Ilias Bilionis

Professor of Mechanical Engineering

Purdue University
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United States

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Dr. Ilias Bilionis is an Associate Professor at Purdue University in the United States. His research interests encompass complex concentrated alloys, machine learning applications in physics, and Bayesian methods for data analysis in dynamical systems. He has published recent articles on topics such as high-hardness alloys, uncertainty quantification in modeling physical systems, and eco-feedback interventions in energy conservation. Dr. Bilionis's work integrates experimental data with advanced computational techniques to address challenges in materials science and energy management.

Recent Grants

Grant: Close

CPS: Medium: A meta-learning approach to enable autonomous buildings

Open Date: 2021-07-01

Close Date: 2024-06-30

Grant: Close

DMREF: Discovery of high-temperature, oxidation-resistant, complex, concentrated alloys via data science driven multi-resolution experiments and simulations

Open Date: 2019-10-01

Close Date: 2023-09-30

Grant: Close

Workshop and Grantees Meeting: Positioning Engineering Design and Systems Engineering Research for Sustained Societal Impact; West Lafayette, Indiana; October 7-8, 2019

Open Date: 2019-08-01

Close Date: 2021-07-31

Grant: Close

AMPS: Collaborative Research: Efficient Algorithms for Ultra-Fast Detection of Power System Contingencies in the Transient Regime

Open Date: 2018-08-15

Close Date: 2022-07-31

Grant: Close

SCC-IRG Track 1: Sociotechnical Systems to Enable Smart and Connected Energy-Aware Residential Communities

Open Date: 2018-01-01

Close Date: 2022-12-31

Positions (1)

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Ilias Bilionis

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Purdue University

Postdoctoral Researcher in Agentic AI for Scientific Instruments and Autonomous Experimentation at Purdue University

Purdue University is seeking a postdoctoral researcher for the ICoN Programmable Cloud Lab AI effort, led by Ilias Bilionis and Tianyi Zhang . The project focuses on agentic AI for scientific settings, especially systems that can interact safely and reliably with the physical world, including scientific instruments and laboratory systems. The research topics include harness engineering for scientific AI agents , curating and evaluating reusable agent skills , connecting coding agents with instruments , designing safe and auditable systems for autonomous experimentation , and developing domain-specific languages for scientific workflows . The post is especially relevant for candidates interested in AI for science, autonomous labs, scientific machine learning, and trustworthy AI systems. Applicants should have a PhD in engineering, computer science, applied mathematics, mathematics, physics, materials science, or a related scientific field. Strong experience with agentic AI , particularly coding agents, is preferred. Helpful background includes harness engineering, tool use, agent evaluation, scientific automation, and laboratory instrumentation. Knowledge of category theory is highlighted as an exceptional qualification. The position offers a collaborative environment spanning AI, experimentation, instrumentation, data, and physical modeling. The post also notes that Alejandro Strachan and Arun Mannodi Kanakkithodi are hiring a related postdoc on the same project with more emphasis on materials science expertise. Interested candidates should use the application link provided in the post. No deadline or funding amount is specified in the announcement.

Articles (15)

Collaborators (7)

Xiaoxu Zhong

Stanford University

UNITED STATES

Sayantan Bhattacharya

Assistant Professor

University of Maryland Baltimore County

UNITED STATES

Panagiota Karava

Purdue University

UNITED STATES

Shirley Dyke

Professor

Purdue University

UNITED STATES

Torsten Reimer

Professor

Purdue University

UNITED STATES

Jongseong Choi

Assistant Professor

State University of New York, Korea

SOUTH KOREA

Tatiana Ringenberg

Assistant Professor at Purdue University

Purdue University

UNITED STATES
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