10th July 2026 : The IEEE Computer Society (CS) Chapter, Bhubaneswar Section, successfully organized a technical talk on “Feature Selection in Machine Learning” delivered by Dr. Satya Verma
IEEE CS Chapter, Bhubaneswar Section News Bulletin
Expert Talk on “Feature Selection in Machine Learning” Conducted Successfully
Bhubaneswar, 10 July 2026 — The IEEE Computer Society (CS) Chapter, Bhubaneswar Section, successfully organized a technical talk on “Feature Selection in Machine Learning” delivered by Dr. Satya Verma, Assistant Professor, Department of CSE, Institute of Technical Education and Research (ITER), Siksha ‘O’ Anusandhan, Bhubaneswar, on 10th July 2026.
The session attracted enthusiastic participation from more than 20 IEEE professional and student members. Notable attendees included Er. Hare Krishna Ratha, Advisor, IEEE Bhubaneswar Section and Chair, IEEE CS Chapter, Bhubaneswar Section, along with Executive Committee members Dr. Tapas Patra and Dr. Sricheta Parui. The event was efficiently managed by Dr. Amiya Ranjan Panda, Secretary, IEEE CS Chapter, Bhubaneswar Section.
About the Talk
In her engaging and informative presentation, Dr. Satya Verma highlighted feature selection as a critical preprocessing step in machine learning. She explained how identifying the most relevant attributes from high-dimensional datasets helps eliminate redundant and irrelevant features, thereby reducing computational complexity, mitigating overfitting, and enhancing model generalization.
Dr. Verma elaborated on the major categories of feature selection techniques:
- Filter methods (based on statistical measures)
- Wrapper methods (evaluating subsets using predictive models)
- Embedded methods (integrating selection during model training)
She also touched upon recent advances including hybrid approaches and evolutionary algorithms that balance accuracy and efficiency. The talk underscored the importance of feature selection in domains such as bioinformatics, text mining, healthcare analytics, financial time series analysis, NLP, and image processing.
The abstract emphasized that effective feature selection not only accelerates training but also improves interpretability and strengthens robust decision-making in real-world machine learning applications.
Speaker Profile
Dr. Satya Verma is an Assistant Professor in the Department of CSE at ITER, Siksha ‘O’ Anusandhan, Bhubaneswar. She received her Ph.D. from National Institute of Technology, Raipur (2024), M.Tech. (Honors) from NIT Raipur (2011), and B.E. from Pt. Ravishankar Shukla University, Raipur (2003). With 18 years of academic experience, she has published numerous research articles in reputed SCI/Scopus journals and international conferences. She also holds one utility patent and two design patents. Her research interests include Feature Engineering, Feature Selection Techniques, Meta-heuristic Optimization, Machine Learning, Deep Learning, Financial Time Series Analysis, Natural Language Processing, and Image Processing.
Feedback and Acknowledgements
Participants found the session highly informative and insightful. The IEEE CS Chapter, Bhubaneswar Section extends its sincere gratitude to Dr. Satya Verma for sharing her expertise and delivering such a valuable talk. The Chapter also thanks all the attendees and organizing team members for making the event a success.
Stay tuned to the IEEE CS Chapter, Bhubaneswar Section website for more upcoming technical events, workshops, and webinars.
For more details, contact: IEEE CS Chapter, Bhubaneswar Section
