Sili Deng

Sili Deng is an Associate Professor and Doherty Chair in Ocean Utilization at the Massachusetts Institute of Technology's Department of Mechanical Engineering since July 2024, previously serving as Assistant Professor from 2019-2024. She leads the Deng Energy and Nanotechnology Group (DENG), focusing on interdisciplinary research bridging energy conversion, nanomaterial synthesis, and scientific machine learning.

Her educational background includes a B.S. from Tsinghua University (2010), followed by an M.A. (2012) and Ph.D. (2016) from Princeton University. Postdoctoral work was conducted at Stanford University (2016-2018).

Research interests center on physics-informed data-driven modeling of reacting flows with applications in high-efficiency engines, carbon-neutral materials, flame synthesis of nanomaterials, and multiphase chemically reacting flows. Her group combines experimental and computational approaches to address fundamental challenges in combustion dynamics, emission reduction, and thermal management systems.

Recent publications (2023-2025) demonstrate a strong trend toward integrating machine learning with traditional combustion engineering, particularly through Bayesian neural networks for kinetic uncertainty quantification, thermal runaway prediction in batteries, and reaction-transport coupling analysis. Key thematic areas include energy storage materials, nanocatalysis, and computational fluid dynamics for reacting systems.

• Faculty Early Career Development Program (CAREER) Award, National Science Foundation (2022)
• Bernard Lewis Fellowship, Combustion Institute (2016)
• Gordon Wu Prize for Excellence, Princeton University (2014)
• Excellence in Teaching Award, Princeton University (2014)
• Princeton Energy and Climate Scholarship (2013)

Deng actively mentors graduate students through her research group, with current openings for Ph.D. candidates and postdocs focusing on energy conversion and nanomaterial synthesis. Her lab maintains strong industry and government collaborations, particularly in battery safety and combustion efficiency projects. The Deng Energy and Nanotechnology Group operates advanced experimental facilities for flame synthesis and computational infrastructure for physics-informed machine learning.