About me
I am a 5th year Computer Science Ph.D. student at the University of Utah. I received a B.Tech. in Computer Science from Indian Institute of Technology (IIT) Kanpur.
Research Interests
I am working towards understanding ML models through the lens of Computational Topology and Visualization. I believe that the strong mathematical foundations of topological analysis and interactive capabilities through visualization techniques can pave a path to traverse the inherently complex structures of ML models, especially in the context of deep learning. I am creating frameworks for Topological Data Analysis (TDA) and visualization to analyze and reason about deep learning models, as a step towards explainable and interpretable ML.
Resume
Publications
Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale
A. Rathore, S. Palande, J. S. Anderson, et al.
TopoAct: Exploring the Shape of Activations in Deep Learning
A. Rathore, N. Chalapathi, S. Palande, B. Wang.
Mapper Interactive: A Scalable, Extendable, and Interactive Toolbox for the Visual Exploration of High-Dimensional Data.
Y. Zhou, N. Chalapathi, A. Rathore, Y. Zhao and B. Wang.
VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations
A. Rathore, S. Dev, J.M. Philips , S. Srikumar, et al.
Talks
A Visual Tour of Bias Mitigation Techniques for Word Representations
Talk at AAAI 2021, Virtual
A Visual Tour of Bias Mitigation Techniques for Word Representations
Talk at KDD 2021, Singapore (Virtual)
(Upcoming) Exploring the topology of fine-tuned language models
Talk at Michigan State University, Michigan (Virtual)
(Upcoming) An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations
Talk at NeurIPS 2021, Virtual