Pravin Chopade is a Research Engineer, Artificial Intelligence (AI) Research Labs at Educational Testing Service (ETS), USA. He earned his PhD in Computational Science and Engineering (CSE) from the Department of Computational Science and Engineering (CSE), College of Engineering at North Carolina A &T State University, Greensboro, USA, his MS in Electrical Engineering from the University of Pune, Government College of Engineering, Pune (COEP), India, and BS in Electrical Engineering from the Amravati University, Government College of Engineering, Amravati, India. He also holds Post Graduate Diploma in Advanced Information Technology from the International Institute of Information Technology (IIIT), Pune, India.
Prior to ETS, Dr. Chopade was a Research Scientist II, Artificial Intelligence and Machine Learning at ACTNext, ACT Inc, Iowa City, USA and Research Scientist at iLab, Department of Computer Science, College of Engineering, North Carolina A & T State University, Greensboro, USA. His project was funded by the United States Department of Defense (DOD) and the Army Research Laboratory (ARL-ARO). During his doctoral work Dr. Chopade received funding and research awards from the DOD- Defense Threat Reduction Agency (DTRA) and Pennsylvania State University, NC-LSAMP, and the National Science Foundation (NSF). He also has 10 years of teaching experience as Lecturer, Assistant and Associate Professor of Electrical Engineering.
Dr. Chopade has published and presented 60 articles in peer-reviewed journals, conferences, filed two patent applications, in addition to having received a number of research grants and awards. Dr. Chopade serves as reviewer for several peer-reviewed journals from IEEE, Science Direct Elsevier, Springer, IET, IETE, SAGE-Part O, SAGE-track, InderScience and many more. He is the former IEEE Division/Region-3 Secretary for Central North Carolina (CNC) section and IEEE Computer Society Chapter.
Artificial Intelligence and Machine Learning-Multimodal Analytics
His current research interests involve developing intelligent, adaptive learning and assessment systems which be used at scale in real-world scenarios (robust learning, teaching and assessment algorithm development, related data integration and visualization), collaborative problem solving (educational measurement in games and simulations), predictive modeling, deep knowledge tracing, recommendation engine, knowledge mining MOOCs and other technological innovations.
His major field of interest and research includes big data/large-scale networks analytics and visualization, data integration and personalization, data mining, Machine Learning, Smart Grid, IntiGrid, GridStat design, and the protection and survivability of interconnected large-scale networks.
Member – Institution of Electrical and Electronics Engineers (IEEE)
Member- IEEE Computer Society
Member- Association for Computing Machinery (ACM)