Citations to all the publications can be found in my Google Scholar and ResearchGate profiles.

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2024

  1. E. U. Samani and A. G. Banerjee. Persistent Homology Meets Object Unity: Object Recognition in Clutter. IEEE Transactions on Robotics, 40: 886-902, 2024. [Link]

  2. A. Krishnan, X. Yang, U. Seth, J. M. Jeyachandran, J. Y. Ahn, R. Gardner, S. F. Pedigo, A. W. Blom-Schieber, A. G. Banerjee, and K. Manohar. Data-Driven Ergonomic Risk Assessment of Complex Hand-Intensive Manufacturing Processes, submitted for review. [Pre-print].

  3. X. Yang, Z. Yu, and A. G. Banerjee. Sparse Color-Code Net: Real-Time RGB-Based 6D Object Pose Estimation for Edge Devices, under review.

  4. T. Zhang, N. Werner, and A. G. Banerjee. Toward Automated Formation of Composite Micro-Structures Using Holographic Optical Tweezers, under review.

2023

  1. E. U. Samani and A. G. Banerjee. Human-Inspired Topological Representations for Visual Object Recognition in Unseen Environments. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop on Robotic Perception and Mapping: Frontier Vision & Learning Techniques, 2023. [Print]

  2. C. Salazar and A. G. Banerjee. A Distance Correlation-Based Approach to Characterize the Effectiveness of Recurrent Neural Networks for Time Series Forecasting, under revision. [Pre-print]

  3. E. U. Samani, F. Tao, H. R. Dasari, S. Ding, and A. G. Banerjee. F2BEV: Bird's Eye View Generation from Surround-View Fisheye Camera Images for Automated Driving. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 9367-9374, 2023. [Link]

  4. A. Badias and A. G. Banerjee. Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning. IEEE Transactions on Neural Networks and Learning Systems, in press. [Link]

  5. B. Wong, W. Marquette, N. Bykov, T. M. Paine, and A. G. Banerjee. Human-Assisted Robotic Detection of Foreign Object Debris Inside Confined Spaces of Marine Vessels Using Probabilistic Mapping. Robotics and Autonomous Systems, 161: 104349, 2023. [Link]

2022

  1. J. Liu, L. N. Boyle, and A. G. Banerjee. An Inverse Reinforcement Learning Approach for Customizing Automated Lane Change Systems. IEEE Transactions on Vehicular Technology, 71(9): 9261-9271, 2022. [Link]

  2. S. Hwang, A. G. Banerjee, and L. N. Boyle. Predicting Driver's Transition Time to a Secondary Task Given an In-vehicle Alert. IEEE Transactions on Intelligent Transportation Systems, 23(5): 4739-4745, 2022. [Link]

  3. M. Ruediger, T. M. Paine, and A. G. Banerjee. Simulation of Underwater Environments to Investigate Multi-Robot Systems for Marine Hull Inspection. In Proceedings of IEEE OCEANS 2022 Hampton Roads Conference, Hampton Roads, VA, 1-7, 2022. [Link]

  4. A. Vashisth, A. Banerjee, Y.-C. Lin, S. K. Murakonda, and R. Kareem. Radio Frequency Field Enabled Platform for Additive Manufacturing of Continuous Fiber Composites. Provisional Application 63/366,680.

  5. A. W. Blom-Schieber, A. G. Banerjee, W. Guo, and E. U. Samani. Fiber Placement Tow End Detection Using Machine Learning. Patent Application 17/543,224. [Link]

2021

  1. E. U. Samani, X. Yang, and A. G. Banerjee. Visual Object Recognition in Indoor Environments Using Topologically Persistent Features. IEEE Robotics and Automation Letters, 6(4): 7509-7516, 2021. [Link]

  2. V. Tereshchuk, N. Bykov, S. Pedigo, S. Devasia, and A. G. Banerjee. A Scheduling Method for Multi-Robot Assembly of Aircraft Structures with Soft Task Precedence Constraints. Robotics and Computer-Integrated Manufacturing, 17, 102154, 2021. [Link]

  3. Z. Liu, A. G. Banerjee, and Y. Choe. Identifying the Influential Inputs for Network Output Variance Using Sparse Polynomial Chaos Expansion. IEEE Transactions on Automation Science and Engineering, 18(3): 1026-1036, 2021. [Link]

  4. A. W. Blom-Schieber, W. Guo, E. U. Samani, and A. G. Banerjee. Improved Tow-End Recognition for Fiber Placement Inspection Using Machine Learning. In Proceedings of the American Society for Composites 36th Annual Technical Conference (ASC), 1117-1134, 2021. [Link]

