Madhusmita Das | software engineering | Best Researcher Award

Ms. Madhusmita Das | software engineering | Best Researcher Award

Research Scholar, National Institute of Technology Karnataka, Surathkal, India

Madhusmita Das is a Ph.D. candidate at the Institute of Technology Karnataka, Surathkal, focusing on reliability assessment of safety-critical systems through advanced machine learning models and bio-optimization algorithms. With a solid foundation in data science, she excels in analyzing user behavior and engagement, translating insights into impactful business strategies and research outcomes.

Profile

Scopus

Strengths for the Award

Diverse Research Interests and Publications: Madhusmita Das has a broad range of research interests encompassing machine learning, bio-optimization algorithms, reliability analysis, and verification methods. Her work spans numerous relevant topics, including safety-critical systems, software defect prediction, and reliability assessment of drone systems. This wide-ranging expertise is evident in her substantial number of high-impact publications across various prestigious conferences and journals.

Impactful Contributions: Her research on “Hybrid Bio-Optimized Algorithms for Hyperparameter Tuning in Machine Learning Models” and other related works demonstrates her ability to apply complex algorithms to practical problems, making significant contributions to the field of machine learning and system reliability.

Recognition and Awards: The provisional selection for the “Best Researcher Award” for her work in hybrid bio-optimized algorithms reflects her recognition in the academic community. Her technical paper presentation at state levels and qualified GATE also underscore her expertise and commitment to her field.

Extensive Experience and Skills: Madhusmita’s background in programming, big data technologies, machine learning, and data visualization tools is robust. Her skills in managing research from inception to publication further demonstrate her comprehensive approach and capability.

Areas for Improvement

Research Diversity and Novelty: While her research is extensive, focusing on a few emerging or less explored areas could enhance the novelty of her contributions. This might involve delving into cutting-edge topics like quantum computing applications in machine learning or the integration of AI with emerging technologies.

Broader Impact and Collaboration: Strengthening collaborations with other researchers or institutions could broaden the impact of her work. Collaborations can lead to interdisciplinary research opportunities, potentially increasing the scope and application of her findings.

Public Engagement: Expanding efforts to disseminate research findings to non-specialist audiences or through popular science platforms could enhance the visibility and impact of her work. Engaging in public lectures, webinars, or media could further her influence.

Education 🎓

Madhusmita is pursuing her Ph.D. in Computer Science/Information Technology at the Institute of Technology Karnataka, Surathkal (2019-Present), with a CGPA of 8.67. Her research covers topics such as verification & validation, reliability analysis, and bio-optimization algorithms. She completed her M.Tech. with honors from NIT Raipur in 2012 and her B.Tech. from SOA University, Bhubaneswar, in 2008.

Experience 💼

Madhusmita has served as an Assistant Professor at MVJ College of Engineering, Bangalore (Nov 2013 – Nov 2016), and Sanjeevani College of Engineering, Pune (Jul 2012 – Nov 2013). Her work spans teaching, research, and project mentoring, contributing significantly to the academic and research communities.

Research Interests 🔬

Her research interests include verification and validation methods, formal techniques, risk analysis, system reliability, and software defect prediction. She is also passionate about machine learning and computational intelligence, focusing on bio-optimization algorithms and optimization techniques.

Awards 🏆

Madhusmita was provisionally selected for the “Best Researcher Award” for her work on hybrid bio-optimized algorithms in machine learning, set to be awarded in 2024. She also earned recognition for her state-level presentation on AI in 2011 and qualified GATE in 2010.

Publications Top Notes📚

Hybrid Bio-Optimized Algorithms for Hyperparameter Tuning in Machine Learning Models: A Software Defect Prediction Case Study, Mathematics, 2024, MDPI.

Formal Specification and Verification of Drone System using TLA+: A Case Study, 2022 IEEE/ACIS 23rd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2022, pp. 156-161.

Reliability Assessment of a Drone Communication System using Truncated Markov Analysis, 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023, pp. 1-6.

Fault Tree Analysis: A Review on Analysis, Simulation Tools, and Reliability Dataset for Safety-critical Systems, International Conference on Mining for a Greener Future: Technological developments and Sustainable Practices (ICMFGF 2024), 2024, NITK Surathkal, India.

Safety Assessment of Railway Crossing Junction Via Petri Nets, 5th International Conference on Innovative Trends In Information Technology ICITIIT’24, 2024, IIIT Kottayam, India, pp. 1-8.

Conclusion

Madhusmita Das is a strong candidate for the Best Researcher Award due to her significant contributions to machine learning, data science, and system reliability. Her extensive publication record, impactful research, and recognized achievements highlight her as a leading figure in her field. Addressing areas for improvement, such as exploring novel research avenues and enhancing public engagement, could further strengthen her candidacy and broaden the impact of her work.

Jawad Khan | Software Engineering | Best Researcher Award

Prof Dr.Jawad Khan | Software Engineering | Best Researcher Award

Assistant Professor Gachon University  South Korea

Dr. Jawad Khan is an Assistant Professor at Gachon University, South Korea. With extensive experience in data science and artificial intelligence, Dr. Khan’s work focuses on semantic learning, machine learning, and natural language processing. He has made significant contributions to the fields of text mining, software engineering, and cloud computing. Dr. Khan is dedicated to advancing research in these areas through innovative approaches and interdisciplinary collaboration.

Profile

Scopus

Education

🎓 Dr. Khan completed his Ph.D. in Computer Science and Engineering from Kyung Hee University, South Korea, in 2020. His thesis, “An Ensemble-based Effective Features Engineering and Intelligent Unified Framework for Sentiment Analysis,” was supervised by Prof. Young-Koo Lee. He holds an M.Sc. in Computer Science from Kohat University of Science and Technology, Pakistan, where he developed a computerized hotel management system under the guidance of Mr. Qadeem Khan. He earned his B.Sc. in Computer Science from the University of Malakand, Pakistan.

Experience

💼 From October 2020 to February 2023, Dr. Khan served as a Postdoctoral Fellow in the Department of Applied Artificial Intelligence at Hanyang University, South Korea, focusing on big data mining and sentiment analysis. Prior to this, he was a Research Associate at Kyung Hee University, South Korea, from March 2014 to September 2020, where he worked on social media analytics and sentiment classification.

Research Interests

🔍 Dr. Khan’s research interests encompass data science, artificial intelligence, natural language processing, semantic learning, machine learning, deep learning, text mining, data mining, software engineering, computer vision, cloud computing, and IoT. He is particularly focused on developing intelligent frameworks for sentiment analysis and enhancing feature engineering techniques.

Awards & Honors

🏆 Dr. Khan has been honored with a fully funded Ph.D. scholarship from Kyung Hee University, which he held from March 2014 to September 2020. This prestigious award supported his doctoral studies and research in computer science and engineering.

Publications

📝 Dr. Khan has numerous publications in esteemed journals and conferences. Here are some of his notable works:

  1. Factors influencing vendor organizations in the selection of DevOps for global software development: an exploratory study using a systematic literature review. Cognition, Technology & Work (2023).
  2. Investigating the dynamic relationship between stigma of fear, discrimination and employees performance among healthcare workers during Covid-19 pandemic. Cognition, Technology & Work (2023).
  3. An empirical study for prioritizing issue of software project management team. Cognition, Technology & Work (2023).
  4. Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection. IEEE Access 11 (2023).
  5. Monkeypox detection using CNN with transfer learning. Sensors 23, no. 4 (2023).