<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Research on Abhiraj Bibhar</title><link>https://abhiraj.pages.dev/research/</link><description>Recent content in Research on Abhiraj Bibhar</description><generator>Hugo</generator><language>en</language><atom:link href="https://abhiraj.pages.dev/research/index.xml" rel="self" type="application/rss+xml"/><item><title>FedCare: Privacy-Preserving Clinical Language Models</title><link>https://abhiraj.pages.dev/research/fedcare-privacy-preserving-clinical-nlp/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/research/fedcare-privacy-preserving-clinical-nlp/</guid><description>A multi-institution collaboration building federated NLP models for clinical decision support without centralizing patient data.</description></item><item><title>Trustworthy &amp; Private Machine Learning</title><link>https://abhiraj.pages.dev/research/trustworthy-private-machine-learning/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/research/trustworthy-private-machine-learning/</guid><description>Developing federated learning and differential privacy techniques that let sensitive data — especially in healthcare — be used for training without compromising individual privacy.</description></item><item><title>GlassBox: Visual Debugging for Graph Neural Networks</title><link>https://abhiraj.pages.dev/research/glassbox-visual-debugging-gnn/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/research/glassbox-visual-debugging-gnn/</guid><description>An open-source toolkit for interactively inspecting attention and message-passing behavior in GNNs.</description></item><item><title>Human-Centered AI</title><link>https://abhiraj.pages.dev/research/human-centered-ai/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/research/human-centered-ai/</guid><description>Studying how people build trust and mental models of AI systems, and designing interaction techniques that support meaningful human oversight.</description></item><item><title>EquiTutor: Adaptive Learning at Scale</title><link>https://abhiraj.pages.dev/research/equitutor-adaptive-learning-at-scale/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/research/equitutor-adaptive-learning-at-scale/</guid><description>A large-scale study of multimodal tutoring interfaces deployed across three partner school districts.</description></item><item><title>Explainable &amp; Interpretable Systems</title><link>https://abhiraj.pages.dev/research/explainable-interpretable-systems/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/research/explainable-interpretable-systems/</guid><description>Creating visualization and analysis tools that make complex models — including graph neural networks and large language models — easier to understand and debug.</description></item><item><title>AI for Education</title><link>https://abhiraj.pages.dev/research/ai-for-education/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/research/ai-for-education/</guid><description>Building adaptive tutoring systems that respond to learners&amp;rsquo; cognitive load and support equitable access to personalized instruction.</description></item></channel></rss>