Yicong Li

I’m a Ph.D. candidate in Computer Science at Harvard University, advised by Prof. Hanspeter Pfister in Visual Computing Group (VCG). I also work closely with Prof. Jeff W. Lichtman at Harvard’s Center for Brain Science, Prof. Bill Lotter at Dana-Farber Cancer Institute/Harvard Medical School, and Prof. Wanhua Li at Nanyang Technological University.

Previously, I obtained my master’s degree from Tsinghua University advised by Prof. Yang Li and my bachelor’s degree from Sichuan University. During this period, I’m fortunate to have worked with Prof. Nir Shavit and Prof. Lu Mi at MIT CSAIL, and Prof. Faisal Mahmood at Brigham and Women’s Hospital.

I interned at Genentech in Dr. Dan Ruderman’s team, at Microsoft Research with Dr. Kristen Severson, at Simons Foundation’s Flatiron Institute with Prof. Dmitri “Mitya” B. Chklovskii and Prof. Jingpeng Wu, and at Huawei with Changzheng Zhang and Prof. Nanshan Zhong’s team.

My research aims to develop bleeding-edge AI techniques to address important real-world challenges. I’m broadly interested in:

• Computer Vision and Deep Learning: self/semi-supervised learning, generative modeling, multi-modal learning, transfer learning, domain adaptation, image segmentation/reconstruction/compression, etc.
• Multimodal Large Language Models: vision-language foundation models, in-context learning of multimodal LLMs, LLMs post-training, evaluation of LLMs, etc.
• AI for Healthcare: MRI/CT/X-Ray image analysis, AI-assisted pulmonary function diagnosis and quality control, embryo viability prediction in clinical IVF, etc.
• AI for Neuroscience: 2D/3D neuron segmentation, synapse detection, electron microscopy image reconstruction, AI-assisted efficient imaging, vision foundation models for connectomics, etc.
• AI for Biology: computational pathology, cancer biomarker discovery, cancer survival analysis, etc.

I’m the recepient of the Fellowship of Laverack Family Innovation Fund in the Division of Engineering and Applied Sciences from Harvard University and my research has been featured in MIT News, Forbes, MarkTechPost, Computer Vision News, and ERCIM News.