转发 |【重磅活动日程！】波士顿2024中国科学技术大学校友峰会

波士顿2024年中国科学技术大学校友峰会将在MIT的MIT Stata Center Room 32-155 (32 Vassar St, Cambridge, MA 02139) 举办，我们届时会有志愿者在门口指引大家到活动的教室。

附近停车场：Albany Street Parking Garage （36 Albany St, Cambridge, MA 02139），$11/day for weekends

MIT Stata Center 卫星地图

MIT Stata Center 外部

George Dai (8212)

Chief Investment Officer

Weatherbie Capital

George Dai is Chief Investment Officer and Portfolio Manager of Weatherbie Capital, LLC. George is a Portfolio Manager on the Weatherbie Specialized Growth, Weatherbie Long/Short, Alger Dynamic Opportunities and Weatherbie Enduring Growth Strategies. George joined Weatherbie Capital in March 2001 and has 25 years of investment experience. During his tenure at Weatherbie, he has been featured and quoted in several publications such as: The New York Times, Investor’s Business Daily, Barron’s, Reuters, Business Insider and Bloomberg. Prior to joining Weatherbie, he was an equity analyst with 1838 Investment Advisors. George received his M.B.A. from the Wharton School, University of Pennsylvania, (Director’s List), and his Ph.D. in chemistry from Johns Hopkins University. Previously, he earned a B.S. from the University of Science and Technology of China and was a pharmaceutical research scientist at Procter & Gamble. George is a prized Bridge player, and he holds four U.S. patents.

Philip Zhang 张引 (8103)

JD/PhD, Managing Principal

Milstein Zhang & Wu LLC

Dr. Zhang is Managing Principal of Milstein Zhang & Wu LLC, a law firm he co-founded in 2009. Dr. Zhang has 25 years of experience representing private and public companies and research institutions, particularly in the areas of pharmaceuticals, medical devices and advanced materials, including advising clients on IP strategies, worldwide patent procurement, patent validity and freedom-to-operate, and technology licensing.  Dr. Zhang received his J.D. from Vanderbilt University Law School in 1999, his Ph.D. (organic chemistry) from Dartmouth College in 1995, and graduated from the University of Science & Technology of China in 1986.

Lixin Gao 高立新 (8100)

Professor, Department of Electrical and Computer Engineering

University of Massachusetts, Amherst

Lixin Gao is a University Distinguished Professor of Electrical and Computer Engineering at the University of Massachusetts at Amherst. She received a Ph.D. degree in Computer Science from the University of Massachusetts at Amherst. Her research interests include online social networks, and Internet routing, network virtualization and cloud computing. Between May 1999 and January 2000, she was a visiting researcher at AT&T Research Labs and DIMACS. She was an Alfred P. Sloan fellow between 2003-2005, received an NSF CAREER Award in 1999 and a fellowship from Harvard University Radcliffe Institute in 2021. She won the best paper award from IEEE INFOCOM 2010, and the test-of-time award in ACM SIGMETRICS 2010. Her paper in ACM Cloud Computing 2011 was honored with “Paper of Distinction”.  She is a fellow of IEEE and ACM.

Jianwei Che 车健为 (8803)

Director, Computational Chemistry Core

Dana Farber Cancer Institute

Jianwei Che, PhD is a group leader at the Center for Protein Degradation of Dana-Farber Cancer Institute (DFCI) and the director of computational chemistry core in the Department of Cancer Biology. Dr. Che’s research is focused on developing and applying molecular modeling and informatics methods for the discovery and optimization of selective small molecules for modulating protein functions.

Dr. Che leads a computational group in collaboration with chemists, structural biologists, and cell biologists to identify and optimize novel small molecules that target disease-relevant proteins such as kinases, E3 ligases, and transcription factors. Currently, his main research interests include covalent small molecule discovery and small molecule-induced protein-protein interactions, such as molecular glues. Prior to joining DFCI, Dr. Che led technology development for sensitive detection of cancer mutations in circulating tumor DNA from plasma samples at M3Bio, using molecular barcoding in library construction and sequencing data analysis. He was also a senior research investigator at the Genomics Institute of Novartis Research Foundation, where he applied various molecular modeling methods in small molecule drug discovery projects and biomarker research. Additionally, he is a scientific co-founder of matchpoint ther. Dr. Che has published over 90 peer reviewed scientific publications and is an inventor in many patents.

