About me

Amit Surana received his Bachelor’s degree in Mechanical Engineering from Indian Institute of Technology Bombay in 2000, his M.S. in Mechanical Engineering and M.A. in Mathematics both from Pennsylvania State University in 2002 and 2003, respectively, and his PhD in Mechanical Engineering from Massachusetts Institute of Technology (MIT) in 2007. 

Since 2007 he has served in various roles of increasing responsibility at RTX Technology Research Center (formerly United Technologies Research Center), where he is now a Principal Technical Fellow of Dynamical Systems and Controls. During 2007-2009 at research center, he worked on problems related to model reduction, estimation and control in distributed parameter systems, uncertainty quantification in large scale dynamic networks, and sensor network control and coordination. Since 2010 he has served as a principal investigator of projects in the areas of collaborative autonomy with emphasis on human machine teams, and data analytics with an interdisciplinary approach combining techniques from dynamical systems, control theory and machine learning.  During 2021-2022 he was also an Acting Discipline Lead for the Optimization and Control Technologies discipline. In his current role as a technical fellow, he also provides technical leadership and direction for applications of systems and controls, and more broadly applied mathematics to RTX products, identification of strategic opportunities, leveraging of external relationships, and staff technical guidance and mentoring. He is a member of Connecticut Academy of Science and Engineering (CASE), IEEE Senior Member,  and a member of Tau Beta Pi and Sigma Xi . 

Links:

• CV

• google scholar, research gate

Research interests

I am broadly interested in the areas of systems and control, data sciences and applied mathematics. Particular topics include:

• Nonlinear dynamical systems, operator theoretic techniques

• Model reduction, estimation and control of high dimensional dynamical systems

• Learning for dynamics and controls 

• Decision making under uncertainty including  reinforcement learning 

• Applied machine learning 

• Multi agent planning and coordination, and human supervisory control

• Quantum computing 

Applications: data driven systems and controls, collaborative autonomy,  sensor resource management, guidance, navigation and control,  human machine teaming, prognostics and health management in aerospace systems,  insitu monitoring and controls in advanced/additive manufacturing, automated human inspection, biology, vortex dynamics, fluid mixing and separation.

Further details can be found here: research projects and related publications. 

Selected honors and awards

• Elected to Connecticut Academy of Science and Engineering (CASE), 2024.

• Outstanding Achievement Award, Raytheon Technologies Research Center, 2021.

• 2017 Grainger Grant Award by the Grainger Foundation and the National Academy of Engineering (NAE).

• Outstanding Achievement Award, United Technologies Research Center, 2017.

• Invited to US Frontiers of Engineering (FOE) Symposium 2016 by the National Academy of Engineering (NAE).

• Technical Excellence Award, United Technologies Research Center, 2015- Highest Individual Award at UTRC for contributions to science and technology.

• Padmakar P. Lele Student Award for Outstanding Research and Thesis, Department of Mechanical Engineering, MIT, May 2007.

Press coverage 

• CASE 2024, Press Release.

• AFRL's Airlift Challenge, News Article. 

• SCORCH Project, News Article. 

• 2017 Grainger Grant, Press Release. 

• National Academy of Engineering, 2016 US Frontiers of Engineering Symposium.

• MIT solves 100-year-old engineering problem, MIT News and MIT Tech Talk.