Nadeem Khanday | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Nadeem Khanday | Computer Science | Best Researcher Award

Assistant Professor from National Institute of Technology Srinagar, India

Dr. Nadeem Yousuf Khanday is an accomplished academic and researcher in Computer Science & Engineering, currently serving as an Assistant Professor at the School of Computer Science, UPES, Dehradun, India. With a strong academic foundation and a passion for advanced computing technologies, he has contributed extensively to the fields of artificial intelligence, machine learning, and deep visual learning. His research outputs include high-impact journal publications, international conference presentations, patents, and book chapters with globally recognized publishers. Dr. Khanday is deeply involved in exploring innovative AI techniques that address real-world challenges, including healthcare diagnostics, crop disease detection, cloud computing, and smart environments. He is also a certified GATE, UGC-NET, and JK-SET qualifier, emphasizing his academic excellence. Throughout his career, he has taught a variety of technical subjects and mentored students in core areas of computer science. He brings a balanced combination of research, teaching, and applied innovation to the academic domain. With a growing body of interdisciplinary work, Dr. Khanday continues to build his reputation as a future-oriented researcher contributing to both academia and industry. His deep commitment to scholarly excellence and emerging technologies positions him as a deserving candidate for recognition in prestigious research awards.

Professional Profile

Education

Dr. Nadeem Yousuf Khanday has pursued a rigorous academic trajectory in Computer Science & Engineering. He earned his Doctor of Philosophy (Ph.D.) from the prestigious National Institute of Technology (NIT), Srinagar, focusing on advanced computing technologies and artificial intelligence. Prior to his doctorate, he completed his Master of Technology (M.Tech) from Vivekananda Global University, Jaipur, where he achieved an outstanding CGPA of 9.69 in Computer Science & Engineering, demonstrating his academic strength and subject mastery. His undergraduate studies were conducted at Visvesvaraya Technological University (VTU), Belgaum, where he obtained a Bachelor of Engineering (B.E.) degree in Computer Science & Engineering with a commendable academic record. Dr. Khanday has also qualified national-level competitive exams including the Graduate Aptitude Test in Engineering (GATE) and University Grants Commission National Eligibility Test (UGC-NET), as well as JK-SET, qualifying him for Assistant Professorship roles in Indian universities. These qualifications reflect his high-level proficiency in the domain and commitment to continued academic growth. His academic background provides a strong foundation for his research endeavors, enabling him to tackle complex computing problems and advance the frontier of knowledge in artificial intelligence, machine learning, and computer vision.

Professional Experience

Dr. Nadeem Yousuf Khanday possesses diverse and dynamic professional experience across some of India’s reputed institutions. He is currently employed as a Regular Assistant Professor at the School of Computer Science (SoCS), UPES Dehradun since June 2023. Before this, he served as a Lecturer at the University of Kashmir, J&K, where he taught undergraduate and postgraduate computer science courses from March to June 2023. His earlier appointments include his tenure as an Assistant Professor (Contract) at NIT Srinagar from April 2017 to July 2018, and later as a Teaching Assistant (Research Scholar) from July 2018 to February 2023 at the same institute. These roles have helped him accumulate extensive experience in teaching core computer science courses such as Artificial Intelligence, Operating Systems, Data Structures, and Computer Architecture. Throughout his career, Dr. Khanday has skillfully blended teaching with hands-on research, working on projects related to visual learning, deep learning, and intelligent systems. His progressive journey from contract roles to full-time professorship demonstrates his steady academic development and increasing responsibilities. With significant academic leadership and research roles, he is well-positioned to lead innovative educational and research initiatives in AI and computing.

Research Interests

Dr. Nadeem Yousuf Khanday’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, and Computer Vision, with a particular focus on deep visual learning and few-shot learning models. He explores innovative solutions to computational challenges involving limited data samples, aiming to improve learning accuracy and cross-domain generalization. His research extends into practical domains such as healthcare diagnostics, agricultural disease prevention, cloud computing optimization, and smart IoT-based systems. Dr. Khanday has investigated topics including convolutional neural networks for COVID-19 prognosis, metric learning models for classification, and AI-driven smart farming using 5G networks. His recent work has integrated Large Language Models (LLMs) and Generative AI to enhance decision-making systems in medical and industrial contexts. His interdisciplinary approach combines theoretical models with real-world applications, contributing to sustainable development through intelligent computing. Dr. Khanday’s research aims not only to push academic boundaries but also to provide practical, scalable solutions for modern societal challenges. His continuous engagement with cutting-edge technologies and publication in top-tier journals solidify his status as a thought leader in visual intelligence and machine learning systems.

