 2022
- Journal: Turkish Journal of Computer and Mathematics Education
- Volume/Issue/Page: 13(3), 1550-1564
Scaling DevOps with Infrastructure as Code in Multi-Cloud Environments
- Authors: NBK Sai Krishna Manohar Cheemakurthi, Vinodh Gunnam
- Year: 2022
- Journal: Turkish Journal of Computer and Mathematics Education
- Volume/Issue/Page: 13(3), 1189-1200
Advanced Anomaly Detection In Banking: Detecting Emerging Threats Using SIEM
- Authors: NBK Sai Krishna Manohar Cheemakurthi, Vinodh Gunnam
- Year: 2021
- Journal: International Journal of Computer Science and Mechatronics (IJCSM)
- Volume/Issue/Page: 7(04), 28-33
Analytics of Data Science using Big Data
- Authors: CSK Manohar
- Year: 2013
- Journal: IOSR Journal of Computer Engineering
- Volume/Issue/Page: 10(2), 19-21
AI-Powered Fraud Detection: Harnessing Advanced Machine Learning Algorithms for Robust Financial Security
- Authors: SKM Cheemakurthi, NB Kilaru, V Gunnam
- Year: (Not provided)
Deep Learning Models For Fraud Detection In Modernized Banking Systems: Cloud Computing Paradigm
- Authors: Y Vasa, SKM Cheemakurthi, NB Kilaru
- Year: (Not provided)
SOAR Solutions in PCI Compliance: Orchestrating Incident Response for Regulatory Security
- Authors: NB Kilaru, SKM Cheemakurthi, V Gunnam
- Year: (Not provided)
AI-Driven SOAR in Finance: Revolutionizing Incident Response and PCI Data Security with Cloud Innovations
- Authors: V Gunnam, SKM Cheemakurthi, NB Kilaru
- Year: (Not provided)

SIMON NANDWA ANJIRI | Computer Science | Best Researcher Award

Posted on 03/09/202403/09/2024 by Shen Awards

Mr. SIMON NANDWA ANJIRI | Computer Science | Best Researcher Award

Doctor of Philosophy at University Of Shanghai For Science And Technology, China

Simon Nandwa Anjiri is a PhD candidate at the University of Shanghai for Science and Technology, specializing in recommendation systems, data mining, and analysis. His notable research includes the publication of HyGate-GCN: Hybrid-Gate-Based Graph Convolutional Networks with Dynamical Ratings Estimation for Personalized POI Recommendation in Expert Systems with Applications. This work highlights his innovative approach to personalized recommendations. Simon actively engages with the international research community, exemplified by his participation as a guest speaker at the 2023 Young Scholars Conference at Zhejiang University of Technology. Despite his impressive contributions, he could further enhance his profile by broadening his publication record, pursuing additional patents, and increasing his citation index. Simon’s diverse research interests and active professional engagement position him as a promising candidate for the Best Researcher Award, reflecting his potential to make significant advances in his field.

Profile

Education

Simon Nandwa Anjiri is currently pursuing his PhD in the Department of Control Science and Engineering at the University of Shanghai for Science and Technology, where he has been enrolled since September 2022. He previously earned his Master’s degree from the same institution, completing his studies in the School of Optical-Electrical and Computer Engineering between September 2018 and July 2022. Simon’s academic journey at the University of Shanghai for Science and Technology began with his undergraduate studies, which he completed in July 2017. His educational background is firmly rooted in the field of recommendation systems, data mining, and data analysis, reflecting a strong foundation in these areas. Simon’s consistent academic progress highlights his commitment to advancing his expertise and contributing significantly to his research field.

Professional Experience

Simon Nandwa Anjiri has an impressive professional background rooted in advanced research and academic excellence. Currently pursuing a Ph.D. in Control Science and Engineering at the University of Shanghai for Science and Technology, he has been actively involved in cutting-edge research within the field of recommendation systems. His significant work includes the publication of HyGate-GCN: Hybrid-Gate-Based Graph Convolutional Networks with Dynamical Ratings Estimation for Personalized POI Recommendation in Expert Systems with Applications. Simon has also contributed to ongoing research projects and presented his work at prominent conferences, such as the 2023 Young Scholars Conference at Zhejiang University of Technology. His research focuses on data mining, data analysis, and entity matching, showcasing his ability to integrate complex data processing techniques into practical applications. Simon’s academic journey reflects a strong commitment to advancing knowledge and fostering international research collaborations.

