Meet the Team
Barry Ravichandran
Senior R&D Engineer
Kitware Remote
M.S. in Computer Science and Engineering
The Pennsylvania State University
B.E. in Computer Science and Engineering
Anna University, College of Engineering, Guindy
Bharadwaj “Barry” Ravichandran is a senior R&D engineer on Kitware’s Computer Vision Team. He has played an integral role in a variety of Kitware’s government projects, including Defense Advanced Research Projects Agency Point-Of-Care Ultrasound Automated Interpretation (DARPA POCUS-AI), Chief Digital and AI Office Joint AI Test Infrastructure Capability (CDAO JATIC), and DARPA In The Moment (ITM) projects.
In addition to his projects, Barry has served as an official paper reviewer for top-tier computer vision conferences since 2021.
Before securing his full-time position at Kitware, Barry was an R&D intern for the annotation team. Through this internship, he learned a lot about Kitware’s work and learning culture. He worked closely with Keith Fieldhouse, director of cyber-physical systems at Kitware, and Roddy Collins, Ph.D. and principal engineer at Kitware, who served as his mentors.
Prior to joining Kitware, Barry worked as a research assistant at The Pennsylvania State University’s Laboratory for Perception, Action and Cognition (LPAC). His research focused on building an end-to-end system that could predict human foot pressure from human pose joints. The predicted foot pressure could then be used to quantitatively measure human stability through stability-relevant components such as Center of Pressure (CoP) and Base of Support (BoS).
Barry received his master’s degree in computer science and engineering from The Pennsylvania State University. He received his bachelor’s degree in the same field of study from Anna University, College of Engineering, Guindy.
Publications
- B. Hu, B. RichardWebster, P. Tunison, E. Veenhuis, B. Ravichandran, A. Lynch, S. Crowell, A. Genova, V. Bolea, S. Jourdain, and A. Whitesell, "NRTK: an open source natural robustness toolkit for the evaluation of computer vision models," in Assurance and Security for AI-enabled Systems, 2024. [URL]
- A. Hoogs, A. Lynch, S. Brockman, C. Funk, B. Ravichandran, and M. Dawkins, "Creating Deep Learning Detectors in VIAME for Rare Objects in Marine Imagery," in 2024 Ocean Sciences Meeting Poster, 2024. [URL]
- B. Ravichandran, A. Lynch, S. Brockman, B. RichardWebster, D. Du, A. Hoogs, and C. Funk, "LEARN: A Unified Framework for Multi-Task Domain Adapt Few-Shot Learning," in Preprint, 2024. [URL]
- S. Aylward, B. Ravichandran, C. Funk, B. Moore, F. Li, J. Crall, M. Morris, J. Anderson, A. Hersh, Y. Bronshteyn, and S. Montgomery, "ARGUS: An Open-Source Platform for Ultrasound Video AI That Supports Multiple Point-of-Care Applications," in MHSRS 2023, 2023. [URL]
- B. Ravichandran, R. Collins, K. Fieldhouse, K. Corona, and A. Hoogs, "From Leaderboard To Operations: DIVA Transition Experiences," in 2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), 2022. [URL]
- J. Scott, B. Ravichandran, C. Funk, R. Collins, and Y. Liu, "From Image to Stability: Learning Dynamics from Human Pose," in European Conference on Computer Vision 2020, 2020.