Personal Profile

Contact Information
207 Lab of Mechanics
Iowa State University
Ames, IA 50011
515-294-5212
soumiks (@) iastate.edu
Dr. Soumik Sarkar
Associate Professor
Ph. D. Mechanical Engineering, Penn State University, 2011
M.S. Mechanical Engineering, Penn State University, 2009
M.S. Mathematics, Penn State University, 2009
B.E. Mechanical Engineering, Jadavpur University, 2006

Dr. Soumik Sarkar received his B. Eng. Degree in Mechanical Engineering in 2006 from Jadavpur University, Kolkata, India. He received M.S. in Mechanical Engineering and M.A. in Mathematics in 2009 from Penn State University. Dr. Sarkar received his Ph.D. in Mechanical Engineering from Penn State in 2011. He joined the Department of Mechanical Engineering at Iowa State as an Assistant Professor in Fall 2014. Currently he is an Associate Professor of Mechanical Engineering and Computer Science and a Walter W Wilson Faculty Fellow in Engineering. Dr. Sarkar’s research interests include Machine Learning, Sensor Fusion, and Distributed Optimization and Control with applications to complex Cyber-Physical Systems such as aerospace, energy & smart building systems, transportation, design & manufacturing and agriculture systems. He co‐authored more than 202 peer-reviewed publications including 79 journal papers and 8 book chapters. Dr. Sarkar is currently serving as an Associate Editor of Frontiers in Robotics and AI: Sensor Fusion and Machine Perception journal, Plant Phenomics, a Science Partner Journal and an NVIDIA DLI University Ambassadorship. He received about $20M federal and private funding over the past seven years at Iowa State. He was selected to be an Iowa state Plant Science Institute scholar in 2018, received the Iowa State College of Engineering Award for Early Achievement in Research in 2019 and the Iowa State University Award for Early Achievement in Research in 2020. Dr. Sarkar is a recipient of the prestigious NSF CISE Career Initiation Initiative (CRII) award in 2015, the Young Investigator award from the US Air Force Office of Scientific Research (AFOSR) in 2017 and the NSF CAREER award in 2019.

[Google Scholars] [CV]

