Mohit Iyyer

Mohit Iyyer is an Associate Professor of Computer Science at the University of Maryland, College Park, with an affiliate appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS). He leads research in the Computational Linguistics and Information Processing (CLIP) Lab, focusing on natural language processing and machine learning. Previously, he was an associate professor at UMass CS, a Young Investigator at AI2, and completed his PhD at UMD CS.

Dr. Iyyer's research spans multiple critical areas in NLP and AI, with particular emphasis on improving instruction following in large language models, evaluating long-form and multilingual text generation, supporting creative writing through human-LLM collaboration systems, and enhancing the robustness of AI-generated text detectors against adversarial attacks. His work addresses fundamental challenges in language model capabilities, including long-context understanding, multilingual processing, and the evaluation of complex language generation tasks.

His recent publications demonstrate a strong trend toward addressing the practical challenges of deploying large language models in real-world scenarios. Key themes include the development of robust evaluation frameworks for long-form text generation, techniques for improving model instruction following capabilities, methods for detecting AI-generated content, and tools for supporting creative writing tasks. His research bridges theoretical advances with practical applications across multiple domains.

• Samsung AI Researcher of the Year award (2022)
• NSF CAREER award (2021)
• Distinguished Paper award at CCS 2023
• Outstanding paper award at EACL 2023
• Best long paper at NAACL 2018 (for ELMo)

Dr. Iyyer has advised numerous PhD students who have gone on to successful careers in both academia and industry, including positions at Google DeepMind, Microsoft, Virginia Tech, and Cornell. His research has been supported by significant grants, notably the NSF CAREER award for his work on interactive storytelling. He actively collaborates with researchers across institutions and regularly presents his work at leading AI and NLP conferences worldwide.

He leads the Computational Linguistics and Information Processing (CLIP) Lab at the University of Maryland, which focuses on cutting-edge research in natural language processing. The lab has developed innovative approaches to language model evaluation, instruction following, creative writing assistance, and AI-generated text detection. Current projects include developing benchmarks for computer-using web agents, improving long-context language model capabilities, and exploring culturally-aware multilingual question answering systems.