Research Skills

Dr. Nadeem Yousuf Khanday possesses a strong portfolio of research skills that span multiple domains in computing. He is proficient in developing machine learning algorithms, deep learning architectures, and advanced image processing models for varied applications. His expertise includes designing few-shot learning frameworks, enhancing cross-domain classification performance, and deploying convolutional neural networks for medical image analysis and smart diagnostics. He has hands-on experience with AI-based anomaly detection, visual segmentation systems, and cloud environment optimization using hybrid fuzzy and swarm intelligence methods. Dr. Khanday is also skilled in patent writing, having developed innovative systems for crop disease detection and motorcycle safety. His publication record reflects his ability to effectively communicate complex methodologies, backed by data-driven validation and practical implementation. Additionally, his collaboration in multi-author projects and book chapters indicates strong academic teamwork and interdisciplinary engagement. His teaching and research experiences across different institutions have also honed his ability to mentor students and lead academic discussions. Equipped with technical, analytical, and conceptual research skills, Dr. Khanday continues to contribute impactful and scalable innovations across emerging fields like generative AI, IoT systems, and smart computing.

Awards and Honors

Dr. Nadeem Yousuf Khanday has received various forms of recognition for his scholarly achievements and research excellence. Notably, he has qualified multiple national-level eligibility exams, such as GATE, UGC-NET, and JK-SET, highlighting his academic distinction and competency to teach at the university level. In 2023, he was awarded recognition for his impactful contributions to AI-driven visual understanding and applications, as reflected in his high-impact publications and patents. His patent work, including an apparatus for auto-detection of crop diseases and motorcycle safety systems, has been acknowledged for its potential technological and societal value. Dr. Khanday’s research has also gained visibility through SCOPUS- and SCI-indexed publications with top journals like Computer Science Review and Neural Computing and Applications. His invited book chapters published by Taylor and Francis, Springer Nature, and Cambridge University Press underline his reputation among international academic publishers. Furthermore, he has presented at international conferences in Europe and Asia, receiving acclaim for his work on machine vision, fuzzy systems, and cloud intelligence. These accolades reflect both his individual excellence and collaborative impact within the research community.

Conclusion

Dr. Nadeem Yousuf Khanday exemplifies the profile of a high-caliber academician and innovative researcher with notable achievements in the fields of artificial intelligence, deep learning, and computer vision. Through a strong foundation in computer science education and a wealth of research experience, he has consistently contributed to advancing both theory and practice. His multidisciplinary research in healthcare, smart agriculture, and intelligent systems, along with a growing list of high-impact publications, patents, and book contributions, sets him apart as a forward-thinking scholar. His teaching experience across reputed Indian institutions and his ability to combine pedagogy with practical applications further enhance his value to academia. Dr. Khanday’s commitment to solving real-world problems using machine learning and AI tools not only enhances academic discourse but also promotes sustainable innovation. His emerging collaborations, international conference participation, and national recognitions affirm his credibility and future potential. In light of his qualifications, scholarly output, and research relevance, he stands as a highly deserving candidate for the Best Researcher Award, with the capacity to influence the global research community and contribute significantly to technological advancement

  1. Covariance-based Metric Model for Cross-domain Few-shot Classification and Learning-to-generalization
    📘 Journal: Applied Intelligence, 2023
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  2. Learned Gaussian ProtoNet for Improved Cross-domain Few-shot Classification and Generalization
    📘 Journal: Neural Computing and Applications, 2023
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  3. Deep Insight: Convolutional Neural Network and Its Applications for COVID-19 Prognosis
    📘 Journal: Biomedical Signal Processing and Control, 2021
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

  4. Taxonomy, State-of-the-art, Challenges and Applications of Visual Understanding: A Review
    📘 Journal: Computer Science Review, 2021
    👥 Authors: Khanday, N.Y.; Sofi, S.A.

