Prasanna Balachandran

Prasanna Balachandran is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia. His research focuses on materials informatics, density functional theory, and machine learning applied to accelerate the discovery of novel materials. He leads the Materials Informatics Group, which integrates computational methods with experimental validation to address challenges in 2D materials, magnetic alloys, and advanced ceramics.

Education: No formal education details provided in the text.

Research Interests
His work spans:
- Materials Informatics: Leveraging AI/ML for accelerated materials design.
- Magnetic Materials: Exploring skyrmions and chiral magnets for spintronics.
- Machine Learning: Developing adaptive algorithms for property prediction.
- Additive Manufacturing: Improving printability and material performance in metal alloys.
- Ferroic Materials: Designing electrocaloric and piezoelectric ceramics.

Key Contributions
- Developed active learning frameworks for optimizing HKUST-1 thin films and MTX alloys.
- Advanced Bayesian approaches for melt pool geometry prediction in additive manufacturing.
- Published over 150 peer-reviewed articles, including high-impact work in ACS Applied Materials, Applied Physics Letters, and Journal of Applied Physics.

Awards & Recognition

• Research Excellence Award, University of Virginia (2020)
• DARPA Young Faculty Award (2020)
• Rising Star in Computational Materials Science (2019)

Teaching & Mentorship
Taught courses such as MSE 4592/6592 (Materials Informatics), MAE 3420 (Computational Methods), and MSE 2090 (Materials Science). Mentors students in AI-driven materials design and additive manufacturing.

Labs & Collaborations
Leads the Materials Informatics Group, collaborating with industry partners and national labs on projects like turbine engine coatings and environmental barrier systems.