Ankit Agrawal

Ankit Agrawal is a Research Professor in the Department of Electrical and Computer Engineering at Northwestern University's McCormick School of Engineering and Applied Science. He also holds an Honorary Professor position at Amity University in India. With over 200 peer-reviewed publications (100+ as first/last author), 15,000+ citations (h-index: 50+), and 75+ invited/keynote talks, he is a leading researcher at the intersection of artificial intelligence and materials science. His work spans multiple disciplines with significant contributions to both theoretical frameworks and practical applications.

Ankit earned his Ph.D. in Computer Science with a minor in Bioinformatics and Computational Biology from Iowa State University (2006-2009), followed by a B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Roorkee (2002-2006). His academic journey progressed from Graduate Assistant at Iowa State to Postdoctoral Fellow at Northwestern, eventually leading to his current position as Research Professor.

Dr. Agrawal's research focuses on Artificial Intelligence, High Performance Data Mining, Materials Informatics, Healthcare Informatics, Social Media Analytics, and Bioinformatics. His work bridges computational methods with domain-specific applications, particularly in developing AI-driven approaches for materials discovery, healthcare analytics, and social media analysis. He has pioneered techniques for materials property prediction using deep learning, microstructure optimization, and AI-driven nanocombinatorics for accelerated structural characterization.

His extensive publication record demonstrates a clear trajectory toward increasingly sophisticated AI applications in materials science, with recent work focusing on hybrid AI models (combining LLMs with graph neural networks), structure-aware transfer learning, and inverse design frameworks. The publications reveal a strong emphasis on practical applications that bridge the gap between computational prediction and experimental validation in materials science.

• Featured in Stanford/Elsevier's list of top 2% scientists worldwide (09/2024)
• Named a Top Scholar by ScholarGPS for being in top 0.5% of scholars worldwide in machine learning, deep learning, and informatics (07/2024)

Dr. Agrawal has secured substantial research funding as PI or Co-PI on over 20 projects totaling millions of dollars from prestigious agencies including NSF, DOE, NIST, DARPA, and industry partners like Toyota. His current projects include the Center for Hierarchical Materials Design (CHiMaD) Phase III, AI-Driven Nanocombinatorics for Accelerated Structural Characterization, and Explainable AI for Science and Engineering (XAISE). He has also developed multiple software tools that have advanced the field of materials informatics.

As a key contributor to Northwestern's Center for Nanocombinatorics and the Center for Hierarchical Materials Design, Dr. Agrawal leads interdisciplinary teams that integrate AI expertise with domain knowledge in materials science. His work has established important frameworks for data-driven materials discovery and has been instrumental in advancing the 'fourth paradigm' of science in materials research through informatics and big data approaches.