Anuradha Choudhury | Computer Science and Artificial Intelligence | Women Researcher Award

Ms. Anuradha Choudhury | Computer Science and Artificial Intelligence | Women Researcher Award

Student at OUTR, india

Anuradha Rani Choudhury is a dedicated and aspiring researcher currently pursuing her Master of Technology at OUTR, Bhubaneswar, with an impressive CGPA of 9.20. She holds a Bachelor’s degree in Technology from ITER, Bhubaneswar, and has demonstrated strong technical acumen through impactful projects in machine learning, including sentiment analysis and disease prediction models, both achieving high accuracy. With certifications in machine learning, web development, and Android development, she exhibits a strong foundation in diverse technological domains. Anuradha has actively participated in seminars and workshops, showcasing her commitment to continuous learning. Her proficiency in programming languages such as Python, Java, and C, along with web technologies, complements her research skills. Additionally, her involvement in extracurricular activities like sports, NCC, and student leadership reflects a well-rounded personality. While she is at an early stage in her research journey, Anuradha shows promising potential for future contributions to the field of technology and applied sciences.

Professional Profile 

🎓 Education of Anuradha Rani Choudhury

Anuradha Rani Choudhury has built a strong academic foundation in the field of technology and engineering. She is currently pursuing her Master of Technology (M.Tech) at Odisha University of Technology and Research (OUTR), Bhubaneswar, maintaining an excellent CGPA of 9.20 (2023–2025). She previously earned her Bachelor of Technology (B.Tech) from ITER, Bhubaneswar, graduating with a CGPA of 7.73 in 2022. Her earlier academic journey includes completing 12th grade (Science) from Stewart Science College, Cuttack under the CHSE Board, scoring 57.5%, and her 10th grade from D.A.V. Public School, Berhampur under the CBSE Board, where she achieved a commendable 83.6%. Her academic progression highlights her consistent dedication and growth in technical education.

💼 Professional Experience of Anuradha Rani Choudhury

Anuradha Rani Choudhury has gained valuable hands-on experience through academic projects and certified training programs in the fields of machine learning, data science, and software development. She successfully led a Sentiment Analysis project in 2024, where she implemented advanced models such as Naïve Bayes, Logistic Regression, SVM, and Neural Networks, achieving an outstanding . In 2023, she developed a Disease Prediction Model using patient physiological data, which delivered an impressive . Additionally, Anuradha has completed certification-based training in Machine Learning (Project Mantra), Web Development (Verzeo), and Android Development (Pixaflip Technologies). Her participation in workshops and seminars, along with her technical proficiency in languages like Python, Java, and SQL, further reflects her readiness for research and real-world problem-solving in the tech industry.

🔬 Research Interest of Anuradha Rani Choudhury

Anuradha Rani Choudhury’s research interests lie primarily in the dynamic fields of Machine Learning, Artificial Intelligence, and Data Science, with a strong inclination toward applying these technologies in healthcare and human-centered applications. She is passionate about exploring predictive modeling, sentiment analysis, and disease diagnosis systems that leverage advanced algorithms to generate actionable insights from complex data. Her academic projects reflect her enthusiasm for building intelligent systems capable of improving decision-making and automation. Anuradha is also interested in the integration of deep learning and neural networks to enhance model accuracy and efficiency. As she progresses in her academic and professional journey, she aims to contribute to impactful, real-world solutions through innovative and ethically grounded research in intelligent technologies.

🏅 Awards and Honors of Anuradha Rani Choudhury

Anuradha Rani Choudhury has been recognized for her diverse talents and active participation in both academic and extracurricular arenas. She earned the 2nd prize in poem writing at the Ganjam Kalaparishad in 2017, showcasing her creative expression and literary flair. In the same year, she also secured the 2nd prize in athletics at D.A.V. Public School, reflecting her athletic spirit and commitment to physical excellence. Additionally, she holds the prestigious NCC “A” Certificate (2013–2015), highlighting her discipline, leadership, and dedication to national service. These honors demonstrate her well-rounded personality, balancing academic rigor with artistic and physical achievements.

Conclusion

Anuradha Rani Choudhury is a promising emerging researcher with a solid academic background, project experience in machine learning, and proactive engagement in technical skill development. However, to be highly competitive for the Best Researcher Award, particularly at national or international levels, she would benefit from Publishing research papers. Involving in long-term, original research with measurable impact. Demonstrating broader research influence and leadership.

📚 Publications Top Noted

  1. Title: Real-time Face Mask Detection in Nuclear Power Plants: A Deep Learning Framework Using Hybrid CNN-MobileNetV2 Architecture
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra, S. Mohanty, S. Mishra
    Year: 2025
    Citation: 0
    Published In: Intelligent Computing Techniques and Applications, pp. 87–91

  2. Title: A Comparative Analysis of Deep Learning Techniques for Face Mask Detection System in Nuclear Power Plant
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra
    Year: 2025
    Citation: 0
    Published In: 2025 10th International Conference on Signal Processing and Communication

  3. Title: Enhancing Lung Cancer Detection by Leveraging Machine Learning Algorithms
    Authors: A.R. Choudhury, S.R. Panda, A.K. Mishra, J. Routray
    Year: 2025
    Citation: 0
    Published In: 2025 10th International Conference on Signal Processing and Communication