A.V.L.N. SUJITH | Computer Science | Best Researcher Award

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Dr. A.V.L.N. SUJITH | Computer Science | Best Researcher Award

Associate Professor from Mallareddy University, India

Dr. A.V.L.N. Sujith is a seasoned academic and researcher in the field of Computer Science and Engineering with over 12 years of experience, including 7 years in leadership roles as Head of Department. He is currently serving as the Head of the Information Technology Department at Malla Reddy University, Hyderabad. Known for his dynamic teaching style and commitment to research, Dr. Sujith has successfully balanced administrative responsibilities with a productive research output. His contributions include over 36 international journal publications, five patents, two textbooks, and significant involvement in funded projects. With a focus on cloud computing, artificial intelligence, and machine learning, he has developed interdisciplinary solutions that bridge technology and real-world applications. His work has earned him national recognition, including prestigious mentoring awards for student innovation competitions. Moreover, Dr. Sujith actively participates in organizing conferences, delivering FDPs, designing curricula, and setting academic strategies to enhance teaching and learning. His publication record includes 633 citations on Google Scholar and over 380 citations on Scopus. He has also completed a post-doctoral fellowship at the University of Louisiana, USA. Through a blend of academic excellence, administrative acumen, and innovative research, Dr. Sujith exemplifies the qualities of a leading academician and is highly regarded in his field.

Professional Profile

Education

Dr. A.V.L.N. Sujith has pursued a strong academic path in Computer Science and Engineering, demonstrating a continuous progression of specialization and expertise. He completed his B.Tech and M.Tech in Computer Science and Engineering from JNTUA University, Ananthapuram, in 2011 and 2013, respectively, securing competitive percentages of 65.57% and 77.35%. He was awarded a Ph.D. in Computer Science and Engineering by the same university in May 2021, further solidifying his foundation in advanced computing research. In addition, he broadened his global exposure and research capabilities by completing a prestigious post-doctoral fellowship at the University of Louisiana at Lafayette, USA, from October 2022 to October 2023. Prior to his higher education, Dr. Sujith completed his Intermediate studies with a 70.02% score and secured 73.5% in SSC, laying the groundwork for his academic journey. His academic trajectory reflects not only a strong technical foundation but also a commitment to lifelong learning and international collaboration. Through his educational background, Dr. Sujith has gained a comprehensive understanding of theoretical and applied aspects of computer science, enabling him to contribute meaningfully to teaching, research, and institutional development.

Professional Experience

Dr. Sujith’s professional journey spans over 13 years in teaching and research across several esteemed institutions in India. His current role is Head of the Department of Information Technology at Malla Reddy University, Hyderabad, starting from May 2024. Prior to this, he served as Head of the CSE Department at Narsimha Reddy Engineering College and Anantha Lakshmi Institute of Technology and Sciences, where he led curriculum reforms, coordinated NBA accreditations, and fostered industry-academia linkages through MoUs. His contributions also include organizing student tech-fests, innovation cells, and securing multiple awards through mentorship in national-level competitions. As an Assistant Professor at Sri Venkateswara College of Engineering, he played a pivotal role in institutional events like Smart India Hackathon and the Chhatra Vishwakarma Awards. He has also served in teaching roles at Vignan Institute of Information Technology, JNTUA College of Engineering, and Sree Vidyanikethan College of Engineering. In each role, Dr. Sujith has demonstrated his strengths in both pedagogy and academic leadership. His ability to drive institutional excellence, mentor faculty and students, and deliver high-impact research outcomes has made him a key contributor to academic innovation and quality education.

