Shuchin Aeron
Associate Professsor
Department of Electrical and Computer Engineering
Tufts University, 161 College Ave, Medford, 02155
Secondary appointments: Tufts department of Mathematics, Tufts department of Computer Science
Short bio
Shuchin Aeron is an associate professor in the Department of Electrical and Computer Engineering at Tufts School of Engineering. He received his Ph.D. from Boston University in 2009 where he received the best thesis awards from both the department of ECE and from the School of Engineering. He is a recipient of Dean’s fellowship and a Schlumberger-Doll research grant in support of his PhD research. From 2009-2022 he was a postdoctoral research fellow at Schlumberger-Doll Research (SDR), where he worked on signal processing solution products for borehole acoustics leading to multiple patents. In 2016, he received the NSF CAREER award supporting his research in tensor algebraic methods for data analytics. He was a visiting faculty at Mitsubishi Electric Research Labs (MERL) in 2019. He is currently a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and an associate editor for IEEE Transactions on Geosciences and Remote Sensing (TGRS) since 2018. His research interests are in signal processing, information theory, tensor data analytics, statistical machine learning, and optimal transport with applications and impact in a number of domains ranging from geopyhics, imaging, natural language processing, cognitive sciences, bioinformatics, and high energy physics.
Recent talks and slides
[Slides] 2023 Summer workshop, IAIFI, Tufts University, Plenary talk.
[Slides] "Multivariate rank via entropy regularized optimal transport: sample efficiency, goodness-of-fit measures, and applications", 2023 Joint Math Meetings, AMS Special Session on Topology, Algebra, and Geometry in the Mathematics of Data Science II
[Slides] "Hard Negative Sampling via Regularized Optimal Transport for Contrastive Representation Learning" IEEE International Joint Conference on Neural Networks, IJCNN, 2023
Publications
All my publications tend to first appear on ArXiv. Please visit the Google Scholar page for most updated bibliographic information as well as links to the pdf. Most code repos for the papers are available via the links in the manuscripts.
Some representative (partially compiled list) publications are itemized under different research areas/topics on the page - Broader sci-tech impact.
Please contact me at shuchin at ece dot tufts dot edu for any additional information needed regarding the papers or if you have any feedback or comments on them.
Teaching
(2013 - present) EE 127 Information theory, Introductory level graduate course. [Course syllabus]
(2020 - present) EE 24 Proababilistic systems analysis, Undergraduate probability. [Course syllabus]
(2012 - 2020) EE 23 Linear Systems, Undergraduate signal processing.
(2023 - ) EE 193 Probability in high dimensions with applications to data science. [Course syllabus, notes, and exercises]
Other classes
Optimization via vector space methods, Fall 2020
Detection and estimation theory, Fall 2013