Peng Yi 伊鹏 (9808)

Assistant Professor, Joslin Diabetes Center

Harvard Medical School

Peng Yi was a student in 9808 (98207) from USTC. He earned his Ph.D. in genetics from UT Southwestern Medical Center and then completed postdoctoral training in the Department of Molecular and Cell Biology at Harvard University. He is currently an investigator at the Joslin Diabetes Center, an Assistant Professor of Medicine at Harvard Medical School, and an affiliated faculty member at the Harvard Stem Cell Institute. His lab is interested in researching pancreatic beta cell regeneration and protection against autoimmunity, aiming to understand the underlying mechanisms of Type 1 diabetes and find potential treatments or cures.

Wayne Ye 叶万瑜 (0204)

President, Dolphin Capital

Wayne Ye is an angel investor, portfolio manager, entrepreneur and Ph.D. in Particle Physics. Dr. Ye has rich experience in quantitative research, trading, venture investing and post-investment management. He conducted research and portfolio management in multiple renowned funds including Millennium Partners, and is currently heading the investment and recruitment efforts for his firm.

Jiang He 何江 (0508)

Co-founder, Senior Director of Scientific Affairs, Vizgen

Jiang He is the scientific co-founder and VP of R&D, Reagents in Vizgen, a life science company pioneering in single-cell spatial genomics. He completed his postdoc at MIT, Ph.D. at Harvard University in Xiaowei Zhuang’s lab, and B.S. from University of Science and Technology of China. His work focused on developing single molecule imaging techniques and applying them to study different biological processes. Within Vizgen, Jiang oversees the reagent and product development, as well as the lab service division. Jiang has been recognized with numerous awards including Forbes 30 under 30 in Healthcare, Spotlight Scholar at AIF, and STAT Wunderkind awardee. Jiang was also the Commencement Speaker at Harvard University in 2016, the first Chinese graduate to ever speak at Harvard’s commencement ceremony. His speech “The spider’s bite” argued the importance of disseminating the scientific knowledge to where it’s most needed. In addition to his academic efforts, Jiang has written a non-fictional book about rural China, titled Zouchu Zijide Tiankong (Walking Out a Way of My Own), to raise awareness of the living and health conditions of resource-limited regions in China. His story has been broadly covered by many media outlets, including the Forbes, Boston Globe, Huffington Post, Harvard Crimson, MIT News, Sixth Tone, Asia Times, Global Times, People’s Daily, China Daily, Sina News, Yahoo News, Tecent News, CCTV, HunanTV, and many others.

Jiawei Zhang 张佳伟 (1101)

Assistant Professor, Computer Science

University of Wisconsin, Madison

Jiawei Zhang is an incoming assistant professor in the Department of Computer Sciences at the University of Wisconsin–Madison. Currently, he is a postdoctoral fellow supported by The MIT Postdoctoral Fellowship For Engineering Excellence in the Laboratory for Information & Decision Systems (LIDS) at MIT, working with Prof. Asuman Ozdaglar and Prof. Saurabh Amin. He obtained the Ph.D. degree in Computer and Information Engineering from the Chinese University of Hong Kong, Shenzhen, with an advisory of Prof. Zhi-Quan (Tom) Luo, and was honored with the Presidential Award for Outstanding Doctoral Students. Previously, he obtained the B.Sc. in Mathematics (Hua Loo-Keng Talent Program) from the University of Science and Technology of China. His research interests include: • Optimization theory and algorithms with application to machine learning, energy, and signal processing • Optimization, generalization, and robustness of machine learning, reinforcement learning, generative models (including diffusion models, large models, foundation models)