Research

I am affiliated with a number of research groups. Most recently, I'm at Brown Visual Computing, where I researched how to create body-aware generative models with Bryce Blinn and Professor Daniel Ritchie. Before this, I worked with Professor Benyuan Liu at The University of Massachusetts Lowell to specialize state-of-the-art deep learning methods to automate biomedical procedures, such as disease diagnosis and endoscope video processing.

Feel free to check out my papers! You can click on each paper's title to open its abstract.

Publications

Deep Learning for Gastric Location Classification: An Analysis of Location Boundaries and Improvements through Attention and Contrastive Learning

Chenxi Zhang, Alex Ding, Zhehong Fu, Jing Ni, Qilei Chen, Zinan Xiong, Benyuan Liu, Yu Cao, Shujiao Chen, Xiaowei LiuSpecial Issue for the ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, 2023

Learning Body-Aware 3D Shape Generative Models

Bryce Blinn, Alex Ding, R. Kenny Jones, Manolis Savva, Srinath Sridhar, Daniel Ritchie

Detection of Endoscope Withdrawal Time in Colonoscopy Videos

Ying Li, Alex Ding, Yu Cao, Benyuan Liu, Shujiao ChenIEEE International Conference on Machine Learning and Applications (Pasedena, California), December 2021

Gastric Location Classification During Esophagogastroduodenoscopy Using Deep Neural Networks

Alex Ding, Ying Li, Qilei Chen, Yu Cao, Benyuan Liu, Shujiao Chen, Xiaowei LiuIEEE Symposium on Bioinformatics and Bioengineering (Kragujevac, Serbia), October 2021

Retinopathy of Prematurity Stage Diagnosis Using Object Segmentation and Convolutional Neural Networks

Alex Ding, Qilei Chen, Yu Cao, Benyuan LiuInternational Joint Conference on Neural Networks (Glasgow, United Kingdom), July 2020

An Evaluation of UPC++ by Porting Shared-Memory Parallel Graph Algorithms

Alex Ding, Yan GuFall MIT PRIMES Conference (Cambridge, Massachusetts), October 2019