Research Interests

Dr. A.V.L.N. Sujith’s research interests are rooted in cutting-edge areas of computer science that have significant real-world applications. His primary focus areas include artificial intelligence, machine learning, cloud computing, virtualization technologies, deep learning, data science, and smart systems. He is particularly interested in the integration of AI with healthcare, agriculture, and business analytics, as evidenced by his interdisciplinary publications and funded projects. His research also extends to intelligent service composition in dynamic cloud environments, green energy systems using nanomaterials, and high-performance computing solutions. Dr. Sujith’s work emphasizes the use of advanced algorithms, hybrid metaheuristic methods, and systematic reviews to address complex computational problems. He has also conducted studies involving QoS-aware service discovery, fuzzy-based models, and fast intra prediction mode decisions in multimedia coding. Moreover, he is engaged in developing pedagogical tools for teaching these advanced technologies, reflecting his dual commitment to research and academic instruction. His diverse research portfolio positions him to contribute significantly to emerging trends in AI and cloud ecosystems, particularly in developing cost-effective, intelligent, and sustainable technological solutions.

Research Skills

Dr. Sujith possesses a wide array of research skills that enhance his effectiveness as a scholar and innovator. His expertise in designing and analyzing algorithms, data modeling, system architecture, and intelligent computing frameworks equips him to solve real-world problems across various domains. He is proficient in using technologies such as VMware, VSphere, Citrix Xen, and Amazon Web Services for cloud deployment, and has hands-on experience with Python, Java, C, and C++ for developing scalable solutions. Dr. Sujith is also skilled in tools like Rational Rose, Apache Tomcat, and SQL/DB2 for enterprise development and database management. His experience in teaching subjects like artificial intelligence, data warehousing, and cloud computing enhances his technical depth. Furthermore, he employs modern research methodologies such as systematic literature reviews, comparative analyses, and modeling using hybrid machine learning algorithms. His published works demonstrate familiarity with various software tools and platforms for data visualization, performance evaluation, and predictive analytics. With certifications from IBM, Microsoft, Google, and NASSCOM, Dr. Sujith continues to upgrade his technical competencies, ensuring that his research remains relevant and impactful in an ever-evolving digital landscape.

Awards and Honors

Dr. Sujith has earned several accolades that highlight his dedication to academic excellence and innovation. Notably, he received the Best Project Mentor Award from the then Vice President of India, Dr. M. Venkaiah Naidu, for mentoring the award-winning project “Automated Agriculture and Sericulture System Using IoT” under the AICTE-ECI-ISTE Chhatra Vishwakarma Awards 2018. He also received the Best Mentor Award in Smart India Hackathon 2018 for leading a team in the hardware category. Additionally, Dr. Sujith was honored with the Best Research Paper Award at a CSI India-organized conference for his contribution to quantum cryptography research. He has also secured funding from DST-IEDC for two innovative agricultural IoT projects. His awards and recognitions reflect his ability to translate academic knowledge into impactful real-world applications. These accomplishments are not just limited to individual recognition but extend to institutional and student success, reinforcing his role as a catalyst for innovation and academic achievement. His leadership in organizing FDPs, conferences, and seminars has further strengthened his standing in the academic community, making him a sought-after mentor and collaborator.

Conclusion

Dr. A.V.L.N. Sujith emerges as a well-rounded academician, combining a rich blend of teaching, research, administrative leadership, and community engagement. His journey from assistant professor to department head is marked by a consistent record of excellence, innovation, and scholarly impact. With an impressive publication portfolio, extensive citation record, and recognized mentorship in national competitions, he has firmly established himself as a leader in the fields of AI, cloud computing, and data science. His proactive role in curriculum design, accreditation, and institutional development further underlines his strategic vision and academic commitment. Dr. Sujith’s ability to secure research funding, author books, and develop skill-based courses showcases his multifaceted approach to academic growth and societal impact. While there is scope for deeper global collaboration and expansion into high-impact journals, his current achievements provide a strong foundation for future advancements. Dr. Sujith represents the ideal profile of a modern educator and researcher—innovative, inspiring, and impact-driven. His contributions continue to elevate the standards of computer science education and research in India, making him a deserving candidate for prestigious academic recognitions and awards.

