Prakash Chandra Chhipa
Doctoral Researcher, Luleå Universtiy of Technology, Sweden
A35374, Luleå Universtiy of Technology, Sweden
Prakash recieved PhD in Computer Vision in April 2025 from Luleå tekniska universitet, Sweden, focusing on making self-supervised representation learning robust, domain-aware, and ready for the real world. From distorted camera views to unseen adversarial threats, his research aimed to make self-supervised AI more resilient, adaptable, and aware of the domains it serves—from hospitals to mines. He authored and co-authored dozens of works—within and beyond his thesis—with many publications in top-tier venues including ECCV, ICLR, ACCV, WACV, and more. During this journey, he served as a reviewer, delivered invited talks across three continents, and held a visiting researcher position. He also supervised four master’s theses, participated in prestigious summer schools, received multiple grants and fellowships, and was featured on credible platforms—all while collaborating with inspiring researchers across the globe.
Before academia, Prakash spent over a decade in industrial R&D, building AI systems from concept to real-world deployment. At Samsung R&D (2012–2018), he worked across roles—from individual contributor to senior staff—on projects like large-scale content recognition for Samsung TVs (ACR systems in the US, EU, and Korea), contextual ad recommendations using reinforcement learning, and video/music analysis pipelines. He contributed five invention disclosures and 11 international patent applications, including many granted patents with multimillion-dollar valuation.
At Arkray R&D (2018–2020), he built and led the AI team, significantly contributing in delivering products like AI-based urinalysis systems (launched in 2019) exploring blood glucose estimation models, and RNA-based early cancer detection tools. He bridged clinical needs and machine learning innovation—contributing to multiple patent filings and pushing AI into real-world healthcare diagnostics.
This spectrum of experience—from training large-scale models to leading teams, from prototypes to patents—enables him to drive high-impact AI research and build tangible, scalable products. His combined industry and academic journey makes him uniquely positioned to lead innovation where scientific depth meets product relevance.
Please check his updated CV here.
Academic Research Highlights
Recieved PhD in Computer Vision from Luleå tekniska universitet, Sweden. Research focused on robustness and domain-aware self-supervised representation learning. Published rsearch works in top conferences including ICLR, ECCV, WACV, ICIP and ICCV/ECCV workshops. Have been a reviewer at CVPR, NeurIPS, ICLR, and other conferences, industrial research with 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 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
| Apr 08, 2025 | 🎓 Sucessfully defended PhD with thesis titled ‘Towards Robust and Domain-aware Self-supervised Representation Learning’). 🎓 |
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| Jan 22, 2025 | 🎉 Paper titled ‘ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks’ accepted in ICLR 2025. 🎉 |
| Nov 02, 2024 | 🥇 Featured in Swedish Trans-Atlantic Researchers and Scholars Network (STARS) for recent work. 🥇 |
| Oct 29, 2024 | 🎓 Accepted as DAAD AI-Net Fellow 2024 on subject ‘AI for Science’ with networking tour to host German institute for potential collaboration in Artificial Intelligence. 🎓 |
| Sep 20, 2024 | 🎉 Paper titled ‘LCM: Log Conformal Maps for Robust Representation Learning to Mitigate Perspective Distortion’ accepted in ACCV 2024. 🎉 |
| Aug 15, 2024 | 🎉 Paper titled ‘Open-Vocabulary Object Detectors: Robustness Challenges under Distribution Shifts’ accepted in ECCV OOD-CV workshop 2024. 🎉 |
| Jul 03, 2024 | 🎉 Paper titled ‘Möbius Transform for Mitigating Perspective Distortions in Representation Learning’ accepted in ECCV 2024. 🎉 |
