Welcome
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
You can check out my work here and on my Google Scholar.
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
Recent News
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.
May 2022: I have passed my qualifying exam and am now a PhD candidate! Thank you to my committee members Prof. Finale Doshi-Velez, Prof. Yves Atchadé, Prof. Sham Kakade, and Prof. Demba Ba.
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.
Dec 2021: I have accepted a summer 2022 research internship position in the Biomedical Machine Learning group at Microsoft Research Lab -- New England!
Aug 2021: I am hired as the teaching assistant for Harvard's graduate-level course on Deep Learning for Natural Language Processing.