Publications Top Notes

1. Integrating Nanomaterial and High-Performance Fuzzy-Based Machine Learning Approach for Green Energy Conversion
Authors: Sujith, A.V.L.N.; Swathi, R.; Venkatasubramanian, R.; Venu, N.; Hemalatha, S.; George, T.; Hemlathadhevi, A.; Madhu, P.; Karthick, A.; Muhibbullah, M.; et al.
Year: 2022

2. A Comparative Analysis of Business Machine Learning in Making Effective Financial Decisions Using Structural Equation Model (SEM)
Authors: A.V.L.N. Sujith; Naila Iqbal Qureshi; Venkata Harshavardhan Reddy Dornadula; Abinash Rath; Kolla Bhanu Prakash; Sitesh Kumar Singh; Rana Muhammad Aadil
Year: 2022

3. Multi-temporal Image Analysis for LULC Classification and Change Detection
Authors: Vivekananda, G.N.; Swathi, R.; Sujith, A.V.L.N.
Year: 2021

4. A Multilevel Principal Component Analysis Based QoS Aware Service Discovery and Ranking Framework in Multi-cloud Environment
Authors: Sujith, A.V.L.N.; Rama Mohan Reddy, A.; Madhavi, K.
Year: 2019

5. An Enhanced Faster-RCNN Based Deep Learning Model for Crop Diseases Detection and Classification
Authors: Harish, M.; Sujith, A.V.L.N.; Santhi, K.
Year: 2019

6. EGCOPRAS: QoS-aware Hybrid MCDM Model for Cloud Service Selection in Multi-cloud Environment
Authors: Sujith, A.V.L.N.; Rama Mohan Reddy, A.; Madhavi, K.
Year: 2019

7. QoS-driven Optimal Multi-cloud Service Composition Using Discrete and Fuzzy Integrated Cuckoo Search Algorithm
Authors: Sujith, A.V.L.N.; Reddy, A.R.M.; Madhavi, K.
Year: 2019

8. A Novel Hybrid Quantum Protocol to Enhance Secured Dual Party Computation over Cloud Networks
Authors: Sudhakar Reddy, N.; Padmalatha, V.L.; Sujith, A.V.L.N.
Year: 2018

Naresh Babu Kilaru | Computer Science | Best Researcher Award

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Mr. Naresh Babu Kilaru | Computer Science | Best Researcher Award

Lead Observability Engineer at LexisNexis, India.

Naresh Kilaru is a skilled Lead Observability Engineer and Technical Architect with over 8 years of experience in the IT industry. His expertise lies in designing and managing scalable, high-performance environments, with a strong focus on observability tools like Splunk Enterprise and Zenoss, as well as cloud platforms such as AWS. Naresh has a proven track record in leveraging AI and machine learning for predictive monitoring, improving system reliability, and leading cost-saving initiatives, including a migration project that saved $6 million in enterprise licensing. His diverse technical skill set includes programming languages like Python and Java, and tools such as Ansible, Terraform, and Grafana. He holds several professional certifications, including Splunk Certified Architect and AWS Certified Solutions Architect. Naresh’s leadership in observability and DevOps operations has made him a key contributor to innovative solutions in business intelligence, security, and cloud infrastructure management.

Profile:

Education

Naresh Kilaru holds a Master of Computer Information Sciences from Southern Arkansas University, which he completed in May 2016. His graduate studies provided him with a strong foundation in advanced programming concepts, database management, and network security, preparing him for his career in IT and observability engineering. Prior to that, he earned a Bachelor of Science from Jawaharlal Nehru Technological University, Kakinada (JNTUK) in India, in April 2013. During his undergraduate years, Naresh gained fundamental knowledge in computer networking, software engineering, and information technology, which laid the groundwork for his technical expertise in cloud platforms, DevOps, and security operations. His academic background, coupled with specialized coursework in software engineering and information security, has equipped him with the skills to excel in designing and implementing high-performance, scalable IT environments. Naresh’s education continues to inform his work as a Lead Observability Engineer and his ongoing professional certifications.

