<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Teaching on Abhiraj Bibhar</title><link>https://abhiraj.pages.dev/teaching/</link><description>Recent content in Teaching on Abhiraj Bibhar</description><generator>Hugo</generator><language>en</language><atom:link href="https://abhiraj.pages.dev/teaching/index.xml" rel="self" type="application/rss+xml"/><item><title>Data Structures &amp; Algorithms</title><link>https://abhiraj.pages.dev/teaching/cs210-data-structures-algorithms/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/teaching/cs210-data-structures-algorithms/</guid><description>Fundamental data structures, algorithm design paradigms, and complexity analysis with hands-on programming labs.</description></item><item><title>Human-Computer Interaction</title><link>https://abhiraj.pages.dev/teaching/cs640-human-computer-interaction/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/teaching/cs640-human-computer-interaction/</guid><description>Design and evaluation of interactive systems, covering usability, accessibility, and participatory design methods.</description></item><item><title>Machine Learning Foundations</title><link>https://abhiraj.pages.dev/teaching/cs501-machine-learning-foundations/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/teaching/cs501-machine-learning-foundations/</guid><description>Core principles of statistical learning, optimization, and neural networks with an emphasis on rigorous evaluation and reproducibility.</description></item><item><title>Seminar in Trustworthy AI</title><link>https://abhiraj.pages.dev/teaching/cs700-seminar-trustworthy-ai/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://abhiraj.pages.dev/teaching/cs700-seminar-trustworthy-ai/</guid><description>A research seminar examining fairness, privacy, and explainability in modern machine learning systems through primary literature.</description></item></channel></rss>