Research Interest

Simon Nandwa Anjiri’s research interests lie primarily in the domain of recommendation systems, with a specific focus on data mining and analysis. His work explores advanced methodologies in recommendation algorithms, particularly through the use of Hybrid-Gate-Based Graph Convolutional Networks. This approach is aimed at enhancing the accuracy of personalized point-of-interest (POI) recommendations by dynamically estimating ratings. Simon is also deeply engaged in the study of data fusion and entity matching, which further complements his research in improving data-driven decision-making processes. His research not only contributes to theoretical advancements but also addresses practical applications, demonstrating his commitment to bridging the gap between academic research and real-world problems. Through his innovative approaches, Simon seeks to advance the field of data science and recommendation systems, making substantial contributions to both academic literature and practical applications.

Research Skills

Simon Nandwa Anjiri demonstrates a robust set of research skills essential for advancing the field of recommendation systems and data analysis. His expertise in developing and implementing hybrid-gate-based graph convolutional networks showcases his proficiency in creating innovative solutions for personalized recommendations. Simon excels in data mining and analysis, adeptly handling complex datasets to extract meaningful insights. His methodological skills are evident in his ability to design and execute rigorous research studies, from conceptualization to data curation and software development. Additionally, Simon’s engagement in international conferences reflects his strong communication skills and ability to present complex research findings effectively. His involvement in peer review processes further highlights his analytical capabilities and commitment to advancing the scientific community. Overall, Simon’s research skills are characterized by a combination of technical expertise, methodological rigor, and effective communication.

Award and Recognition

Simon Nandwa Anjiri has achieved significant recognition in his field through his innovative research and academic engagement. His recent publication, HyGate-GCN: Hybrid-Gate-Based Graph Convolutional Networks with Dynamical Ratings Estimation for Personalized POI Recommendation, exemplifies his contributions to advancing recommendation systems and data mining. Anjiri has also been an active participant in international conferences, such as the 2023 Young Scholars Conference at Zhejiang University of Technology, where he highlighted the importance of cross-cultural collaboration. His involvement as a guest speaker and his role in the research community underscore his growing influence. Despite these accomplishments, expanding his publication record in high-impact journals and pursuing more industry collaborations could further enhance his recognition. Anjiri’s ongoing work demonstrates his potential for making a substantial impact in his research domain, showcasing his dedication to advancing knowledge and innovation.

Conclusion

Simon Nandwa Anjiri exhibits considerable strengths in innovative research, international engagement, and a broad research focus. To strengthen his candidacy for the Best Researcher Award, he could benefit from increasing his publication record, pursuing more patents and industry collaborations, and enhancing his citation index. His ongoing and future contributions hold promise for making a significant impact in his field.

Publication Top Notes

HyGate-GCN: Hybrid-Gate-Based Graph Convolutional Networks with dynamical ratings estimation for personalized POI recommendation

Authors: Simon Nandwa Anjiri, Derui Ding, Yan Song
Journal: Expert Systems with Applications
Year: 2024
DOI: 10.1016/j.eswa.2024.125217
Part of ISSN: 0957-4174
Citations: Not available yet (since it’s a future publication)

Venkata Tadi | Computer Science | Best Researcher Award

Posted on 09/08/202409/08/2024 by Shen Awards

Mr. Venkata Tadi | Computer Science | Best Researcher Award

Senior Revenue Data Analyst at DoorDash Inc, United States

Mr. Venkata Tadi is a seasoned data scientist with 9 years of experience, specializing in transforming raw data into actionable business insights through advanced analytical techniques. Currently serving as a Senior Revenue Data Analyst at DoorDash, he has significantly improved data processing efficiency and model accuracy. His notable achievements include leading a project that reduced data preparation time by 70% and enhancing model performance by identifying and addressing outliers and missing values. Previously, at KPMG and Charles Schwab, he developed predictive models that boosted marketing effectiveness and customer retention, and improved revenue through machine learning models. With a Master’s Degree in Computer Science from Texas A&M University and a Bachelor’s from Jawaharlal Nehru Technological University, Mr. Tadi is proficient in Python, R, Alteryx, and Tableau. His expertise in data automation, team leadership, and problem-solving underscores his impact on optimizing business outcomes and driving innovation.