  4. Title: Deep Learning Based Automated Lung Cancer Detection from CT Scan Leveraging Transfer Learning
    Authors: A.R. Choudhury, J. Rautray, P. Mishra, M. Kandpal, S.S. Dalai
    Year: 2025
    Citation: 0
    Published In: Procedia Computer Science, Volume 258, Pages 2748–2759

  5. Title: Face Mask Detection System for Safety Assurance in Nuclear Power Facilities from Harmful and Hazardous Substance Using Convolutional Neural Network and Image Processing
    Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra
    Year: 2025
    Citation: 0
    Published In: International Journal of Computer Applications 975, 8887

 

 

 

 

 

 

Yasin Fatemi | Computer Science and Artificial Intelligence | Best Researcher Award

Yasin Fatemi | Computer Science and Artificial Intelligence | Best Researcher Award

Mr Yasin Fatemi, Auburn University, United States

Based on the details provided, Mr. Yasin Fatemi is a highly suitable candidate for a Researcher of the Year Award.

Publication profile

google scholar

Educational Background 📚

Mr. Fatemi has a robust academic foundation with a Ph.D. in Industrial and Systems Engineering from Auburn University, where he has maintained a perfect GPA of 4.0. His ongoing M.Sc. in Data Science further complements his expertise, and he also holds an M.Sc. and B.Sc. in Industrial and Systems Engineering from Tarbiat Modares University and the University of Kurdistan, respectively. This diverse and interdisciplinary educational background supports his innovative research in healthcare and systems optimization.

Research Experience and Contributions 🔬

Mr. Fatemi’s research is both extensive and impactful. His recent work involves using machine learning and network analysis to address critical healthcare issues such as low birth weight prediction, racial disparities in maternal outcomes, and cardiovascular death among liver transplant recipients. These projects showcase his ability to apply advanced analytical methods to real-world problems, significantly contributing to the fields of healthcare and data science. His studies have utilized cutting-edge techniques such as Recursive Feature Elimination, SHapley Additive exPlanations (SHAP), and network feature analysis, highlighting his technical prowess and innovation.

Publications and Academic Output 📝

Mr. Fatemi has authored several peer-reviewed articles, contributing to reputable journals like Frontiers in Public Health and Journal of Multidisciplinary Healthcare. His research on the stress and compensation perceptions of frontline nurses during the COVID-19 pandemic, as well as his work on hospital smart notification systems, demonstrates his commitment to improving healthcare environments and outcomes. His publications reflect his ability to tackle diverse and pressing issues, making him a significant contributor to the academic community.

Technical and Academic Skills 🛠️

Mr. Fatemi’s technical skills are impressive, encompassing data analysis tools like Python, R, and SQL, and specialized software for simulation and optimization. His expertise in machine learning, statistical learning, and network analysis is evident in his research outputs, further establishing his credibility as an innovative researcher.

Conclusion

Mr. Yasin Fatemi’s strong educational background, extensive research experience, and impactful contributions to healthcare and data science make him an excellent candidate for a Best Researcher Award. His ability to apply complex analytical techniques to critical issues in healthcare and his consistent academic excellence underscore his suitability for this recognition.

Publication top notes

Investigating frontline nurse stress: perceptions of job demands, organizational support, and social support during the current COVID-19 pandemic

Listening to the Voice of the hospitalized child: comparing children’s experiences to their parents

The Cost of Frontline Nursing: Investigating Perception of Compensation Inadequacy During the COVID-19 Pandemic

ChatGPT in Teaching and Learning: A Systematic Review

Machine Learning Approach for Cardiovascular Death Prediction among Nonalcoholic Steatohepatitis (NASH) Liver Transplant Recipients

Evaluating a Hospital Smart Notification System in a Simulated Environment: The Method

Machine Learning Approaches for Cardiovascular Death Prediction Among Nash Liver Transplant Recipients

 

 

William Lawless | Computer Science and Artificial Intelligence | Best Researcher Award

William Lawless | Computer Science and Artificial Intelligence | Best Researcher Award

Dr William Lawless, Paine College, United States

W.F. Lawless is a pioneering mechanical engineer known for blowing the whistle on nuclear waste mismanagement in 1983. He earned his PhD in 1992, focusing on organizational failures among leading scientists. Invited to join the DOE’s citizens advisory board at Savannah River Site, he coauthored key recommendations for environmental remediation. His research centers on autonomous human-machine teams, and he has edited nine influential books on AI, including the award-nominated Human-Machine Shared Contexts. With over 300 peer-reviewed publications, he has organized multiple symposia and special issues, contributing significantly to the field of artificial intelligence. 🔬🤖📚

Publication profile

Orcid

Research focus

William Lawless’s research focuses on the dynamics of human-machine collaboration, particularly in the context of autonomy and uncertainty. His work explores how knowledge, risk perception, and interdependence influence the effectiveness of autonomous teams. By examining models that integrate quantum-like principles, he aims to enhance our understanding of decision-making processes within complex systems. His publications highlight the essential tension between knowledge and uncertainty, proposing new frameworks for improving human-machine interactions. This interdisciplinary approach bridges technology and human factors, contributing significantly to fields like robotics, artificial intelligence, and human-computer interaction. 🤖📊🔍

Publication top notes

Shannon Holes, Black Holes, and Knowledge: The Essential Tension for Autonomous Human–Machine Teams Facing Uncertainty

A Quantum-like Model of Interdependence for Embodied Human–Machine Teams: Reviewing the Path to Autonomy Facing Complexity and Uncertainty

Risk Determination versus Risk Perception: A New Model of Reality for Human–Machine Autonomy