Research Funding

  • CPS: Frontier: Collaborative Research: COALESCE: COntext Aware LEarning for Sustainable CybEr-Agricultural Systems (as PI) sponsored by NSF and USDA-NIFA ($7,000,000, 4/15/2021 - 3/31/2026)
  • SCC-IRG Track 2: Smart Integrated Farm Network for Rural Agricultural Communities (SIRAC) (as Senior Personnel) sponsored by NSF ($1,499,830, 10/1/2020 - 9/30/2023)
  • RII Track-2 FEC: Data-Enabled Discovery and Design to Transform Liquid-Based Energy Storage (D3TaLES) (as Senior Personnel) sponsored by NSF ($1,989,220, 9/1/2020 - 8/31/2024)
  • Multiplexed Immunomarker Screening to Enable Patient-Tailored Immunotherapies (as Co-PI) sponsored by Congressionally Directed Medical Research Programs (CDMRP) ($587,996, 9/1/2020 - 8/31/2022)
  • Context-aware learning for inverse design in photovoltaics (as Co-PI) sponsored by ARPA-E ($2,000,000, 4/15/2020 - 4/14/2022)
  • CPS: Medium: Collaborative Research: Active Shooter Tracking & Evacuation Routing for Survival (ASTERS) (as ISU PI) sponsored by NSF ($649,982, 10/1/19-9/30/2022)
  • Deep Insight - Deep-net driven approach to estimate driver state from naturalistic data (as Co-PI) sponsored by DOT – Federal Highway Administration (FHWA) ($1,354,417, 9/1/2019 – 8/31/2023)
  • Fast Topology Optimization and Shape Style Transfer Using Machine Learning (as PI) sponsored by ANSYS ($75,000, 07/26/2019 – 05/15/2020)
  • FACT: A Scalable Cyber Ecosystem for Acquisition, Curation, and Analysis of multispectral UAV image data (as Co-PI) sponsored by USDA-NIFA ($500,000, 07/01/2019 - 06/31/2022)
  • CAREER:  Robustifying  Machine  Learning  for  Cyber-Physical  Systems (PI) sponsored by NSF ($511,620, 03/01/2019 - 02/29/2024)
  • PALM: Physics-Aware Learning for Microstructure Design – Phase I (as Co-PI) sponsored by DARPA ($400,000, 12/21/2018 - 09/20/2019)
  • Modeling multidimensional risk in real-world driver with diabetes (as Co-PI)  sponsored by Toyota ($198,664, 06/01/2018 - 02/28/2021)
  • Battery-free RFID Sensor Network with Spatiotemporal Pattern Network Based Data Fusion System for Human Presence Sensing (as Co-PI) sponsored by ARPA-E ($2,000,000, 06/01/2018 - 05/31/2021)
  • Predicting Driving Safety in Advancing Age (as Co-PI) sponsored by University of Nebraska Medical Center (original award from NIH) – ($94,639, 05/01/2017 - 08/31/2018)
  • Neural-Symbolic approach to Real-time Decision-making in Complex Aerospace Systems (as PI) sponsored by AFOSR - Young Investigator Program ($360,000, 5/1/2017 – 4/30/2020)
  • A multi-scale data assimilation framework for layered sensing and hierarchical control of disease spread in field crops (as PI) sponsored by NSF/USDA-NIFA
    ($990,471, 3/1/2017 - 2/29/2020)
  • Saliency-driven robotic networks for Spatiotemporal plant Phenotyping (as Co-PI) sponsored by NSF/USDA-NIFA ($820,021, 12/15/2016 - 12/14/2019)
  • PFI: BIC- A Smart Service System for Traffic Incident Management Enabled by Large-data Innovations (TIMELI) (as Co-PI) sponsored by NSF ($1,000,000, 09/01/2016 - 08/31/2019)
  • CM: Machine-Learning Driven Decision Support in Design for Manufacturability (as Co-PI) sponsored by NSF ($415,175, 09/01/2016 - 08/31/2019)
  • Big Data for Sustainable Cities & Decision Making (as Co-PI) sponsored by Iowa State Presidential Initiative on Interdisciplinary Research ($375,000, 08/01/2016 - 07/31/2019)
  • D3AI: Data drive discoveries for agricultural innovation (as Co-PI) sponsored by Iowa State Presidential Initiative on Interdisciplinary Research ($750,000, 10/01/2015 - 09/30/2018)
  • Using Engineering tools to identify and quantify biotic and abiotic stress in soybean for customable agriculture production (as Co-PI) sponsored by Iowa Soybean Association ($185,590, 10/01/2015 – 09/30/2018) 
  • Novel Machine Learning based methods for low-light image/video denoising (as Co-PI) sponsored by Regents Innovation Fund and Rockwell Collins Inc. ($200,000, 01/01/2015 - 05/31/2017)
  • A Knowledge Representation and Information Fusion Framework for Decision Making in Complex Cyber-Physical Systems (as PI) sponsored by NSF ($182,906, 05/15/2015 - 05/14/2017)
  • A Scalable Multi-agent Systems approach to Building HVAC Systems Control for Energy Efficiency (as Co-PI) sponsored by Iowa Energy Center ($100,000, 01/01/2015 - 08/31/2016)

Teaching

Courses taught as instructor at the Department of Mechanical Engineering, Iowa State University, Ames, IA USA (August 2014 to present):         
  • Graduate course on Data Analytics and Machine Learning for Cyber-Physical Systems Applications, Spring 2017, Spring 2018
  • Junior Level Course on Engineering Measurements, Fall 2016
  • Senior Level Course on System Dynamics and Control, Fall 2014, Spring 2015, Fall 2017
  • Freshmen Level Course on Mechanical Engineering Problem Solving with Computer Applications, Fall 2015, Spring 2016