  5. B. Parsa and A. G. Banerjee. A Multi-Task Learning Approach for Human Action Detection and Ergonomics Risk Assessment. In Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), Virtual, 2352-2362, 2021. [Link]

  6. A. G. Banerjee. Collaborative Robots for Assembly of Large-Scale Structures. In S. K. Gupta, V. Krovi, and C. Schlenoff (Eds.), Manufacturing in the Era of 4th Industrial Revolution, World Scientific Publishing Company, Singapore, 2021. [Link]

2020

  1. N. Zobeiry, C. Seaton, M. Salviato, X, Chen, A. Banerjee, S. Devasia, J. Yang, A. Blom-Schieber, J. Buttrick, and S. Pedigo. A Factory-Centric Workforce Development Approach for Aerospace Industry. Proceedings of the Society for the Advancement of Material and Process Engineering Conference (SAMPE), Virtual, 2020.

  2. J. Liu, S. Hwang, W. Yund, J. D. Neidig, S. M. Hartford, L. N. Boyle, and A. G. Banerjee. A Predictive Analytics Tool to Provide Visibility into Completion of Work Orders in Supply Chain Systems. ASME Journal of Computing and Information Science in Engineering, Special Issue on Machine Learning Applications in Manufacturing, 20(3): 031003, 2020. [Link]

2019

  1. E. U. Samani, W. Guo, and A. G. Banerjee. Deep Learning-Based Semantic Segmentation of Microscale Objects. In Proceedings of International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), Helsinki, Finland, 2019. [Expanded version]

  2. 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. [Link]

  3. 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. [Link]

  4. S. Hwang, L. N. Boyle, and A. G. Banerjee. Identifying Characteristics that Impact Motor Carrier Safety Using Bayesian Networks, Accident Analysis & Prevention, 128: 40-45, 2019. [Link]

  5. D. M. Buckland, M. L. Cummings, D. B. Mark, A. G. Banerjee, K. Snyder, and M. A. Starks. Design Considerations for UAV-Delivered Opioid Overdose Interventions. In Proceedings of IEEE Aerospace Conference, Big Sky, MT, USA, 1-7, 2019. [Link]

2018

  1. 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. [Link].

  2. J. Liu, L. N. Boyle, and A. G. Banerjee. Predicting Interstate Motor Carrier Crash Rate Level using Classification Models. Accident Analysis & Prevention, 120: 211-218, 2018. [Link]

  3. 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 (CASE), Munich, Germany, 1460-1465, 2018. [Link]

  4. 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 (CIE), Quebec City, QC, Canada, V01BT02A034, 2018. [Link]

  5. K. Manohar, T. Hogan, J. Buttrick, A. G. Banerjee, J. N. Kutz, and S. L. Brunton. Predicting Shim Gaps in Aircraft Assembly with Machine Learning and Sparse Sensing. Journal of Manufacturing Systems, Special Issue on Smart Manufacturing, 48: 87-95, 2018. [Link]

  6. 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. [Link]

2017

  1. 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. [Link]

  2. R. Chen, Y-C. Chen, W. Guo, and A. G. Banerjee. A Note on Community Trees in Networks. In Advances in Neural Information Processing Systems (NIPS) Workshop on Synergies in Geometric Data Analysis, 2017. [Link]

  3. 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, Special Issue on High Performance Computing and Data Analytics for Cyber-Manufacturing, 43(2): 225-234, 2017. [Link]

  4. K. Rajasekaran, E. U. Samani, J. Stewart, and A. G. Banerjee. Imaging-Guided Collision-Free Transport of Multiple Optically Trapped Beads. In Proceedings of International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), Montréal, Canada, 1-6, 2017. [Link]

2016

  1. W. Guo and A. G. Banerjee. Toward Automated Prediction of Manufacturing Productivity Based on Feature Selection Using Topological Data Analysis. In Proceedings of IEEE International Symposium on Assembly and Manufacturing (ISAM), Ft. Worth, TX, 31-36, 2016. [Link]

  2. K. Rajasekaran, M. Bollavaram, and A. G. Banerjee. Toward Automated Formation of Microsphere Arrangements Using Multiplexed Optical Tweezers. In Proceedings of SPIE Optical Trapping and Optical Micromanipulation XIII Conference (OTOM), San Diego, CA, 99222Y, 2016. [Link]

  3. M. Bollavaram, P. Sane, S. Chowdhury, S. K. Gupta, and A. G. Banerjee. Automated Detection of Live Cells and Microspheres in Low Contrast Bright Field Microscopy. In Proceedings of International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS), Paris, France, 1-6, 2016. [Link]

