Dr. Douglas Allaire
- Associate Professor, Mechanical Engineering
- Sallie and Don Davis ’61 Faculty Fellow
Research Interests
Machine learning
Artificial Intelligence
Optimization
Uncertainty quantification
Dr. Douglas Allaire holds B.S., M.S., and Ph.D. degrees from the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology. His current research focuses on the development of computational methods for the analysis, design, and operation of complex systems. He is specifically interested in uncertainty quantification, multidisciplinary design optimization, machine learning, and prescriptive analytics. He is currently working on projects involving the development of computational methods for enabling self-aware unmanned aerial vehicles, the development of optimal algorithms for multi-information source management in design of materials, and the efficient propagation of uncertainty through model chains.
Phone: (979) 458-9889
Email: [email protected]
Educational Background
- Ph.D, Aerospace Engineering, Massachusetts Institute of Technology — 2009
- M.S., Aerospace Engineering, Massachusetts Institute of Technology — 2006
- B.S., Aerospace Engineering, Massachusetts Institute of Technology — 2004
Awards & Honors
- 2018 ASME CIE Young Engineer Award
- 2018 ASME DAC Best Paper Award
- 2017 Dean of Engineering Excellence Award
- 2017 James J. Cain Graduate Teaching Award
Selected Publications
- Burrows, B. and Allaire, D., “Nonlinear Kalman filtering via measure change,” American Society of Mechanical Engineers (ASME) Journal of Dynamic Systems, Measurement, and Control 142(2):021006, 2020.
- Ghoreishi, S.F., Thomison, W.D., and Allaire, D., “Sequential Information-Theoretic and Reification-Based Approach for Querying Multi-Information Sources,” American Institute of Aeronautics and Astronautics (AIAA) Journal of Aerospace Information Systems, 16(12): 575-587, 2019.
- Ghoreishi, S.F., Molkeri, A., Arroyave, R., Allaire, D., and Srivastava, A., “Efficient Use of Multiple Information Sources in Material Design,” Acta Materialia, 180: 260-271, 2019.
- Ghoreishi, S.F., Friedman, S., and Allaire, D., “Adaptive dimensionality reduction for fast sequential optimization with Gaussian processes,” American Society of Mechanical Engineers (ASME) Journal of Mechanical Design, 141(7):071404, 2019.
- Swischuk, R. and Allaire, D., “A machine learning approach to aircraft sensor error detection and correction,” American Society of Mechanical Engineers (ASME) Journal of Computing and Infomation Science in Engineering, 19(4):041009, 2019.