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Viterbi Faculty Directory

Satyandra K. Gupta

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Smith International Professorship in Mechanical Engineering and Professor of Aerospace and Mechanical Engineering and Computer Science

Education

  • 1994, Doctoral Degree, Mechanical Engineering, University of Maryland College Park
  • 1989, Master's Degree, Production Engineering, Indian Institute of Technology-Delhi
  • 1988, Bachelor's Degree, Mechanical Engineering, Indian Institute of Technology-Roorkee

Biography


Dr. Satyandra K. Gupta holds Smith International Professorship in the Aerospace and Mechanical Engineering Department and the Department of Computer Science in the Viterbi School of Engineering at the University of Southern California. He is also the founding director of the Center for Advanced Manufacturing at the University of Southern California. Prior to joining the University of Southern California, he was a Professor in the Department of Mechanical Engineering and the Institute for Systems Research at the University of Maryland, College Park. He was also the founding director of the Maryland Robotics Center and the Advanced Manufacturing Laboratory at the University of Maryland. Before joining the University of Maryland, he was a Research Scientist in the Robotics Institute at Carnegie Mellon University.

He served as a Program Director for the National Robotics Initiative at the National Science Foundation from September 2012 to September 2014. He served as a guest researcher at National Institute of Standards and Technology from September 2011 to August 2012. He currently serves as a member of the Technical Advisory Committee for Advanced Robotics for Manufacturing (ARM) Institute and a member of the National Materials and Manufacturing Board (NMMB). He testified at “Make It in America” Hearing for the US House of Representatives in 2015. He served as a member of the 2015 Autonomy Summer Study Task Force for the Defense Science Board. He was a member of the committee that conducted a study titled Options for a National Plan for Smart Manufacturing for National Academies of Sciences, Engineering, and Medicine in 2023. He also serves on Forbes Tech Council.

He is a co-founder and Chief Scientist at GrayMatter Robotics, a company focused on robotic automation solutions for high-mix manufacturing applications. GrayMatter Robotics' smart robotics cells are installed in many factories in the US serving aerospace & defense, specialty vehicles, marine & boats, metal fabrication, sports equipment, and furniture & sanitary ware sectors. These cells are helping companies to increase human productivity, reduce ergonomically challenging work, compress cycle times, expand capacity and improve sustainability.

Dr. Gupta received a Bachelor of Engineering (B.E.) degree in Mechanical Engineering from the University of Roorkee (currently known as the Indian Institute of Technology, Roorkee) in 1988. He received a Gold Medal for securing the first rank in his B.E. class (1988) and a Gold Medal for the best Engineering Design Project (1988). He received a Master of Technology (M. Tech.) in Production Engineering from the Indian Institute of Technology, Delhi, in 1989. He received a Ph.D. in Mechanical Engineering from the University of Maryland, College Park, in 1994.

Dr. Gupta's research is focused on developing human-centered automation to increase human productivity, reduce health risks for humans, and enable innovation. He is developing the next generation of robotic solutions that can serve as smart assistants for humans and creating decision support systems that empower humans to make more informed decisions in a timely manner. He is making advances in physics-informed artificial intelligence and machine learning to realize smart robotic assistants and decision support systems that operate in domains characterized by model uncertainty, complex physics, and fast decision-making speeds. Primary applications addressed by his group include multi-agent environment monitoring and information gathering, computer-aided design, and smart manufacturing. He is currently developing smart robotic assistants for a wide variety of manufacturing operations such as assembly, composite prepreg layup, kitting, finishing, inspection, and machine tending. He is also developing robotic cells for multiscale additive manufacturing.

Dr. Gupta has authored more than five hundred articles in journals, conference proceedings, and book chapters. He also holds sixteen patents. In addition, he has delivered more than two hundred invited seminars and lectures.

He is a former Editor-in-Chief of the ASME Journal of Computing and Information Science in Engineering. He also served as the Editor-in-Chief for Advanced Manufacturing Book Series published by World Scientific Publishing Company. He has served as an Associate Editor for IEEE Transactions on Automation Science and Engineering, ASME Journal of Computing and Information Science in Engineering, ASME Journal of Mechanisms and Robotics, and SME Journal of Manufacturing Processes. He currently serves as a member of Advisory Board for ASME Journal of Computing and Information Science in Engineering, Journal of Intelligent Manufacturing, and Smart and Sustainable Manufacturing Systems Journal.

