Andrew Lan

Machine Learning for Education

Andrew (Shiting) Lan, Assistant Professor

College of Information and Computer Sciences
University of Massachusetts Amherst

Address: 140 Governors Dr., Amherst, MA 01003
E-mail: andrewlan at cs dot umass dot edu

I am an assistant professor in the Manning College of Information and Computer Sciences, University of Massachusetts Amherst, since Jan. 2019.

From Feb. 2017 to Dec. 2018, I was a postdoctoral research associate in the EDGE Lab at the Department of Electrical Engineering, Princeton University, advised by Prof. Mung Chiang. I received my M.S. and Ph.D. degrees in Electrical and Computer Engineering in May 2014 and May 2016, respectively, from the Digital Signal Processing (DSP) group at Rice University, advised by Prof. Richard Baraniuk. I also worked for OpenStax. Prior to that, I received my BS degree in Physics and Mathematics from the Hong Kong University of Science and Technology in 2010. During that, I also studied at the Georgia Institute of Technology for a semester.

My research focuses on the development of artificial intelligence (AI) and especially natural language processing (NLP) methods to enable scalable and effective personalized learning in education. My research spans areas such as learner modeling, personalization, content generation, and human-in-the-loop AI. My vision is to build an machine learning system that enables a world in which every learner has access to highquality, affordable, and personalized learning. I have co-organized a series of workshops on machine learning for education; see ml4ed for details.

At the same time, I am generally interested in machine learning topics, including convex and nonconvex optimization, Bayesian inference, deep learning, and the future of work.

Nov 2023: Excited to be part of the Learning Engineering Virtual Institute (LEVI) Program as the LLM Methodology hub! Thanks to Schmidt Futures for supporting our work.
Sept 2023: We participated in the NAEP Math Automated Scoring Challenge and was a grand prize winner. Check it out here!

May 2023: Thank you, NSF, for funding my CAREER proposal!

April 2023: See you at our Fifth Workshop on Intelligent Textbooks at AIED 2023!

Aug 2022: We will be starting new projects sponsored by the NSF; see here and here. Thank you for your support!

Jan 2022: We participated in the NAEP Automated Scoring Challenge and was among the grand prize winners for the item-specific task. Check it out here!

Nov 2021: Congratulations to Aritra on receiving a Duolingo English Test's Doctoral Dissertation Award!