2015

  1. A. G. Banerjee*, B. Beckmann, J. Carbone, L. DeRose, A. Giani, P. Koudal, J. Salvo, D. Yan, and W. Yund. Cloud Computing-based Marketplace for Collaborative Design and Manufacturing. In Proceedings of Second International Summit on IoT 360°, Rome, Italy, 409-418, 2015 (*alphabetical listing of authors). [Link]

  2. A. G. Banerjee, M. Khan, J. Higgins, and A. K. Das. Discovering and Validating Breast Cancer Treatment Correlations using an Associative Memory Model and Statistical Methods. In Proceedings of IEEE International Conference on Healthcare Informatics (ICHI), Dallas, TX, 390-397, 2015. [Link]

  3. A. G. Banerjee, M. Khan, J. Higgins, A. Giani, and A. K. Das. An Associative Memory Model for Integration of Fragmented Research Data and Identification of Treatment Correlations in Breast Cancer Care. In Proceedings of AMIA Annual Symposium, San Francisco, CA, 306-313, 2015. [Link]

  4. A. G. Banerjee, W. Yund, D. Yang, P. Koudal, J. Carbone, and J. Salvo. A Hybrid Statistical Method for Accurate Prediction of Supplier Delivery Times of Aircraft Engine Parts. In Proceedings of ASME Computers and Information in Engineering Conference (CIE), Boston, MA, V01BT02A037, 2015. [Link]

  5. A. G. Banerjee, A. Barnes, K. N. Kaipa, J, Liu, S. Shriyam, N. Shah, and S. K. Gupta. An Ontology to Enable Optimized Task Partitioning in Human-Robot Collaboration for Warehouse Kitting Operations. In Proceedings of SPIE 9494, Next-Generation Robotics II Conference, Baltimore, MD, 94940H, 2015. [Link]

  6. A. G. Banerjee and N. Roy. Efficiently Solving Repeated Integer Linear Programming Problems by Learning Solutions of Similar Linear Programming Problems using Boosting Trees. MIT Computer Science and Artificial Intelligence Laboratory Technical Report, 2015. [Link]

2013-14

  1. 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. [Link]

  2. 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. [Link]

  3. A. G. Banerjee and S. Ray Majumder. Toward Controlling Perturbations in Robotic Sensor Networks. In Proceedings of SPIE 9116, Next-Generation Robots and Systems Conference, Baltimore, MD, 91160B, 2014. [Link]

  4. A. G. Banerjee and S. K. Gupta. Research in Automated Planning and Control for Micromanipulation. IEEE Transactions on Automation Science and Engineering, Special Section on Micro-Assembly for Manufacturing at Small Scales, 10(3): 485-495, 2013. [Link]

2011-12

  1. 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. [Link]

  2. 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, Special Section on Photonics and Nanotechnology in Biophysics and Biomedical Research, 16(5): 051302, 2011. [Link]

  3. S. Tellex*, T. Kollar*, S. Dickerson, M. R. Walter, A. G. Banerjee, S. Teller, and N. Roy. Approaching the Symbol Grounding Problem with Probabilistic Graphical Models. AI Magazine, Special Issue on Dialog with Robots, 32(4): 64-76, 2011 (*equal contribution). [Link]

  4. A. G. Banerjee*, M. Ono*, N. Roy, and B. C. Williams. Regression-based LP Solver for Chance Constrained Finite Horizon Optimal Control with Nonconvex Constraints. In Proceedings of American Control Conference (ACC), San Francisco, CA, 131-138, 2011 (*equal contribution). [Link]

  5. S. Tellex*, T. Kollar*, S. Dickerson*, M. R. Walter, A. G. Banerjee, S. Teller, and N. Roy. Understanding Natural Language Commands for Robotic Navigation and Mobile Manipulation. In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Special Track on Physically Grounded AI, San Francisco, CA, 1507-1514, 2011 (*equal contribution). [Link]

  6. J. C. Ryan, M. L. Cummings, N. Roy, A. Banerjee, and A. Schulte. Designing an Interactive Local and Global Decision Support System for Aircraft Carrier Deck Scheduling. In Proceedings of AIAA Infotech@Aerospace (I@A), St. Louis, MO, 2011. [Link]

  7. S. Tellex, T. Kollar, S. Dickerson, M. R. Walter, A. G. Banerjee, S. Teller, and N. Roy. Interpreting Robotic Mobile Manipulation Commands Expressed in Natural Language. In IEEE Interational Conference on Robotics and Automation (ICRA) Workshop on Manipulation Under Uncertainty, 2011.

