Industrial & Systems Engineering
- (206) 543-5388
- MEB 222
- Faculty Website
- Scale-independent Multimodal Automated Real Time Systems (SMARTS) Lab
- Ph.D. in Mechanical Engineering, University of Maryland, 2009
- M.S. in Mechanical Engineering, University of Maryland, 2006
- B.Tech. in Manufacturing Science and Engineering, Indian Institute of Technology, 2004
- Research Scientist, Complex Systems Engineering Laboratory, General Electric Global Research, Sept 2012 – July 2015
- Research Scientist, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Jan 2012 – Aug 2012
- Postdoctoral Associate, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Sep 2009 – Dec 2011
Dr. Banerjee’s research is on developing automated decision-making systems for multiple agents (robots and humans) that operate in uncertain environments. Such systems are useful in a wide variety of manufacturing and biomedical applications at different spatial and temporal scales. Examples include manipulation of industrial parts using mobile ground robots, management of inventory levels in large-scale assembly plants, control of biological cells with optical tweezers, and support of clinicians in prescribing treatment plans for cancer patients.
For all of these systems, automated decision-making requires generation of feasible action sequences for the agents to optimize a given set of operational objectives. To achieve this end, his approach is to integrate physical and mathematical modeling of system dynamics, model-based stochastic optimal control and planning, and system response data-driven knowledge discovery leading to model refinement. The integration effort is supplemented by the development of novel, theoretically rigorous, and computationally efficient modeling, optimization, and data analysis methods that leverage key system characteristics to achieve robust performance.
Dr. Banerjee’s work has been recognized with several awards and honors including the 2012 Most Cited Paper Award from the Computer-Aided Design journal, the 2009 Best Dissertation Award from the Department of Mechanical Engineering at the University of Maryland, and the 2009 George Harhalakis Outstanding Systems Engineering Graduate Student Award from the Institute for Systems Research at the University of Maryland. He has also been invited to present his work at the inaugural University of Southern California symposium on the “Futures of Robotics” and the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems anniversary workshop on “20 years of Microrobotics: progress, challenges, and future directions.”
- V. Tereshchuk, J. Stewart, N. Bykov, S. Pedigo, S. Devasia, and A. G. Banerjee. An Efficient Scheduling Algorithm for Multi-Robot Task Allocation in Assembling Aircraft Structures. IEEE Robotics and Automation Letters, 4(4): 3844-3851, 2019.
- B. Parsa, E. U. Samani, R. Hendrix, C. Devine, S. M. Singh, S. Devasia, and A. G. Banerjee. Toward Ergonomic Risk Prediction via Segmentation of Indoor Object Manipulation Actions Using Spatiotemporal Convolutional Networks. IEEE Robotics and Automation Letters, 4(4): 3153-3160, 2019.
- N. Rahimi, J. Liu, A. Shishkarev, I. Buzytsky, and A. G. Banerjee. Auction Bidding Methods for Multiagent Consensus Optimization in Supply-Demand Networks. IEEE Robotics and Automation Letters, 3(4): 4415-4422, 2018.
- A. G. Banerjee, K. Rajasekaran, and B. Parsa. A Step Toward Learning to Control Tens of Optically Actuated Microrobots in Three Dimensions. In Proceedings of IEEE International Conference on Automation Science and Engineering, Munich, Germany, 1460-1465, 2018.
- J. Liu, S. Hwang, W. Yund, L. N. Boyle, and A. G. Banerjee. Predicting Purchase Orders Delivery Times using Regression Models with Dimension Reduction. In Proceedings of ASME Computers & Information in Engineering Conference, Quebec City, QC, Canada, V01BT02A034, 2018.
- W. Guo, K. Manohar, S. L. Brunton, and A. G. Banerjee. Sparse-TDA: Sparse Realization of Topological Data Analysis for Multi-Way Classification. IEEE Transactions on Knowledge and Data Engineering, 30(7): 1403-1408, 2018.
- K. Rajasekaran, E. Samani, M. Bollavaram, J. Stewart, and A. G. Banerjee. An Accurate Perception Method for Low Contrast Bright Field Microscopy in Heterogeneous Microenvironments. Applied Sciences, 7(12): 1327, 2017.
- W. Guo and A. G. Banerjee. Identification of Key Features Using Topological Data Analysis for Accurate Prediction of Manufacturing System Outputs. Journal of Manufacturing Systems, 43(2): 225-234, 2017.
- A. G. Banerjee, S. Chowdhury, and S. K. Gupta. Optical Tweezers: Autonomous Robots for the Manipulation of Biological Cells. IEEE Robotics & Automation Magazine, 21(3): 81-88, 2014.
- J. C. Ryan, A. G. Banerjee, M. L. Cummings, and N. Roy. Comparing the Performance of Expert User Heuristics and an Integer Linear Program in Aircraft Carrier Deck Operations. IEEE Transactions on Cybernetics, 44(6): 761-773, 2014.
- A. G. Banerjee, S. Chowdhury, W. Losert, and S. K. Gupta. Real-Time Path Planning for Coordinated Transport of Multiple Particles using Optical Tweezers. IEEE Transactions on Automation Science and Engineering, 9(4): 669-678, 2012.
- A. G. Banerjee, S. Chowdhury, W. Losert, and S. K. Gupta. Survey on Indirect Optical Manipulation of Cells, Nucleic Acids, and Motor Proteins. Journal of Biomedical Optics, 16(5): 051302, 2011.
Honors & awards
- Big-on-Small Award (nominated), International Conference on Manipulation, Automation and Robotics at Small Scales, 2019
- Top Engineer of the Year, International Association of Top Professionals, 2018
- Above & Beyond Silver Award, General Electric Global Research, 2013
- Most Cited Paper Award, Computer-Aided Design Journal, 2012
- Best Session Presentation Award, American Control Conference, 2011
- Best Dissertation Award, Department of Mechanical Engineering, University of Maryland, 2009
- George Harhalakis Outstanding Graduate Student Award, Institute for Systems Research, University of Maryland, 2009
Assessing ergonomic risk
Ashis Banerjee and a team of researchers used machine learning to develop a new system that can monitor factory and...
Big data and automation
These ME research projects demonstrate how mechanical engineers are expanding future applications of machine learning.