Dr. Gupta has received numerous honors and awards for his contributions to the scientific community. Representative examples include: the Young Investigator Award from the Office of Naval Research in 2000, Robert W. Galvin Outstanding Young Manufacturing Engineer Award from the Society of Manufacturing Engineers in 2001, CAREER Award from the National Science Foundation in 2001, Presidential Early Career Award for Scientists and Engineers (PECASE) in 2001, Invention of the Year Award at the University of Maryland in 2007, Kos Ishii-Toshiba Award from ASME in 2011, Excellence in Research Award from ASME Computers and Information in Engineering Division in 2013, Distinguished Alumnus Award from Indian Institute of Technology, Roorkee in 2014, ASME Design Automation Award in 2021, and Distinguished Alumni Award from Indian Institute of Technology, Delhi in 2022. He was named "The 20 most influential professors in smart manufacturing" by Smart Manufacturing Magazine in June 2020. The Viterbi School of Engineering gave him Use-Inspired Research Award in 2021 for creating solutions that address the U.S. aerospace and defense industry's needs in the advanced manufacturing area. He has also received eleven best paper awards at international conferences. He served as a mentor for the student team that won the 2017 ARIAC competition organized by the National Institute of Standards and Technology, and another team advised by him was a finalist for the 2017 Kuka Innovation Award. He is a fellow of the American Society of Mechanical Engineers (ASME), Institute of Electrical and Electronics Engineers (IEEE), Society of Manufacturing Engineers (SME), and Solid Modeling Association (SMA).

Dr. Gupta's work has received significant attention from the media. His work has been covered by Economist, Forbes, Huffington Post, Baltimore Sun, LA Times, LA Business Journal, Audubon Magazine, IEEE Spectrum, Mechanical Engineering Magazine, Science News, and Smithsonian Magazine.

Research Summary


I am interested in developing human-centered automation solutions to increase human productivity, reduce human health risks, and enable innovation. Realizing human-centered automation requires robotics and automation technologies to reduce the physical human effort and enable humans to focus their effort on high-value tasks. It also requires augmenting human decision-making capabilities to reduce the probability of making mistakes, enabling creativity, and increasing decision-making speed.

During the early part of my career, I focused on developing computationally efficient geometric reasoning techniques, and integrating these techniques with heuristic search methods to solve manufacturability analysis and process planning problems. As the next logical step, I focused on integrating physics-based simulations into planning algorithms to generate plans that can be safely executed in the real-world. I explored both model simplification and meta-modeling approaches to ensure that planning problems can be solved in real-time and can produce good quality plans. I also examined how uncertainty might influence the risk associated with the generated plans and developed methods to generate risk-informed plans. I also investigated how planning problems that involve both discrete and continuous variables can be solved by combining optimization problems with discrete state space search.

Our recent work is focused on solving sequential decision-making problems to endow robots with capabilities to serve as smart assistants for humans. Many emerging robotics applications require multiple collaborating robots to operate under human supervision. To be useful in such applications, smart robotic assistants will need to (1) program themselves, (2) efficiently learn from the observed performance, (3) safely operate in the presence of uncertainty, (4) appropriately call for help during the execution of challenging tasks, and (5) effectively communicate with humans. We are leveraging a physics-informed machine learning approach to speed up sequential decision-making in robotics applications. We use both active learning methods to enable robots to do efficient exploration to build the word model, and we also use imitation learning and inverse reinforcement learning methods to learn from human demonstrations. We have been training neural networks using a combination of data generated from physical experiments and simulations to enable real-time decision making. We have also developed new learning architectures to ensure that the required physics models are enforced during the training. We are developing methods for robots to operate safely in the presence of uncertainty by generating contingency-aware plans. We are developing computational methods for endowing robots with introspective capabilities so that they can seek help from humans on challenging tasks. We are also exploring the use of augmented reality-based interfaces for enabling robots to elicit human guidance.