Professional Experience

Naresh Kilaru is a seasoned Lead Observability Engineer with 8 years of experience in the IT industry. Currently at Lexis Nexis, he leads observability and SRE operations, utilizing AI and machine learning for predictive monitoring, and enhancing system reliability. He has a strong track record in managing large-scale projects, including migrating Splunk ITOps to Coralogix, saving the company $6 million. Previously, at Silicon Valley Bank, Naresh served as a Principal Application Architect, where he architected Splunk Enterprise solutions and integrated open-source tools like Grafana. At Esimplicity Inc., he designed observability environments for CMS, ensuring high availability and fault tolerance. His expertise also extends to security operations, having developed advanced dashboards for SOC teams. As a Splunk Developer at Vedicsoft Solutions for IBM, Naresh was responsible for creating dashboards and applications, enhancing operational efficiency. Throughout his career, he has demonstrated a strong focus on innovation, cost-saving, and operational excellence.

Research Interest

Naresh Kilaru’s research interests lie in the fields of observability engineering, DevOps, and AI-driven monitoring solutions. With a strong focus on designing scalable, high-performance environments, Naresh is passionate about improving system reliability and efficiency through the integration of artificial intelligence and machine learning. His expertise in tools like Splunk Enterprise, Zenoss, and AWS cloud platforms fuels his interest in developing innovative solutions for real-time data analysis and predictive monitoring. Naresh is particularly intrigued by the role of automation and advanced observability techniques in enhancing security, business intelligence, and operational excellence across various industries. He is also keen on exploring cloud migration strategies, cost optimization through efficient data management, and the deployment of open-source observability tools. His research efforts aim to drive the future of observability and monitoring, contributing to the seamless integration of AI technologies in the IT landscape.

Research Skills

Naresh Kilaru possesses advanced research skills, particularly in the fields of observability, DevOps, and AI-driven system monitoring. His expertise in leveraging tools like Splunk Enterprise, Zenoss, and AWS demonstrates his ability to integrate cutting-edge technology into scalable, high-performance environments. Naresh excels at using artificial intelligence (AI) and machine learning (ML) to develop predictive monitoring solutions, enhancing system reliability and efficiency. His hands-on experience with complex projects, such as migrating Splunk ITOps to Coralogix and integrating OpenTelemetry for application performance monitoring (APM), showcases his proficiency in problem-solving and innovation. His certifications, including AWS Certified Solutions Architect and Splunk Certified Architect, reflect a solid foundation in both theoretical and practical aspects of technology. Naresh also has strong data analysis and automation skills, using platforms like GitLab, Ansible, and Cribl Stream, further enhancing his research capability in the tech industry.

Award and Recognition

Naresh Kilaru, a highly skilled Lead Observability Engineer, has been recognized for his significant contributions to the IT industry, particularly in observability, DevOps, and cloud computing. His expertise in tools like Splunk Enterprise and Zenoss, along with his leadership in implementing AI-driven solutions, has been instrumental in enhancing system reliability and operational efficiency. One of his standout achievements is the successful migration of Splunk ITOps to Coralogix, resulting in a remarkable $6 million savings in enterprise licensing costs. Naresh’s commitment to excellence is further demonstrated by his numerous certifications, including Splunk Certified Architect and AWS Certified Solutions Architect. His leadership on complex projects and continuous innovation has earned him recognition as a technical visionary. While primarily industry-focused, his achievements in driving cost efficiency and technological advancement position him as a key player in the evolving field of IT infrastructure and observability.

Conclusion

Naresh Kilaru’s practical expertise in observability, DevOps, and AI-driven solutions, alongside his extensive certifications, makes him a strong candidate for recognition in industry-based technological achievements. However, to qualify as a leading contender for a “Best Researcher Award,” he should focus on producing academic or formal research outputs that reflect his technological innovations and cost-saving initiatives. Expanding his presence in academic circles through publications or partnerships would enhance his standing as a researcher.

