Alumni Members
Former Members
Postdoctoral Researchers
Biswarup Bhattacharyya
Postdoctoral Researcher at the Predictive Science Laboratory.
Fall 2021 – Spring 2022.
Graduate students
Graduate students who completed their M.S. or Ph.D. research under the supervision of the laboratory.
Vanessa Kwarteng
PhD dissertation: Game-theoretic design for energy-efficient behaviors in residential communities.
Fall 2018 – Summer 2023.
Heliben Parikh Naimeskumar
MS Thesis: Bayesian optimization for design parameters of autoinjectors.
Spring 2023.
Sayak Chatterjee
Physics-informed neural networks.
Spring 2022.
Shrenik Zinage Vijaykumar
MS Thesis: Investigation of different data-driven approaches for modeling engineered systems.
Fall 2022.
Sharmila Karumuri
PhD dissertation: Physics-informed machine learning with applications to high-dimensional uncertainty propagation, inverse, and design problems.
Fall 2017 – Fall 2022.
Nimish Awalgaonkar
PhD dissertation: Sequential design of experiments for human preference elicitation with applications to human-building interactions.
Fall 2016 – Spring 2022.
Alana Kathleen Lund
PhD dissertation: Variational inference algorithms for health monitoring of structural systems.
Fall 2016 – Spring 2021.
Co-advised with Prof. S. Dyke.
Ali Lenjani
PhD dissertation: Automating decision support to address system resilience challenges.
Spring 2017 – Spring 2020.
Co-advised with Prof. S. Dyke.
Salar Safarkani
PhD dissertation: Game theoretic foundations of systems engineering.
Fall 2017 – Spring 2020.
Alex D. Casey
PhD dissertation: Estimation of melting point and sensitivity in energetic materials with statistical learning.
Fall 2018 – Spring 2020.
Co-advised with S. Son.
Abhijit Sahu
MS Thesis: Quantification of uncertainty in magnetic characteristics of steel and its effect on the torque profile of a permanent magnet machine.
Spring 2019.
Rohit Tripathy
PhD dissertation: High-dimensional uncertainty quantification.
Spring 2016 – Fall 2019.
Piyush Pandita
PhD dissertation: Bayesian optimal design of experiments for expensive black-box functions under uncertainty.
Spring 2019.
Co-advised with Prof. J. Panchal.
Francisco Peña
PhD dissertation: Efficient computation of fragility curves.
Spring 2019.
Co-advised with Prof. S. Dyke.
Majed Alrefae
PhD dissertation: Optimizing a chemical vapor deposition reactor for high quality graphene manufacturing.
Spring 2017.
Co-advised with Prof. T. S. Fisher.
Chaolei Chen
MS project: Oil reservoir modeling.
Fall 2015 – Spring 2016.
Zengyi Dou
MS Thesis: Bayesian global optimization approach to the oil well placement problem with quantified uncertainties.
Spring 2015.
Undergraduate Students
Undergraduate researchers who contributed to the laboratory through research programs and summer internships.
Bernardo De Araujo Alvarenga
NASA RETHi project on robotic agent simulation.
Summer 2021 – Spring 2022.
Prathyush Ravula
NASA RETHi project on robotic agent simulation.
Summer 2021 – Spring 2022.
Darya Julia Corry
Fault analysis of photovoltaic panels in a space environment.
Spring 2020.
Nicholas Masso
Stochastic modeling of meteorite showers on the Moon’s surface.
Spring 2020 – Fall 2020.
Jacob Evans
Literature review of human–machine interfaces for complex, critical systems.
Summer 2020 – Fall 2020.
Atharva Hans
Design experiments for optimal graphene growth using a chemical vapor deposition reactor.
Summer 2017.
Continued collaboration during Fall 2017 and from Summer 2018 onward.
Bottomley Fellowship recipient, Spring 2019.
Michael Wang
Quantifying the effect of manufacturing uncertainties in weakly coupled arrays of electromechanical oscillators.
Summer 2017.
Jinze Li
Learning algorithms for mechanical computers based on weakly coupled arrays of electromechanical oscillators.
Spring 2017.
Rahul Patni
Deep neural nets and engineering applications.
Spring 2016.
Juan Sebastian Martinez Carvajal
Enhancing graphene manufacturing by designing experiments for roll-to-roll chemical vapor deposition reactors.
Summer 2016.
Martin Figura
Multi-objective optimization of electric engines.
Summer 2016.
Juan Camilo Lopez Ramirez
Uncertainty analysis of granular crystals using Gaussian processes with built-in dimensionality reduction.
Summer 2015.
Zixuan Liu
Solving inverse problems efficiently using Bayesian global optimization.
Summer 2015.
Yinuo Li
Determining minimum energy structures of arbitrary clusters of atoms efficiently using Bayesian global optimization.
Summer 2015.