Bhavan Vasu
Machine Learning Researcher [CV]
I am a third-year Ph.D. candidate at Oregon State University (EECS) advised by Prof. Prasad Tadepalli, working on Interpretable Machine Learning for complex scenes. I am interested in topics that lie at the intersection of Computer Vision, Machine Learning, and Explainable AI. I am also the Vice President for Electrical Engineering and Computer Science Graduate Student Association at Oregon State University and serve as the Workflow Chair of AAAI.
Research Interests:
- Interpretable Machine Learning
- Human-AI Interaction
- Interactive Machine Learning (iML)
Education
Ph.D. in Computer Science, advised by Prof. Prasad Tadepalli, Oregon State University, 2021 – Present, Oregon, USA
Masters of Science in Computer Engineering advised by Prof. Andreas Savakis, Rochester Institute Of Technology (RIT), 2018, New York, USA
B.E in Electronics and Communication Engineering advised by Ms. Seema Srinivas, from Global Academy of Technology, 2015, Bangalore, India
Work experience
Research Fellow, NASA Jet Propulsion Laboratory, California Institute of Technology (CalTech), June 2022 – September 2022.
Graduate Teaching Assistant (AI 537 Computer Vision & CS 362 Software Engineering II, Spring 2022)
Graduate Teaching Assistant (CS 362 Software Engineering II, Winter 2022)
Graduate Research Assistant at Kelly Engineering Center
R&D Engineer, Computer Vision, Kitware Inc
Graduate Research Assistant at the Chester F. Carlson Center for Imaging
R&D Intern, Computer Vision, Kitware Inc
Peer Reviewer
Computer Vision and Image Understanding
IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)
Volunteering
What's new ?
News:
[Febuary 23rd 2024]: Oral Presentation at IAAI 2024, Vancouver, Canada
[November 3rd 2023]: Paper “Interactive Mars Image Content-Based Search with Interpretable Machine Learning” was accepted at IAAI 2024.
[14 November 2022]: I passed my Ph.D. Qualifying Exam! 🙂
[1 November 2022]: Submission titled “Global Explanations for Image Classifiers” accepted at Thirty-Seventh AAAI Conference on Artificial Intelligence‘s (AAAI 2023) Student Abstract and Poster Program, Washington DC
[27 October 2022]: My poster “Rule-Based Explanations for Deep Networks” was awarded “Most Impactful” at the Nation Science Foundation-Pervasive Personalized Intelligence Fall 2022 Meeting in Portland, OR
[10 June 2022]: Elected as the Vice President and Public Relations Officer for the EECS Graduate Student Association at Oregon State University
[03 May 2022]: Selected for NASA Jet Propulsion Laboratory’s (JPL) Graduate Fellowship Program (JPLGF) and will be working on the 2020 Mars mission at JPL in the Summer
[13 April 2022]: Invited to be a peer reviewer for the IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP)
[29 January 2022]: Invited to be a peer reviewer for Computer Vision and Image Understanding Journal (ranked 69 out of 273 in Engineering, Electrical & Electronic)
[15 January 2022]: Explainable AI toolkit (XAITK) receives honorable mention at Pytorch’s Annual Hackathon 2021 in the responsible AI category
[27 July 2021]: Paper on medical imagery retrieval system accepted at WACV 2022
[1 July 2021]: Journal article on Explainable Context-Based Image retrieval accepted at Applied AI Letters
[1 July 2021]: Journal article on Explainable AI Toolkit accepted at Applied AI Letters
[15 October 2020]: Nominated as a committee member to Kitware‘s “AI Team”
[10 July 2020]: My master’s thesis was published in IEEE Access journal, 2020
[14 March 2020]: Oral presentation at IEEE/CVF WACV 2020
[10 Dec 2019] : Paper accepted to WACV 2020. See IASSA in Publications.