Graduate Student Seminar
October 13, 2023
12:00 p.m. ET
Scaife Hall 105
Making Artificial Intelligence Work in Materials Research
The use of modern artificial intelligence, machine learning, informatics, and other data mining approaches is a relatively new development in the chemical and materials domain. These techniques have been exceedingly successful in other application fields, and since there is no fundamental reason why they should not have a similarly transformative impact on chemical and materials research, there is now a concerted effort by the community to introduce them in this new context. These techniques hold tremendous promise for the practical realization of accelerated discovery, rational design, and inverse development of next generation materials systems. However, adapting techniques from other application domains for the study of chemical and materials systems requires a substantial rethinking and redevelopment of the existing methods. In this presentation, we will discuss our efforts along these lines.
Johannes Hachmann, University of Buffalo/New York State Center of Excellence in Materials Informatics
Hachmann is an Associate Professor of Chemical Engineering at the University at Buffalo (UB), the Director of the Engineering Science in Data Science graduate program, a Core Member of the UB Computational and Data-Enabled Science and Engineering graduate program, and a Faculty Member of the New York State Center of Excellence in Materials Informatics. He earned a Dipl.-Chem. degree (2004) after undergraduate studies at the universities of Jena and Cambridge, M.Sc. (2007) and Ph.D. (2010) degrees in Chemistry from Cornell University, and he conducted postdoctoral research at Harvard University before joining the UB faculty in 2014. The research of the Hachmann Group fuses (first-principles) molecular and materials modeling with virtual high-throughput screening and modern data science (i.e., the use of database technology, machine learning, artificial intelligence, and informatics) to advance a data-driven discovery and rational/inverse design paradigm in the chemical and materials disciplines. One of the centerpieces of the group’s efforts is the creation of an open, general-purpose software ecosystem for the data-driven design of chemical systems and the exploration of chemical space. This work was recognized with a 2018 NSF CAREER Award.
Upcoming Events
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March 14 2025
10:00 AM ET
Materials Science and Engineering
A Journey from Atoms to Materials: Computationally-Guided Discovery and Design of Functional Materials, presented by Prashun Gorai, Rensselaer Polytechnic Institute
McConomy Auditorium, First Floor Cohon University Center
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March 21 2025
10:00 AM ET
Materials Science and Engineering
Thermophysical and Thermochemical Properties of Transition Metal Diborides up to and above 3000 degrees, presented by Scott J. McCormack, University of California, Davis
McConomy Auditorium, First Floor Cohon University Center
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March 28 2025
10:00 AM ET
Materials Science and Engineering
Deciphering microscopic mechanisms driving assembly and flow of soft materials, presented by Vikram Jadhao, Indiana University, Bloomington
McConomy Auditorium, First Floor Cohon University Center
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April 11 2025
10:00 AM ET
Materials Science and Engineering
The Green Steel Revolution, presented by Sara Hornby-Anderson
McConomy Auditorium, First Floor Cohon University Center
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April 18 2025
10:00 AM ET
Materials Science and Engineering
presented by Robert Macfarlane, Massachusetts Institute of Technology
McConomy Auditorium, First Floor Cohon University Center
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April 25 2025
10:00 AM ET
Materials Science and Engineering
Oxide Dispersion Strengthening via Additive Processing: A Revolutionary New Approach for High Temperature Alloys, presented by Michael J. Mills, The Ohio State University
McConomy Auditorium, First Floor Cohon University Center