S. Mohammad Mostafavi I.
I am a research scientist and team leader at Lunit (Learning Unit) where we conquer cancer with AI. In Lunit's Oncology group, we focus on Computational Pathology and Oncology, aiming to develop biomarkers for cancer treatment. Within the oncology AI research's model-centric teams, we develop top-performing AI models - from data selection/annotation to final deliverables - thanks to the multidisciplinary environment we have with pathologists, medical doctors, biomedical engineers, product/platform engineers, and business/strategy developers.
Prior to that, I was a Ph.D. candidate and research assistant at the computer vision lab at GIST and KAIST. Our CVPR22, ICCV21, CVPR20 (oral) and CVPR19 papers together with the TPAMI21 and IJCV21 journal publications were some of my research outputs with my professors.
My main interests currently are AI based digital pathology and Medical AI, and my daily tasks involve Computer Vision, Machine Learning and MLOps.
Prior to that I focused on Event-based Vision, 3D Reconstruction, SLAM, and robotics. I have experience in:
- AI based digital pathology
- Medical image processing
- Event-based vision
- Deep learning for computer vision applications
- 3D reconstruction, SLAM and Stereo matching
- Super-resolution and Image synthesis
- Industrial and Urban applications of computer vision
Please check my Educational background and selected publications below. Further details, and information about my Professional experience, Honors and awards, Programming skills, Patent, and more are available in my CV. Thank you!
CV  / 
Google Scholar  / 
LinkedIn  / 
GitHub
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Educational background
- Ph.D. Gwangju Institute of Science and Technology (GIST), South Korea.
Sep. 2015 - Aug. 2021
Department of Electrical Engineering and Computer Science - Computer Vision Lab.
Advisors: Prof. Jonghyun Choi (GIST) and Prof. Kuk-Jin Yoon (KAIST)
Dissertation: "Event-based Vision: Image Reconstruction, Super-Resolution, Depth Estimation".
- M.Sc. Hakim Sabzevari University, Iran.
Sep. 2009 - Jul. 2011
Department of Electrical Engineering and Computer Science
Advisors: Prof. Javad Haddadnia and Prof. Payman Moallem.
Thesis: "Facial Image Super Resolution Using Weighted Patch Pairs".
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Selected publications
Affilated with Lunit:
“Micron-resolution spatial analysis near the tumor-stromal border reveals a distinct density distribution of tumor-infiltrating lymphocytes and related genomic features” S Song, G Park, S Kim, S Choi, S Kim, W Jung, M Kang, M Mostafavi, H Song, A Valero, S Pereira, D Yoo, S Kim, S Shin, K Nesmith, CY Ock- AACR Annual Meeting Abstracts 2023
“Artificial intelligence (AI)-powered immune phenotyping to predict outcomes of immuno-oncology (IO)-based regimens in hepatocellular carcinoma (HCC)” H Chon, C Kim, B Kang, J Cheon, G Kim, C Oum, S Kim, G Park, M Mostafavi, M Kang, CY Ock - Journal of Clinical Oncology 2023 (IF 44.54)
“Artificial intelligence (AI)-powered immune phenotyping to predict outcomes of immuno-oncology (IO)-based regimens in hepatocellular carcinoma (HCC)” H Chon, C Kim, B Kang, J Cheon, G Kim, C Oum, S Kim, G Park, M Mostafavi, M Kang, CY Ock - Journal of Clinical Oncology 2023 (IF 44.54)
“Artificial intelligence-powered whole-slide image analyzer reveals a distinctive distribution of tumor-infiltrating lymphocytes in neuroendocrine neoplasms” HG Cho, SI Cho, S Choi, W Jung, J Shin, G Park, J Moon, M Ma, H Song, M Mostafavi, M Kang, S Pereira, K Paeng, D Yoo, CY Ock, S Kim - MDPI Diagnostics 2022 (IF 3.99)
“Artificial intelligence-powered whole-slide image analyzer reveals a distinctive distribution of tumor-infiltrating lymphocytes in neuroendocrine tumors and carcinomas” HG Cho, W Jung, SI Cho, J Shin, G Park, J Moon, M Ma,J Ryu, M Mostafavi, S Park, S Pereira, K Paeng, D Yoo, CY Ock, S Kim - ASCO 2022 Meeting Abstracts
Affilated with Lunit, KAIST and YONSEI:
Affilated with GIST and KAIST:
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