Mountain View, CA
Lake Dai is a seasoned venture investor with over 10 years of experience and a track record of successful exits and top-quartile returns. She is the Founder and Managing Partner of Sancus Ventures, a venture capital firm that invests in software infrastructure, including AI and blockchain technologies. In addition to her investment career, Lake is also an Adjunct Professor at Carnegie Mellon University, where she has been teaching Applied AI at the Master of Engineering program since 2016.
Lake has a strong background in product and engineering, having worked as an early employee and product engineering executive at Alibaba, where she was employee #84 and Head of Product, as well as at Yahoo!, Overture, and various Silicon Valley tech startups. She played a key role in building Alibaba's B2B marketplace from the ground up. Lake has also served on the boards of various tech companies in the fields of autonomous driving, neurotech, and bioinformatics. She is a Board Governor and member of the Audit & Risk Committee and the Lab & Research Committee of GIA, the largest gem and jewelry research, education, and laboratory services organization in the world.
In addition to her professional pursuits, Lake is dedicated to making a positive impact in the tech industry and is involved in several non-profit organizations. She serves as Chairwoman of HYSTA, one of the largest non-profit organizations empowering Chinese American tech founders, and is a member of the executive team of Stanford Women on Boards, leading the technology experience group.
Lake is the inventor of 5 U.S. patents in search algorithms, recommendation algorithms, and text tokenization.
Integrated Innovation Courses
- Applications of Artificial Intelligence
- Master of Science (MS) in Computer Science, Stanford University
- Master of Business Administration (MBA), University of Southern California, Marshall School of Business
- Bachelor of Science in Economics, Beijing International Studies University
- Beta Gamma Sigma
- Yahoo! Super Star Award
- System for Tokenizing text in Languages without Interword Separation | US 10002128
- In-Application Recommendation of Deep States of Native Applications | US 10146559
- Personalizing Deep Search Results Using Subscription Data | US 10157232
- Recommending Content Based On User Profiles Clustered by Subscription Data | US 10311478