Biography
Pramod Abichandani is an academic and a technology entrepreneur. He is an Assistant Professor in the SAET/ECE/CS departments at New Jersey Institute of Technology (NJIT). He is the founder of LocoRobo -- a robotics company focused on the education, consumer, and defense markets. Prior to joining NJIT, he served as a faculty member in the Colleges of Engineering and Business at Drexel University. He received his Bachelors of Engineering (B.E.) degree in 2005 from Nirma Institute of Technology, Gujarat University, India, and his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Drexel University in 2007 and 2011 respectively.
His research interests are centered around optimal, multi-dimensional, data-driven decision-making, through the use of techniques from mathematical programming, linear and nonlinear systems theory, statistics, and machine learning. Specific technical areas include optimal decision-making for multi-robot systems under communication constraints, sensor fusion for naval ship monitoring, cognitive bias effects in handwriting forensics, and embedded systems design for data acquisition and control. Sponsors of his research include the National Science Foundation (NSF), US Army, US Air Force, Office of Naval Research (ONR), National Institute of Health (NIH), Wills Eye Hospital Department of Research, Weight Watchers, Mathworks, Drexel ExCITe Center, and Drexel University's College of Engineering.
On the education front, he works on bringing innovation to the classroom by introducing novel course content, active learning-based pedagogical methodologies, and multiple evaluation techniques. He is leading research efforts that explore credentialing in CS, engineering and analytics education, the scalability of CS, engineering and analytics education innovations and technology, and CS/engineering-specific learning theories for active learning. He has won several awards for his teaching, including the Excellence in Teaching Award (2023) at NJIT and the Continuing Excellence in Teaching (2010) award at Drexel University. In 2013, he was selected to participate in the National Academy of Engineering’s fifth Frontiers of Engineering Education symposium in Irvine, California where he presented his Data Science education initiatives.
His research interests are centered around optimal, multi-dimensional, data-driven decision-making, through the use of techniques from mathematical programming, linear and nonlinear systems theory, statistics, and machine learning. Specific technical areas include optimal decision-making for multi-robot systems under communication constraints, sensor fusion for naval ship monitoring, cognitive bias effects in handwriting forensics, and embedded systems design for data acquisition and control. Sponsors of his research include the National Science Foundation (NSF), US Army, US Air Force, Office of Naval Research (ONR), National Institute of Health (NIH), Wills Eye Hospital Department of Research, Weight Watchers, Mathworks, Drexel ExCITe Center, and Drexel University's College of Engineering.
On the education front, he works on bringing innovation to the classroom by introducing novel course content, active learning-based pedagogical methodologies, and multiple evaluation techniques. He is leading research efforts that explore credentialing in CS, engineering and analytics education, the scalability of CS, engineering and analytics education innovations and technology, and CS/engineering-specific learning theories for active learning. He has won several awards for his teaching, including the Excellence in Teaching Award (2023) at NJIT and the Continuing Excellence in Teaching (2010) award at Drexel University. In 2013, he was selected to participate in the National Academy of Engineering’s fifth Frontiers of Engineering Education symposium in Irvine, California where he presented his Data Science education initiatives.