Shivam Kumar | Computer Science | Best Researcher Award

Published on 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

  1. 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

  2. Fish Classification Using CNN and Logistic Regression from Underwater Images

    • Authors: Shivam Kumar, Pratick Gupta, Pratima Sarkar, Bijoyeta Roy

    • Year: 2023

 

Wisal Zafar | Computer Science | Best Researcher Award

Published on by Shen Awards

Mr. Wisal Zafar | Computer Science | Best Researcher Award

Lecturer at Cecos university of information technology and emerging sciences, Pakistan.

Mr. Wisal Zafar is a dedicated researcher and lecturer with a strong background in software engineering, focusing on artificial intelligence, machine learning, and deep learning applications in healthcare. Born on March 25, 1999, in Peshawar, Pakistan, he has consistently demonstrated a passion for advancing technology’s role in solving real-world problems. He has developed and published research that leverages machine learning for medical diagnoses, including brain tumor analysis and diabetes prediction. As a lecturer and Electronic Data Processing (EDP) Officer at Iqra National University, he is committed to mentoring students and contributing to the field through both teaching and research. His work is distinguished by his continuous learning, keeping pace with emerging trends in AI and big data. Mr. Zafar’s career is marked by his enthusiasm for interdisciplinary research, integrating software engineering with advancements in health and data science. He is eager to expand his research contributions further through collaborations and innovative projects that address global challenges using advanced technologies.

Professional Profile

Education

Wisal Zafar holds an MS in Software Engineering from Iqra National University, Hayatabad Peshawar, completed in July 2024 with a commendable CGPA of 3.62/4.00. His postgraduate studies provided him with in-depth knowledge of advanced topics like artificial intelligence, data analysis, and big data. Prior to this, he earned a BS in Software Engineering from the same institution in October 2020, with a CGPA of 3.47/4.00, building a strong foundation in software development and computer science principles. His academic journey started with an intermediate qualification from Capital Degree College, Peshawar, where he scored 700 out of 1100 marks, and continued with his matriculation from The Jamrud Model High School, achieving 824 out of 1100 marks. His educational background is characterized by consistent academic performance and a focus on both theoretical and practical aspects of software engineering, which has prepared him for his subsequent roles in academia and research.

Professional Experience

Wisal Zafar currently serves as a Lecturer at Iqra National University, Hayatabad, Peshawar, where he has been teaching various software engineering subjects since January 2023. His areas of instruction include Data Science, Artificial Intelligence, Machine Learning, Data Structures, and Algorithms, allowing him to impart advanced knowledge to students and prepare them for careers in technology. Alongside his role as a lecturer, he also holds the position of Electronic Data Processing (EDP) Officer at the same university, a role he has been fulfilling since October 2021. In this capacity, he manages data processing tasks, ensuring the effective handling of academic data and resources. Previously, he gained practical experience as a Junior Web Developer at Pakistan Online Services Software House, where he worked from November 2020 to April 2021, specializing in web development using PHP, Laravel, JavaScript, and other technologies. This diverse experience in academia and industry has equipped Mr. Zafar with the skills to blend theoretical concepts with real-world applications, making him an effective educator and a valuable contributor to research.

Research Interests

Wisal Zafar’s research interests are centered around artificial intelligence (AI), machine learning (ML), deep learning, and their applications in healthcare and data analysis. He is particularly fascinated by the potential of AI and ML in developing advanced diagnostic tools, aiming to improve medical outcomes through data-driven insights. His recent research projects have explored the use of deep learning techniques like YOLOv8s and U-Net for multi-class brain tumor analysis, integrating detection, localization, and segmentation of tumors using MRI data. Additionally, he has delved into predictive models for diabetes diagnosis using various ML algorithms, such as Decision Trees, K-Nearest Neighbors, Random Forest, Logistic Regression, and Support Vector Machines. His interests extend to big data analytics and the role of data science in enhancing information retrieval and management in medical libraries. Through his work, Wisal Zafar seeks to advance the intersection of technology and healthcare, utilizing cutting-edge algorithms and data processing techniques to solve critical challenges and improve human well-being.

Research Skills

Wisal Zafar possesses a diverse skill set in artificial intelligence, machine learning, data analysis, and big data management, making him adept at tackling complex research challenges. He has extensive experience in using programming languages like Python and C++, which he applies to develop machine learning models and algorithms. His technical expertise includes working with deep learning frameworks, as seen in his research on brain tumor analysis using advanced models such as YOLOv8s and U-Net. Additionally, Wisal has proficiency in cloud computing and handling large datasets, which supports his work in big data analytics and the implementation of data-driven decision-making tools. His hands-on experience as a Research Assistant has further refined his skills in conducting surveys, data preprocessing, and statistical analysis. Mr. Zafar is also skilled in web development using frameworks like Laravel and JavaScript, allowing him to create interactive platforms for research applications. His ability to integrate these skills into interdisciplinary projects makes him a capable researcher with a focus on innovation and problem-solving.

Award Recognition

Wisal Zafar’s dedication to research and academic excellence has earned him recognition in the academic community, though he is still working towards broader award recognitions. His recent research publications, including studies on brain tumor analysis and diabetes prediction using machine learning, have been well-received and published in respected journals. These works have contributed significantly to the fields of AI in healthcare and big data analytics, positioning him as a promising researcher. His role as a Lecturer at Iqra National University also reflects the acknowledgment of his expertise, as he is entrusted with educating the next generation of software engineers. Additionally, Wisal has completed several certified courses from platforms like Coursera, receiving certificates in advanced learning algorithms, deep learning, and image processing with Python, which underscore his commitment to continuous learning. While he may not yet have specific awards, his publications, teaching contributions, and commitment to research excellence serve as strong indicators of his potential for future recognition in the field.

Awards and Honors

Wisal Zafar has demonstrated a commitment to continuous professional development through various certifications and achievements, contributing to his expertise in software engineering and AI. He has completed notable courses such as AI for Everyone and Advanced Learning Algorithms through Coursera, which are associated with respected institutions like DeepLearning.AI and Stanford University. These certifications have enhanced his knowledge of machine learning, deep learning, and image processing, enabling him to apply advanced concepts in his research. While he has not yet received specific formal awards, his role as a Lecturer at Iqra National University and his position as an Electronic Data Processing (EDP) Officer are testaments to his skills and recognition within the academic community. His contributions to research, especially in the areas of AI applications in healthcare, have been acknowledged through the publication of his work in peer-reviewed journals. Wisal Zafar’s ongoing pursuit of excellence, both in research and teaching, positions him as a candidate worthy of future awards and honors in the field of software engineering and AI.

Conclusion:

Wisal Zafar has demonstrated considerable research skills and expertise in the field of software engineering, particularly in applying machine learning and AI to medical problems. His academic background, technical skills, and research publications make him a strong contender for the Best Researcher Award. While he could benefit from diversifying his research and increasing his international presence, his current achievements in AI-driven healthcare solutions and data analytics set a solid foundation for this recognition.

Publications Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Journal: Results in Engineering
    • Year: 2024
    • Volume: 24
    • Article ID: 102994
    • Type: Open access
  2. Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed
    • Authors: Shaukat, Z., Zafar, W., Ahmad, W., Ghadi, Y.Y., Algarni, A.
    • Journal: Healthcare (Switzerland)
    • Year: 2023
    • Volume: 11
    • Issue: 21
    • Article ID: 2864
    • Citations: 1
    • Type: Open access