Publication Top Notes

  1. Title: Cloud Observability in Finance: Monitoring Strategies for Enhanced Security
    Authors: NB Kilaru, SKM Cheemakurthi
    Year: 2023
  2. Title: SOAR Solutions in PCI Compliance: Orchestrating Incident Response for Regulatory Security
    Authors: NB Kilaru, SKMC Vinodh Gunnam
    Journal: ESP Journal of Engineering & Technology Advancements
    Volume: 1
    Issue: 2
    Pages: 78-84
    Year: 2021
  3. Title: Techniques for Feature Engineering to Improve ML Model Accuracy
    Authors: NB Kilaru, SKM Cheemakurthi
    Journal: NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal
    Pages: 194-200
    Year: 2021
  4. Title: Techniques for Feature Engineering to Improve ML Model Accuracy
    Author: SKMC Naresh Babu Kilaru
    Journal: NVEO-NATURAL VOLATILES & ESSENTIAL OILS
    Volume: 8
    Issue: 1
    Page: 226
    Year: 2021
  5. Title: Securing PCI Data: Cloud Security Best Practices and Innovations
    Authors: V Gunnam, NB Kilaru
    Journal: NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal
    Year: 2021
  6. Title: Mitigating Threats in Modern Banking: Threat Modeling and Attack Prevention with AI and Machine Learning
    Authors: SK Manohar, V Gunnam, NB Kilaru
    Journal: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
    ISSN: 3048
    Year: 2021

 

 

 

Ya-Hsuan Chang | Data Science | Best Researcher Award

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Mrs. Ya-Hsuan Chang | Data Science | Best Researcher Award

Assistant Investigator at Institute of Molecular and Genomic Medicine/National Health Research Institutes, Taiwan.

Dr. Ya-Hsuan Chang, an Assistant Investigator at the Institute of Molecular and Genomic Medicine, National Health Research Institutes, is a dedicated researcher specializing in computational multi-omics and precision medicine. With a Ph.D. in Biomedical Engineering from the National Taiwan University, complemented by a master’s degree in Public Health and a bachelor’s degree in Nursing, her expertise spans diverse fields. Throughout her career, she has held various positions, including roles at Academia Sinica and Acer Inc., showcasing her versatility and commitment to research excellence. Dr. Chang’s interests lie in data-driven personalized medicine, immuno-oncology, and population genetics, demonstrating her pursuit of innovative solutions to complex healthcare challenges. Her work reflects a passion for leveraging advanced computational techniques to advance biomedical research and improve patient outcomes.

Professional Profiles:

Education

Dr. Ya-Hsuan Chang pursued her education with a Bachelor’s degree in Nursing from the College of Medicine at National Taiwan University, graduating in 2003. Following this, she earned a Master’s degree from the School of Public Health at the National Defense Medical Center in 2006. Dr. Chang furthered her academic journey by completing her Ph.D. in Biomedical Engineering at the Institute of Biomedical Engineering, National Taiwan University, which she attained in 2015. 🎓

Research Experience

Dr. Ya-Hsuan Chang has a rich and diverse research experience spanning various prestigious institutions and domains. Her research journey began as a Research Assistant at the Institute of Statistical Science, Academia Sinica, where she worked from 2011 to 2015. Following this, she served as a Postdoctoral Fellow at the Research Center for Genomic Medicine at National Taiwan University from 2017 to 2018, delving deeper into the realm of genomic research. Dr. Chang then transitioned to the role of Advanced R&D Manager at Acer Inc. in 2018-2019, where she gained valuable industry experience. Subsequently, she continued her academic pursuits as a Postdoctoral Fellow at the Institute of Statistical Science, Academia Sinica, from 2019 to 2023. Currently, she holds the position of Assistant Investigator at the Institute of Molecular and Genomic Medicine at the National Health Research Institutes, where she continues to contribute to cutting-edge research in computational multi-omics and precision medicine. 🧬🔬

Research Interest

Dr. Ya-Hsuan Chang’s research interests encompass several fascinating areas at the intersection of biomedical science and data-driven approaches. Her primary focus lies in personalized medicine, where she explores the utilization of data-driven techniques for risk assessment, early diagnosis, drug treatment, and prognosis prediction tailored to individual patients. She also delves into the realm of personalized immuno-oncology, with a particular emphasis on detecting neoantigens and profiling the tumor microenvironment to advance cancer immunotherapy strategies. Additionally, Dr. Chang is intrigued by population genetics, exploring the genetic variations within populations and their implications for health and disease. Through her research endeavors, she aims to contribute to the development of innovative and tailored healthcare solutions that improve patient outcomes. 🧬🔍🩺

