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Taufiq Daryanto

Taufiq Daryanto is a Ph.D. student in the Department of Computer Science.  He is advised by Eugenia Rho. His research area is at the intersection of natural language processing and human-computer interaction, where he focuses on building human-centered AI systems.

Xiaohan Ding

Xiaohan Ding is a Ph.D. student in the Department of Computer Science.  He is advised by Eugenia Rho.   Ding’s research focuses on exploring the intersection of computational social science, computational linguistics, and natural language processing to enhance human-AI collaboration. Specifically, he investigates the influence of media language on social discourse and the development of […]

Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Series

Multilingual Code Snippets Training for Program Translation

Ming Zhu, Karthik Suresh, Chandan K. Reddy: Multilingual Code Snippets Training for Program Translation. AAAI 2022: 11783-11790

Unified Energy-Based Generative Network for Supervised Image Hashing

Khoa D. Doan, Sarkhan Badirli, Chandan K. Reddy: Unified Energy-Based Generative Network for Supervised Image Hashing. ACCV (6) 2022: 527-543

Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance

Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Chandan K. Reddy: Graph-based Multilingual Language Model: Leveraging Product Relations for Search Relevance. KDD 2022: 2789-2799

Hyperbolic Neural Networks: Theory, Architectures and Applications

Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy: Hyperbolic Neural Networks: Theory, Architectures and Applications. KDD 2022: 4778-4779

GraphZoo: A Development Toolkit for Graph Neural Networks with Hyperbolic Geometries

Anoushka Vyas, Nurendra Choudhary, Mehrdad Khatir, Chandan K. Reddy: GraphZoo: A Development Toolkit for Graph Neural Networks with Hyperbolic Geometries. WWW (Companion Volume) 2022: 184-188

An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury

WindowSHAP: An Efficient Framework for Explaining Time-series Classifiers based on Shapley Values