To augment human decision-making capabilities, we are interested in developing decision support systems that enable humans to make informed decisions in a timely manner for challenging applications. We are making advances in physics-informed artificial intelligence to enable the realization of decision support systems for applications that involve model uncertainty, complex physics, and fast decision-making speeds. We are also developing a novel framework to combine model-based approaches and data-driven approaches in a consistent and unified manner. This enables us to exploit prior knowledge and augment missing components of models through safe and efficient learning. We are also developing a digital twin based alert system that proactively notifies the human supervisor of possible adverse events and serves as a decision support system for humans to make informed decisions.

Based on previous and on-going research, my group has made the following notable contributions:

1. Our patented technology in the area of setup planning for sheet metal bending operations is the basis of Japanese machine tool manufacturer Amada’s automated process planning software for robotic press brakes. Software based on this technology is widely used in the sheet metal industry.
2. Our work in-mold assembly processes enables realizing geometrically complex heterogeneous structures in a cost-effective manner. These advances have enabled the use of novel, bio-inspired design concepts in applications such as robotics, bio-medical devices, thermal management systems, and aerospace structures.
3. Our work on the automated optical micromanipulation system significantly reduces the time needed to conduct experiments and minimize damage to biological cells. This work has enabled biophysicists to conduct new experiments on interplay of cell-cell and cell-substrate adhesion in collective cell migration and make new discoveries.
4. We have developed Robo Raven, the first robotic bird capable of flying outdoors using independent wing control and performing aerobatic maneuvers. This platform is enabling new applications for aerial vehicles in surveillance and environmental monitoring applications.
5. We have developed methodologies for automated generation of alerts and re-tasking suggestions to assist human supervisors of multi-robot teams. This work improved the system performance by enabling human supervisors to make better decisions. Researchers studying human-machine integration at the Army Research Laboratory are using insights gained from this work.
6. We developed a manufacturing cell for enabling humans and robots to collaborate on performing composite prepreg sheet layup. This cell uses advanced machine learning for defect detection and digital twins for cell monitoring. In collaboration with multiple aerospace companies, we have demonstrated that robotic assistants can perform composite sheet layup tasks at human-competitive speeds and reduce human effort in ergonomically challenging tasks.
7. Traditional additive manufacturing (AM) capability is restricted to planar layered printing. My group has developed methods for using nonplanar material deposition in AM. This work has demonstrated the ability to create composite parts with the desired fiber orientation and led to dramatic increase in the performance of 3D printed composite parts.
8. We developed physics-informed AI to power smart robotic assistants that self-program and utilize sensor data to adapt and deliver efficient and safe operational performance in high-mix sanding and polishing applications. GrayMatter Robotics, a company co-founded by him, has commercialized robotic sanding and polishing technology for high-mix manufacturing applications.
9. We have developed a cell for enabling effective human robot collaboration for safely and efficiently performing assembly operations by leveraging the complementary strengths of humans and robots. We have developed methods to generate efficient plans by proactively accounting for the possibility of contingency events. We have also developed generative AI methods to recover from contingency situations during execution. We have demonstrated the usefulness of this approach in improving human productivity in aerospace assembly applications.

