home

About...

Ricky J. Sethi is currently a Research Scientist at UMass Amherst/UMass Medical School. Ricky is also Director of Research for the Madsci Network and an Adjunct Professor at Southern New Hampshire University.

Prior to this, he was at UCLA/USC Information Sciences Institute, where he was chosen as an NSF Computing Innovation Fellow (CIFellow) by the CCC and the CRA; before that, he was a Post-Doctoral Scholar at UCR, where he was the Lead Integration Scientist for the WASA project and participated in ONR's Empire Challenge 10.

Ricky has authored or co-authored over 30 peer-reviewed papers, book chapters, and reports and made numerous presentations on his research in machine learning, computer vision, social computing, and cyberlearning. He has taught various courses in Computer Science, Physics, and General Science as a GSI and Visiting Professor. Ricky has also supervised/mentored undergraduate students, graduate students, and postdoctoral students at UCLA, USC, and UMass.

Ricky has served as a Panelist for the NSF Cyberlearning program, as an Editorial Board Member for the International Journal of Computer Vision & Signal Processing, and a Program Committee member for various conferences. In addition, he is a member of the YSP/Madsci Financial Board, a member of the American Institute of Physics, and a member of IEEE.

Education

Ricky received his B.A. in Molecular and Cellular Biology (Neurobiology) and Physics from the University of California, Berkeley, his M.S. in Physics/Business (Information Systems) from the University of Southern California, and his Ph.D. in Artificial Intelligence from the University of California, Riverside.

External Academic Profiles

Selected Publications

Book Chapters
  1. Nandita M. Nayak *, Ricky J. Sethi *, Bi Song, and Amit K. Roy-Chowdhury, "Modeling and Recognition of Complex Human Activities".
    In T. B. Moeslund, L. Sigal, V. Kruger, and A. Hilton (Eds.), Visual Analysis of Humans. Springer-Verlag (2011). PDF
    (* Both first authors)
  2. Bi Song, Ricky J. Sethi, and Amit K. Roy-Chowdhury, "Wide Area Tracking in Single and Multiple Views".
    In T. B. Moeslund, L. Sigal, V. Kruger, and A. Hilton (Eds.), Visual Analysis of Humans. Springer-Verlag (2011). PDF
  3. Ricky J. Sethi, Amit K. Roy-Chowdhury, and Ashok Veeraraghavan, "Gait Recognition Using Motion Physics in a Neuromorphic Computing Framework".
    In B. Bhanu and V. Govindaraju (Eds.), Multibiometrics for Human Identification. Cambridge University Press (2010). PDF
Journals
  1. Ricky J. Sethi, Hyunjoon Jo, and Yolanda Gil, "Structured Analysis of the Atomic Pair Actions Dataset using Workflows".
    Pattern Recognition Letters, SI: SAHAR (2013). PDF
  2. Ayelet Baram-Tsabari, Ricky J. Sethi, Lynn Bry, and Anat Yarden, "Asking scientists: A decade of questions analyzed by age, gender, and country".
    Science Education (2009). PDF
  3. Ayelet Baram-Tsabari, Ricky J. Sethi, Lynn Bry, and Anat Yarden, "Using questions sent to an Ask-A-Scientist site to identify childrens interests in science".
    Science Education (2006). PDF
Refereed Conferences and Workshops
  1. Ricky J. Sethi, Yolanda Gil, Hyunjoon Jo, and Andrew Philpot, "Large-Scale Multimedia Content Analysis Using Scientific Workflows".
    ACM International Conference on Multimedia (ACM MM) (2013). (Oral) PDF
  2. Yolanda Gil, Angela Knight, Kevin Zhang, Larry Zhang, and Ricky J. Sethi, "An Initial Analysis of Semantic Wikis".
    International Conference on Intelligent User Interfaces (IUI) (2013). PDF
  3. Ricky J. Sethi, Hyunjoon Jo, and Amit K. Roy-Chowdhury, "A Generalized Data-Driven Hamiltonian Monte Carlo for Hierarchical Activity Search".
    IEEE International Conference on Image Processing (ICIP) (2013). PDF
  4. Ricky J. Sethi and Lynn Bry, "The Madsci Network: Direct Communication of Science from Scientist to Layperson".
    21st International Conference on Computers in Education (ICCE) (2013). PDF
  5. Ricky J. Sethi, Hyunjoon Jo, and Yolanda Gil, "Re-Using Workflow Fragments Across Multiple Data Domains".
    Proceedings of the Seventh Workshop on Workflows in Support of Large-Scale Science (WORKS) held in conjunction with ACM/IEEE Supercomputing Conference (SC) (2012). (Oral) PDF
  6. Ricky J. Sethi and Amit K. Roy-Chowdhury, "A Physics-based Stochastic Framework for Activity Recognition and Analysis".
    51st Conference of the Society of Instrument and Control Engineers (SICE) (2011). (Oral)
  7. Matheus Hauder, Yolanda Gil, Ricky J. Sethi, Yan Liu, and Hyunjoon Jo, "Making Data Analysis Expertise Broadly Accessible through Workflows".
    Proceedings of the Sixth Workshop on Workflows in Support of Large-Scale Science (WORKS) held in conjunction with ACM/IEEE Supercomputing Conference (SC) (2011). (Oral) PDF
  8. Ricky J. Sethi and Amit K. Roy-Chowdhury, "Modeling and Recognition of Complex Multi-Person Interactions in Video".
    ACM Workshop on Multimodal Pervasive Video Analysis (ACM MPVA) held in conjunction with ACM Multimedia (ACM MM) (2010). (Oral)
  9. Ricky J. Sethi and Amit K. Roy-Chowdhury, "The Human Action Image".
    19th International Conference on Pattern Recognition (ICPR) (2010). PDF
  10. Ricky J. Sethi and Amit K. Roy-Chowdhury, "A Neurobiologically Motivated Stochastic Method for Analysis of Human Activities in Video".
    19th International Conference on Pattern Recognition (ICPR) (2010). PDF
  11. Ricky J. Sethi, Amit K. Roy-Chowdhury, and Saad Ali, "Activity Recognition by Integrating the Physics of Motion with a Neuromorphic Model of Perception".
    IEEE Workshop on Motion and Video Computing (WMVC)/IEEE Workshop on Applications of Computer Vision (WACV) (2009). PDF


Profile

Ricky J. Sethi

Ricky J. Sethi is currently a Research Scientist at UMass Amherst/UMass Medical School, Director of Research for The Madsci Network, and an Adjunct Professor at Southern New Hampshire University.

  • Affiliations:
    • UMass Amherst/UMass Medical School
    • Southern New Hampshire University
    • The Madsci Network
  • Education:
    • University of California, Berkeley
    • University of Southern California
    • University of California, Riverside
  • Field of Research:
    • Computer Vision
      Group analysis in video using physics-based, machine learning models
    • Data Science
      Multimedia analysis and reproducibility via semantic workflows
    • Online Communities
      Virtual communities & group collaboration for science learning