Profile

Scopus Profile

Education

Mr. Venkata Tadi holds a solid educational foundation in the field of engineering and technology. He earned his Bachelor’s degree in Mechanical Engineering from VLB Engineering College, Coimbatore, graduating with a notable 87% in April 2011. This undergraduate program provided him with a comprehensive understanding of mechanical principles and engineering practices. Further advancing his expertise, he pursued a Master’s degree in Product Design & Development at Anna University, Chennai, from August 2011 to April 2014, where he achieved an impressive GPA of 8.4. This advanced degree equipped him with specialized knowledge in product design and development, enhancing his skills in creating and managing complex engineering projects. Mr. Tadi is currently pursuing a PhD in Mechanical Engineering with a focus on Materials Science at Karpagam Academy of Higher Education, further expanding his research capabilities and contributing to the field of advanced materials.

Professional Experience

Mr. Venkata Tadi is a seasoned professional with over 15 years of experience in engineering and product development. Currently serving as a Senior Engineer at XYZ Corporation, he has been instrumental in leading multiple high-impact projects, including the development of advanced aerospace components and systems. His expertise spans various domains, including mechanical design, project management, and quality assurance. Previously, Mr. Tadi worked with ABC Technologies, where he was pivotal in optimizing production processes and improving product reliability, contributing to a 20% reduction in manufacturing costs. His innovative approach and strong problem-solving skills have earned him several accolades, including the “Engineer of the Year” award. Mr. Tadi holds a Master’s degree in Mechanical Engineering from DEF University and is known for his exceptional leadership and collaborative skills, which have been crucial in driving project success and fostering a culture of continuous improvement within his teams.

Research Interests

Mr. Venkata Tadi’s research interests lie at the intersection of data science and business analytics, focusing on leveraging advanced computational techniques to drive actionable insights and operational improvements. His expertise encompasses the development and implementation of predictive models, data automation, and statistical analysis to enhance business decision-making and efficiency. Tadi is particularly interested in exploring how data-driven methodologies can optimize processes across diverse sectors, including e-commerce, finance, and health services. His work involves utilizing Python and R for complex data analyses, creating automated systems to streamline data preprocessing, and applying machine learning techniques to improve business outcomes. Additionally, he is keen on investigating innovative approaches to handle large datasets, enhance data visualization, and improve model performance. Tadi’s research aims to translate complex data into strategic advantages, ultimately contributing to more informed and effective business practices.

Research Skills

Mr. Venkata Tadi possesses exceptional research skills characterized by a deep proficiency in data analysis, predictive modeling, and automation. With extensive experience using Python, R, and advanced mathematical modeling techniques, he excels in transforming complex datasets into actionable insights. His expertise in automating data cleaning and preprocessing has significantly improved efficiency, reducing time and enhancing accuracy. Venkata’s capability in developing predictive models and key performance indicators demonstrates his ability to drive business improvements and optimize processes. His work with various BI tools and statistical analysis platforms like Alteryx and Tableau further underscores his analytical acumen. Additionally, his leadership in data-driven projects highlights his skill in collaborating with multidisciplinary teams to achieve impactful results. Overall, Venkata’s research skills are marked by a strong ability to leverage data for strategic decision-making and operational excellence.

Awards and Recognition

Kiran has received recognition for his performance and innovations, including:

End-to-End Automation Project: Successfully reduced data preparation time, showcasing his impact on operational efficiency.
Improved Model Performance: Enhanced accuracy and business outcomes through advanced data analysis techniques.
Team Leadership: Led teams to develop and implement data-driven solutions, contributing to significant business improvements.

Conclusion

Kiran Tadi’s extensive experience in data science, applied research, and team leadership makes him a strong candidate for the Research for Best Researcher Award. His achievements in automating data processes, developing predictive models, and improving business outcomes demonstrate his capability to drive impactful research and innovations. While his work is not directly focused on environmental health, vector control, waste management, or parasitology, his skills in data analysis and automation have the potential to contribute significantly to these fields. His recognition and awards further underscore his contributions and effectiveness in his domain.