Jyoti Kumari

Jyoti Kumari is pursuing her Ph.D. in Computer Science and Engineering at the Indian Institute of Technology Patna.

She holds B.Tech and M.Tech degrees in Computer Science and Engineering from AKTU, Lucknow, and her research focuses on deep learning-based analysis of time series data, including anomaly detection, forecasting, and intrusion localization.

She has published research in peer-reviewed SCI and SCIE-indexed journals and actively contributes to advanced research in time series analytics and interpretable AI systems.

Jyoti Kumari has research and project experience through industry-sponsored initiatives at IIT Patna, including DRDO and NRB funded projects.

She has also worked as a Teaching Assistant for undergraduate and postgraduate courses, supporting both theoretical and laboratory sessions in artificial intelligence, deep learning, time series analysis, and computer systems.

B.Tech in Computer Science and Engineering, AKTU Lucknow.

M.Tech in Computer Science and Engineering, AKTU Lucknow.

Ph.D. (Pursuing), Indian Institute of Technology Patna.

Time Series Forecasting, Anomaly Detection, Multivariate Time Series Analysis, Deep Learning, Intrusion Localization, Signal Processing, Interpretable AI.

Jyoti Kumari believes in building strong conceptual foundations while encouraging analytical thinking and practical implementation.

Her teaching approach emphasizes clarity, curiosity, and real-world application through problem-solving, experimentation, and active student participation.

She aims to nurture technically strong, innovative, and lifelong learners capable of solving complex computational problems.

Data Structure, Elements of AI and ML, Object-Oriented Analysis and Design.

Recipient of the UGC Junior Research Fellowship during her Ph.D. at IIT Patna.

Received the PG GATE Scholarship during her M.Tech program.

Awarded Best Student Academic Award during her B.Tech studies.

Jyoti Kumari has published multiple research papers in SCI and SCIE-indexed peer-reviewed journals.

Her research focuses on time series forecasting, anomaly detection, multivariate data analysis, and intrusion localization using deep learning techniques.

She has also contributed to DRDO and NRB funded research projects, reflecting her engagement in applied and impactful research in AI and data science.

jyoti.kumari1@ddn.upes.ac.in