معرفی
Nihar Shah is Associate Professor with joint appointments in Machine Learning and Computer Science at Carnegie Mellon University's School of Computer Science. His research spans statistical learning, game theory, and peer review systems, with applications in fairness and robustness of AI systems.
His publication record demonstrates strong focus on improving scientific evaluation systems through machine learning approaches. Recent experimental work examines bias detection, LLM-generated content identification, and peer review optimization.
Significant honors include NSF CAREER, Google Research Scholar, and JP Morgan Faculty Research awards. He leads research on AI applications for scientific quality assessment deployed in evaluation of over 100,000 research papers.