Outreach

Invited Talks

  • A cyber physical systems approach to agricultural sustainability, Japanese Society of Agricultural Informatics (JSAI) Annual Conference, May 2021.
  • A hands-on introduction to Deep Learning, Midwest Big Data Summer School, Ames, IA, May 2021.
  • Physics-aware Machine Learning for Inverse Design, Honeywell, May 2021.
  • Next Big Research Challenges in CPS, NSF Invited Workshop, April 2021.
  • Building Trust in Deep Learning based Combustion Instability Detection, International Indo-US online workshop on Application of Machine Learning and Dynamical Systems Approach for Early Detection and Control of Combustion Instabilities, January 2021.
  • A cyber physical systems approach to agricultural sustainability, Workshop on Data Science for Agriculture and Natural Resource Management (DSANRM2020), 8th International Conference on Big Data Analytics (BDA2020), December 2020.
  • Machine Learning for Cyber-Physical Systems, Pennsylvania State University, University Park, PA, October, 2019
  • Artificial Intelligence and Machine Learning for Engineering Design and Simulations, ISU CoMFRE Annual Meeting, Ames, IA, October, 2019
  • Deep Learning for Engineering Design and Simulations, Michigan Technological University, Houghton, MI, October, 2019
  • Deep Learning in digital agriculture: From microscopy to canopy, Corteva Agriscience, Johnston, IA, June, 2019
  • Nuts and Bolts of Deep Learning, Midwest Big Data Summer School, Ames, IA, May 2019.
  • ​Deep Learning for Combustion Instability Diagnos tics, 17 th International Conference on Numerical Combustion, Aachen, Germany, May 2019
  • Deep Learning for Cyber-Agricultural Analytics, The 3rd US-JAPAN (NSF-JST) Workshop on Collaborative Global Research on Applying Information Technology, Tokyo, March 2019
  • Deep Learning for Agricultural Analytics, Keynote address in Asia-Pacific Federation for Information Technology in Agriculture/World Congress on Computers in Agriculture (AFITA/WCCA), IIT Bombay, Mumbai, India, October, 2018
  • Deep learning in cyber-enabled design and manufacturing, Georgia Institute of Technology, Atlanta, GA, October, 2018
  • Robustifying Deep Reinforcement Learning agents under adversarial attacks, Honeywell, Minneapolis, MN, September, 2018
  • Probabilistic Graphical Modeling for Building Energy Disaggregation,  Intelligent Buildings Operations workshop, Purdue University, West Lafayette, IN, July, 2018
  • Machine learning Approaches for Building Analytics, Intelligent Buildings Operations workshop, Purdue University, West Lafayette, IN, July, 2018
  • Engineering analytics with machine learning: Roles of supervised, semi-supervised and unsupervised models, Tsinghua University, Beijing, China, July, 2018   
  • Engineering analytics with deep learning: a few success stories, NVIDIA Corporate Headquarters, Santa Clara, CA, February, 2018
  • A multi-scale data assimilation framework for layered sensing and hierarchical control of disease spread in field crops, The 2nd US-JAPAN (NSF-JST) Workshop on Collaborative Global Research on Applying Information Technology, Tokyo, December 2017
  • A multi-scale data assimilation framework for layered sensing and hierarchical control of disease spread in field crops, NSF CPS PI meeting, Washington DC, November 2017
  • ​Applied Deep Learning, Midwest Big Data Summer School, Ames, IA, July 2017
  • ​Spatiotemporal Graphical Modeling for Complex Energy Systems, National Renewable Energy Laboratory, Golden, CO, April 2017
  • Spatiotemporal Graphical Modeling for Complex Cyber-Physical Systems, Department of Statistics, Iowa State University, Ames, IA, February 2017
  • Engineering Analytics with Deep Learning, ExxonMobil Research and Engineering, Annandale, NJ, December 2016
  • A Deep Auto-encoder Approach to Natural Low-light Image Enhancement, Rockwell Collins Inc., Cedar Rapids, IA, May 2016
  • Spatiotemporal Graphical Modeling for Complex Cyber-Physical Systems, University of Colorado Boulder, CO, March 2016
  • Solving Hard Engineering Problems with Deep Learning, Department of Mechanical Engineering, Washington State University, WA, March 2016
  • Machine Learning for Plant Phenotypic Decision-making, Phenotype Prediction: Image Acquisition and Analysis, Iowa State University, Ames, IA, February 2016
  • Solving Hard Engineering Problems with Deep Learning, Department of Computer Science, Iowa State University, Ames, IA, September 2015
  • RGBD Occlusion Detection via Deep Convolutional Neural Networks, NVIDIA GPU Technical Conference, San Jose, CA, March 2015
  • Research Activities at Iowa State in Dynamics, Control and Decision-making: From Aerospace to Building Energy Systems, United Technologies Research Center, East Hartford, CT, March 2015
  • Unsupervised aspects in Autonomous Perception & Decision-making, US Army Research Laboratory, Adelphi, MD, February 2015
  • Learning, Inference and Decision making in Human-cyber-physical Systems, Iowa State University, Ames, IA, January 2014
  • Autonomous Perception and Decision making in Complex Cyber-physical Systems, Missouri University of Science & Technology, Rolla, MO, January 2013
  • Health Monitoring of Human-engineered Complex Systems: A Cyber-physical Approach, Indian Institute of Science, Bangalore, India, June 2011
  • Autonomous Perception and Decision making in Complex Cyber-physical Systems, United Technologies Research Center, East Hartford, CT, April 2011
  • Data-driven Component level Fault Detection in Aircraft Gas Turbine Engines, Propulsion Controls and Diagnostic Workshop, Cleveland, OH USA, December 2009
  • Statistical Estimation of Multiple Faults in Aircraft Gas Turbine Engines, NASA Aviation Safety Technical Conference, Denver, CO USA, October 2008