  8. T. Kollar, S. Dickerson, S. Tellex, A. G. Banerjee, M. R. Walter, S. Teller, and N. Roy. Towards Understanding Hierarchical Natural Language Commands for Robotic Navigation and Manipulation. MIT Computer Science and Artificial Intelligence Laboratory Technical Report, 2011. [Link]

2009-10

  1. A. G. Banerjee, A. Pomerance, W. Losert, and S. K. Gupta. Developing a Stochastic Dynamic Programming Framework for Optical Tweezer based Automated Particle Transport Operations. IEEE Transactions on Automation Science and Engineering, 7(2): 218-227, 2010. [Link]

  2. A. G. Banerjee and N. Roy. Learning Solutions of Similar Linear Programming Problems using Boosting Trees. MIT Computer Science and Artificial Intelligence Laboratory Technical Report, 2010. [Link]

  3. A. G. Banerjee, A. Balijepalli, S. K. Gupta, and T. W. LeBrun. Generating Simplified Trapping Probability Models from Simulation of Optical Tweezers Systems. ASME Journal of Computing and Information Science in Engineering, 9(2): 021003, 2009. [Link]

  4. A. G. Banerjee, W. Losert, and S. K. Gupta. A Decoupled and Prioritized Stochastic Dynamic Programming Approach for Automated Transport of Multiple Particles using Optical Tweezers. In Proceedings of ASME International Conference on Micro and Nanosystems (MNS), San Diego, CA, 785-796, 2009. [Link]

  5. A. Thakur, A. G. Banerjee, and S. K. Gupta. A Survey of CAD Model Simplification Techniques for Physics-based Simulation Applications. Computer-Aided Design, 41(2): 65-80, 2009 (2012 Most Cited Paper Award for Computer-Aided Design). [Link]

  6. A. G. Banerjee. Real-Time Path Planning for Automating Optical Tweezers based Particle Transport Operations. Ph.D. Dissertation, Department of Mechanical Engineering, University of Maryland, College Park, 2009 (Best Dissertation Award from the Department of Mechanical Engineering). [Link]

2006-08

  1. A. S. Deshmukh, A. G. Banerjee, S. K. Gupta, and R. D. Sriram. Content Based Assembly Search: A Step towards Assembly Reuse. Computer-Aided Design, 40(2): 244-261, 2008. [Link]

  2. A. G. Banerjee and S. K. Gupta. Geometric Algorithms for Automated Design of Side Actions in Injection Molding of Complex Parts. Computer-Aided Design, 39(10): 882-897, 2007. [Link]

  3. A. G. Banerjee, X. Li, G. Fowler, and S. K. Gupta. Incorporating Manufacturability Considerations during Design of Injection Molded Multi-Material Objects. Research in Engineering Design, 17(4): 207-231, 2007. [Link]

  4. A. G. Banerjee and S. K. Gupta. Use of Simulation in Developing and Characterizing Motion Planning Approaches for Automated Particle Transport using Optical Tweezers. In Proceedings of International Virtual Manufacturing Workshop (VIRMAN), Turin, Italy, 2008.

  5. A. G. Banerjee, A. Balijepalli, S. K. Gupta, and T. W. LeBrun. Radial Basis Function Based Simplified Trapping Probability Models for Optical Tweezers. In Proceedings of ASME Computers and Information in Engineering Conference (CIE), Brooklyn, NY, 99-109, 2008. [Link]

  6. A. G. Banerjee and S. K. Gupta. A step towards automated design of side actions for injection molding of complex parts. In Proceedings of Geometric Modeling and Processing Conference (GMP), Pittsburgh, PA, 2006; Lecture Notes in Computer Science, 4077: 500-513. [Link]

  7. A. G. Banerjee. Computer Aided Design of Side Actions for Injection Molding of Complex Parts. M. S. Thesis, Department of Mechanical Engineering, University of Maryland, College Park, 2006. [Link]

2003-04

  1. A. K. Behera, A. G. Banerjee, P. S. Reddy, V. Patel, P. Saha, and P. K. Mishra. Development of a compact wire feeding mechanism for micro electro discharge grinding. In Proceedings of All India Manufacturing Technology, Design and Research Conference (AIMTDR), Vellore, India, 2004.

  2. A. Kumar, A. G. Banerjee, S. Paul, and A. Roy Choudhury. Maximization of Slice Height with Uniformity of Surface Roughness in the Direct Slicing of Freeform Surfaces. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 217 (B14802): 765-777, 2003. [Link]

  3. A. G. Banerjee, A. Kumar, S. Tejavath, and A. Roy Choudhury. Adaptive Slicing with Curvature Considerations. International Journal of CAD/CAM, 3(1): 41-58, 2003. [Link]