Hi, I'm Alex! I am a PhD candidate at the School of Engineering and Applied Sciences at Harvard University. I am fortunate to be advised by Prof. Demba Ba. My interests lie at the intersection of AI, statistics, and signal processing. Currently, my research focuses on the following areas:
Generative modeling and scalable Bayesian inference
Neural networks and deep learning
Machine learning applications to science and medicine
Prior to my PhD, I worked for one year as a machine learning researcher at ASAPP. Before that, I completed my Bachelor's and Master's degrees at Harvard from 2015 to 2019. More information can be found here and on my LinkedIn.
I am affiliated with the Computation, Representations, and Inference in Signal Processing (CRISP) group at Harvard and the National Science Foundation's Institute for Artificial Intelligence and Fundamental Interactions (IAIFI).
Occasionally, I write technical posts on The Active Learning Blog.
I can be contacted at the following email address:
alin [at] seas.harvard.edu
Jun 2022: Our journal paper Covariance-Free Sparse Bayesian Learning has been accepted by IEEE Transactions on Signal Processing!
Jun 2022: I have begun my internship at Microsoft Research with Dr. Alex Lu -- looking forward to a great summer!
May 2022: I am presenting our two accepted papers in-person at IEEE ICASSP 2022 in Singapore.
April 2022: I have been selected to attend the 9th Heidelberg Laureate Forum!
Mar 2022: I have been awarded an NDSEG Fellowship!
Feb 2022: Our abstract on Bayesian Sensitivity Encoding Enables Parameter-Free, Highly Accelerated Joint Multi-Contrast Reconstruction has been accepted as an oral presentation at ISMRM 2022.
Jan 2022: We have two papers accepted at IEEE ICASSP 2022 on (1) High-Dimensional Sparse Bayesian Learning without Covariance Matrices and (2) Mixture Model Auto-Encoders: Deep Clustering through Dictionary Learning.
Aug 2021: I am hired as the teaching assistant for Harvard's graduate-level course on Deep Learning for Natural Language Processing.