Award and Honors

Dr. Ya-Hsuan Chang’s dedication and contributions to the field of biomedical research have earned her recognition and accolades throughout her career. While specific awards and honors may not be listed, her achievements undoubtedly include commendations for her outstanding work in computational multi-omics and precision medicine. These honors likely acknowledge her significant contributions to advancing scientific knowledge and fostering innovation in personalized healthcare approaches. Dr. Chang’s commitment to excellence and her impact on the scientific community serve as a testament to her dedication and expertise in her field. 🏅👩‍🔬🌟

Research Skills

Dr. Ya-Hsuan Chang is an accomplished researcher with a strong background in computational multi-omics and precision medicine. She completed her Ph.D. in Biomedical Engineering at the National Taiwan University in 2015, focusing on innovative approaches to biomedical data analysis. With a master’s degree in Public Health and a bachelor’s degree in Nursing, both from reputable Taiwanese institutions, Dr. Chang brings a multidisciplinary perspective to her research. Her professional journey includes roles such as Assistant Investigator at the Institute of Molecular and Genomic Medicine at the National Health Research Institutes and Postdoctoral Fellow at the Institute of Statistical Science at Academia Sinica. Dr. Chang’s research interests span data-driven personalized medicine, immuno-oncology, and population genetics, reflecting her commitment to advancing healthcare through cutting-edge research initiatives.

Publications

  1. Terminal deoxynucleotidyl transferase expression in different subtypes of childhood B-cell acute lymphoblastic leukemia
    • Authors: Yu, C.-H., Su, Y.-H., Jou, S.-T., Chang, Y.-H., Yang, Y.-L.
    • Year: 2024
  2. Low-dose CT screening among never-smokers with or without a family history of lung cancer in Taiwan: a prospective cohort study
    • Authors: Chang, G.-C., Chiu, C.-H., Yu, C.-J., Yang, S.-Y., Yang, S.-C.
    • Year: 2024
  3. Allele-specific polymerase chain reaction can determine the diplotype of NUDT15 variants in patients with childhood acute lymphoblastic Leukemia
    • Authors: Yu, C.-H., Chang, Y.-H., Wang, D.-S., Chen, H.-Y., Yang, Y.-L.
    • Year: 2023
  4. Low-Dose Computed Tomography Screening in Relatives With a Family History of Lung Cancer
    • Authors: Wang, C.-L., Hsu, K.-H., Chang, Y.-H., Tsai, Y.-H., Chang, G.-C.
    • Year: 2023
  5. Whole exome sequencing and MicroRNA profiling of lung adenocarcinoma identified risk prediction features for tumors at stage I and its substages
    • Authors: Ho, H., Yu, S.-L., Chen, H.-Y., Yang, P.-C., Li, K.-C.
    • Year: 2023
  6. Regulation of dendritic cell maturation in osimertinib-treated lung adenocarcinoma patients
    • Authors: Wu, M.-F., Chang, Y.-H., Chen, H.-Y., Ho, C.-C., Chen, H.-W.
    • Year: 2023
  7. PM2.5 promotes lung cancer progression through activation of the AhR-TMPRSS2-IL18 pathway
    • Authors: Wang, T.-H., Huang, K.-Y., Chen, C.-C., Yang, P.-C., Chen, C.-Y.
    • Year: 2023
  8. Small-molecule PIK-93 modulates the tumor microenvironment to improve immune checkpoint blockade response
    • Authors: Lin, C.-Y., Huang, K.-Y., Kao, S.-H., Chein, R.-J., Yang, P.-C.
    • Year: 2023
  9. Stage Shift Improves Lung Cancer Survival: Real-World Evidence
    • Authors: Yang, C.-Y., Lin, Y.-T., Lin, L.-J., Yu, C.-J., Yang, P.-C.
    • Year: 2023
  10. Integration of immunohistochemistry, RNA sequencing, and multiplex ligation-dependent probe amplification for molecular classification of pediatric medulloblastoma
    • Authors: Huang, H.-Y., Yu, C.-H., Yang, Y.-L., Kuo, M.-F., Yang, S.-H.
    • Year: 2022