LE, Lei (乐磊)
I am a senior machine learning engineer at LinkedIn. Before joining LinkedIn, I was an applied scientist at Amazon. Before joining Amazon, I interned at Google Research / Google AI and obtained my PhD degree in Computer Science, from Luddy School of Informatics, Computing and Engineering, Indiana University Bloomington. My research interests lie in Artificial Intelligence, or specifically, statistical machine learning, non-convex optimization and reinforcement learning. At school, I worked with Prof. Martha White, mainly on representation learning.
- 2013.8 - 2019.6, PhD in Computer Science,
Luddy School of Informatics, Computing and Engineering, Indiana University Bloomington, IN, USA. - 2010.9 - 2013.3, Master of Management Science,
School of Economics and Management, Tongji University, Shanghai, China. - 2006.9 - 2010.6, Bachelor of Management Science,
School of Business, East China Normal University, Shanghai, China.
- 2022.2 - present, Senior Machine Learning Engineer at LinkedIn.
- 2019.8 - 2022.2, Applied Scientist at Amazon.
- 2018.9 - 2018.12, Intern at Google, Research and Machine Intelligence Team.
- 2015.8 - 2019.5, Research Assistant. Department of Computer Science, Indiana University Bloomington. Supervisor: Martha White, Ph.D
- 2013.9 - 2015.5, Associate Instructor. Department of Computer Science, Indiana University Bloomington.
- Borisyuk, Fedor, et al. LiRank: Industrial Large Scale Ranking Models at LinkedIn. Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024. [PDF]
- Farzane Aminmansour, Andrew Patterson, Lei Le, Yisu Peng, Daniel Mitchell, Franco Pestilli, Cesar Caiafa, Russell Greiner and Martha White. Learning Macroscopic Brain Connectomes via Group-Sparse Factorization. Advances in Neural Information Processing Systems (NeurIPS), 2019. [PDF]
- Vincent Liu, Raksha Kumaraswam, Lei Le, and Martha White. The utility of sparse representations for control in reinforcement learning. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2019. [PDF]
- Lei Le, Andrew Patterson, and Martha White. Supervised autoencoders: Improving generalization performance with unsupervised regularizers. Advances in Neural Information Processing Systems(NeurIPS), pages 107-117, 2018. [PDF]
- Lei Le and Martha White. Identifying global optimality for dictionary learning. [PDF]
- Lei Le, Raksha Kumaraswamy, and Martha White. Learning sparse representations in reinforcement learning with sparse coding. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17, pages 2067–2073, 2017. [PDF]
- Lei Le and Martha White. Global optimization of regularized factor models using alternating minimization. In 33rd International Conference on Machine Learning (ICML 2016), Advances in Non-convex Analysis and Optimization Workshop , New York City, NY, June 2016.
- Lei Le, Emilio Ferrara, and Alessandro Flammini. On predictability of rare events leveraging social media: A machine learning perspective. In Proceedings of the 3rd ACM Conference on Online Social Networks (COSN’15), Palo Alto, CA, November 2015. [PDF]
| Email: | some.other.lei %A%T gmail %D%O%T com |
|---|---|
| LinkedIn: | www.linkedin.com/in/leile26/ |
I love soccer, basketball and baseball. In my spare time, I watch games and play them. I also like playing the guitar, video games, and reading books and manga.