Prakash Chandra Chhipa
Doctoral Researcher, Luleå Universtiy of Technology, Sweden
A35374, Luleå Universtiy of Technology, Sweden
Currently, Prakash Chandra Chhipa is a Computer Vision Researcher, Ph.D. Candidate at Machine Learning Group at Luleå University of Technology, Sweden, advised by Prof. Marcus Liwicki. Earlier, he proudly contributed to industrial R&D for 8+ years in machine learning and computer vision with multiple MNCs. He has a long-term track record in identifying challenges -> growing research ideas -> building prototypes -> inventing intellectual properties -> developing commercialized products.
Prakash’s research interest is representation learning in computer vision. His emphasis on doctoral research is two-fold. First, working self-supervised representation learning methods for their efficient adaptations on different visual domains such as medical imaging, remote sensing, RGBD images, and others where visual concepts predominantly differ from natural scenes and human supervision is limited. Second, he is working on understanding the effect of distribution shifts on representation learning due to natural and synthetic causes in the real world and attempting to make representation learning robust by mitigating it.
Academic Research Highlights
PhD candidate at ML Group, Luleå University of Technology, Sweden. Defended my licentiate thesis with emphasis on adaptation of self-supervised representation learning methods on beyond natural scene visual domain in March 2023 and now focusing on robust representation learning towards my doctoral thesis. Published rsearch works in top conferences including ECCV, WACV, ICIP and ICCV/ECCV workshops. Have been a reviewer at CVPR, NeurIPS, and other conferences, industrial research wit Swedish companies, and secured multiple grants.
Visiting Researcher at Center for Research in Computer Vision (CRCV), University of Central Florida, USA. Guided by host Prof. Mubarak Shah. Working on robust representation learning and also focusing Geo-localization domain. (Mar-June 2024)
Invited talk at EMBL-European Bioinformatics Institute at Cambridge, UK and MIRAI 2.0 Research and Innovation week at Kyushu University, Fukuoka, Japan. Accepted and participated in machine learning school at Cambridge University, UK and other prestigius venues.
Industrial R&D Work Tenure
Built a team and led computer vision research and development in the microscopic histopathology visual domain at Arkray R&D. Proudly contributed to achieving novel sediment recognition method on low-resolution histopathology for successful commercialization of Urinary Sediment Analyzer AUTION EYE AI-4510. Have been inventor for multiple patent applications (2018-2020).
Machine learning at AI & Data Intelligence Group (Now Advanced Research - Vision AI), Samsung R&D Institute for 6+ years (2012-2018) in different roles. Have been in forefornt for long-term R&D of successful large-scale products Samsung ACR and Samsung Ads focusing majorly on computer vision and reinforcement learning. Have been inventor for multiple granted patents/IP applications and awardee for Innovator of the Year-2017 for multiple IPs.
Worked with HCL Technologies for two years (2010-2012) and have been a contributor for enterprise-scale development of a platform for leading Telcom service provider T-Mobile.
news
| Aug 15, 2024 | Paper titled ‘Open-Vocabulary Object Detectors: Robustness Challenges under Distribution Shifts’ accepted in ECCV OOD-CV workshop. |
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| Jul 03, 2024 | Paper titled ‘Möbius Transform for Mitigating Perspective Distortions in Representation Learning’ accepted in ECCV 2024. |