Awards


  • 2024 American Society of Mechanical Engineers Best Paper Award (Second Place), ASME Manufacturing Science and Engineering Conference
  • 2024 Runner-up, NSF Manufacturing Blue Sky Competition held at SME North American Manufacturing Research Conference (NAMRC)
  • 2023 Finalist for the Best Systems Paper in ACM/IEEE International Conference on Human-Robot Interaction
  • 2023 Second Place in 2023 SME Aerospace and Defense Manufacturing Conference Poster Challenge
  • 2022 American Society of Mechanical Engineers Distinguished Service Award
  • 2022 Indian Institute of Technology, Delhi Distinguished Alumni Award
  • 2022 American Society of Mechanical Engineers Best Paper Award, ASME Computers and Information in Engineering Conference
  • 2022 The Engineers’ Council Distinguished Engineering Educator Achievement Award
  • 2021 Viterbi School of Engineering, University of Southern California Use-Inspired Research Award
  • 2021 Solid Modeling Association (SMA) Fellow
  • 2021 American Society of Mechanical Engineers Best Paper Award (Second Place), ASME Manufacturing Science and Engineering Conference
  • 2021 American Society of Mechanical Engineers Design Automation Award
  • 2020 University of Southern California Maseeh Entrepreneurship Prize Competition, First Place
  • 2020 Orange County Engineering Council Distinguished and Pioneer Educator Award
  • 2020 Society of Manufacturing Engineers (SME) Fellow
  • 2020 IEEE Fellow
  • 2019 First Place in 2019 SME Aerospace and Defense Manufacturing Conference Poster Challenge
  • 2018 Judge’s Choice Award at 2018 Reusable Abstractions of Manufacturing Processes Workshop
  • 2018 American Society of Mechanical Engineers Best Paper Award (Third Place) in 2018 ASME Manufacturing Science and Engineering Conference
  • 2018 American Society of Mechanical Engineers Best Paper Award in 2018 ASME Computers and Information in Engineering Conference
  • 2017 Finalist, Kuka Innovation Award
  • 2017 First Place, NIST Agile Robotics for Industrial Automation Competition (ARIAC)
  • 2017 American Society of Mechanical Engineers ASME Computer Aided Product and Process Development Technical Committee's Best Paper Award
  • 2014 Indian Institute of Technology, Roorkee Distinguished Alumnus Award
  • 2013 American Society of Mechanical Engineers ASME Computers and Information in Engineering Division's Excellence in Research Award
  • 2013 American Society of Mechanical Engineers Computer Aided Product and Process Development Technical Committee's Prakash Krishnaswami Best Paper Award, ASME Computers and Information in Engineering Conference
  • 2012 Best Paper Award, ASME Computers and Information in Engineering Conference
  • 2012 International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines Finalist for Best Paper
  • 2012 Computer Aided Design Journal Most Cited Paper Award
  • 2011 American Society for Mechanical Engineers (ASME) Design for Manufacturing and the Life Cycle Committee Kos Ishii-Toshiba Award
  • 2010 ASME Mechanism and Robotics Conference Compliant Mechanism Application Award
  • 2009 Bioinspiration & Biomimetics Highlights
  • 2007 American Society of Mechanical Engineers (ASME) Fellow
  • 2007 University of Maryland Finalist, Invention of the Year Award in Information Science Category
  • 2007 University of Maryland Invention of the Year Award in Physical Science Category
  • 2006 Science Spectrum Magazine Trailblazer Award
  • 2006 ASME Computers and Information in Engineering Conference Best Paper Award
  • 2003 University of Maryland Business Plan Competition
  • 2002 National Academy of Engineering Selected to Attend Frontiers in Engineering Symposium
  • 2001 Literati Club Highly Commended Award
  • 2001 Society of Manufacturing Engineers Robert W. Galvin Outstanding Young Manufacturing Engineer Award
  • 2001 National Science Foundation CAREER Award
  • 2001 Presidential Early Career Award for Scientists and Engineers
  • 2001 University of Maryland, Institute for Systems Research Outstanding Systems Engineering Faculty Award
  • 2000 Office of Naval Research Young Investigator Award
  • 1999 ASME Design for Manufacturing Conference Best Paper Award
  • 1994 University of Maryland, Institute for Systems Research Outstanding Systems Engineering Graduate Student Award
  • 1994 ASME Computers in Engineering Conference Best Paper Award in the area of Artificial Intelligence and Feature-Based Design and Manufacturing
  • 1988 University of Roorkee Gold Medal for First Rank in Bachelor of Engineering in Mechanical Engineering
  • 1988 University of Roorkee Gold Medal for the Best Engineering Design Project
  • 1988 Science and Technology Entrepreneurship Park, First Prize, Roorkee Chapter Project Competition
Appointments
  • Dir-Center, Director of the Center for Advance Manufacturing
  • Aerospace and Mechanical Engineering
  • Thomas Lord Department of Computer Science

Office
  • OHE 400D
  • Olin Hall of Engineering
  • 3650 McClintock Ave., Los Angeles, CA 90089
  • USC Mail Code: 1453

Contact Information
  • (213) 740-0491
  • guptask@usc.edu

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