Dr. Pratibha Tokas

Dr. Pratibha Tokas is a researcher and academician specializing in Human Activity Recognition, wearable sensor computing, and AI-driven healthcare systems. She completed her Ph.D. in Computer Science and Engineering from MANIT Bhopal.

Her research focuses on developing efficient and interpretable frameworks for real-time activity recognition using IMU and sEMG data, with applications in rehabilitation and telehealth.

She integrates machine learning, signal processing, and edge computing to build intelligent healthcare solutions and has published in reputed journals such as IEEE Sensors Journal and Applied Soft Computing.

Dr. Pratibha Tokas has over seven years of academic and research experience in AI-driven healthcare and data science applications.

Before joining UPES, she served as Assistant Professor at Marwadi University and Smt. S.R. Patel Engineering College, Gujarat. She is currently working as Assistant Professor (Senior Scale) at UPES Dehradun.

Human Activity Recognition | Wearable and IoT-based Healthcare | Deep Learning | Explainable AI | Biomedical Signal Processing | Edge Computing

Dr. Pratibha Tokas believes that effective learning is driven by conceptual clarity, curiosity, and hands-on exploration.

She integrates real-world datasets, practical experimentation, and problem-based learning to help students connect theory with application in AI and data science domains.

Problem Solving | DBMS | Algorithms | Data Structures | Operating Systems | Introductory Artificial Intelligence | Introductory Machine Learning

• Recipient of MHRD Scholarship during Ph.D. at MANIT Bhopal and M.Tech at NIT Durgapur
• Secured workshop grants funded by IUCEE and GUJCOST
• Actively involved in funded research proposals in AI, IoT, and smart healthcare

Dr. Pratibha Tokas is actively engaged in research on sensor-based machine learning, real-time Human Activity Recognition, and AI-driven rehabilitation technologies.

Her work has been published in reputed SCI and Scopus-indexed journals including IEEE Sensors Journal, Applied Soft Computing, and Neural Computing & Applications.

Her ongoing research includes transformer-based temporal modelling, mixed-domain feature engineering, and lightweight attention-based models for wearable sensor data and telehealth systems.

pratibha.tokas@ddn.upes.ac.in