Our People

Meet the team behind the Predictive Science Laboratory — faculty, postdoctoral researchers, and students advancing scientific machine learning and engineering innovation.

Current Members

Faculty

Ilias Bilionis

Ilias Bilionis

Professor of Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Scientific machine learning, uncertainty quantification, information field theory
  • ibilion@purdue.edu

Research Scientists

Atharva Hans

Atharva Hans

Research Scientist
  • Regenstrief Center for Healthcare Engineering, Purdue University
  • Scientific machine learning, uncertainty quantification, physics-informed deep learning, 4D flow MRI, cardiovascular hemodynamics, medical image analysis, agentic AI for scientific workflows
  • hans1@purdue.edu

Postdoctoral Researchers

Alex Alberts

Alex Alberts

Postdoctoral Researcher
  • School of Mechanical Engineering, Purdue University
  • Information field theory, inverse problems, uncertainty quantification, Gaussian processes, scientific machine learning
  • albert31@purdue.edu
Manoja Rajalakshmi Aravindakshan

Manoja Rajalakshmi Aravindakshan

Postdoctoral Researcher
  • School of Mechanical Engineering, Purdue University
  • Lumped parameter modelling, Organ-on-chip models, Scientific machine learning
  • maravind@purdue.edu

Graduate Students

Abhishek Singh

Abhishek Singh

PhD Student in Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Inverse problems; Bayesian inference; uncertainty quantification; data assimilation; physics-informed ML; volumetric PIV/PTV; 4D Flow MRI; spatiotemporal flow reconstruction
  • sing1062@purdue.edu
Andrew Voss

Andrew Voss

MS Student, Mechanical Engineering
  • McCallie School
  • Bayesian Optimal Experiment Design, Additive Manufacturing, Aerospace Structures, Loads, and Dynamics, and curriculum design
  • voss35@purdue.edu
Angkon Biswas

Angkon Biswas

PhD Student in Biomedical Engineering
  • Weldon School of Biomedical Engineering
  • Biomedical Imaging, Computer Vision, Deep Learning, Biofluid mechanics, Computational Fluid Dynamics, Particle Imaging Velocimetry
  • biswas61@purdue.edu
Anubhav Dey

Anubhav Dey

PhD Student in Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Scientific machine learning, uncertainty quantification, Bayesian inverse problems
  • dey24@purdue.edu
Ben C. Wassgren

Ben C. Wassgren

MS Student, Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • bwassgre@purdue.edu
Jaehyun Go

Jaehyun Go

PhD Student in Civil Engineering
  • Lyles School of Civil Engineering, Purdue University
  • Building energy modeling, Bayesian decision-making, uncertainty quantification, smart building systems
  • go16@purdue.edu
Mark Wilkinson

Mark Wilkinson

PhD Student in Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Scientific machine learning, Finite elements, Solid mechanics, Bayesian Inverse problems, Group theory
  • wilki114@purdue.edu
Maxwell Bolt

Maxwell Bolt

PhD Student in Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Scientific machine learning, AI agents for scientific discovery, stochastic differential equations
  • boltm@purdue.edu
Motahareh Mirfarah

Motahareh Mirfarah

PhD Student in Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Scientific machine learning, Bayesian inverse problems, uncertainty quantification, model form uncertainty, cyber-physical systems
  • mmirfara@purdue.edu
Rohan Dekate

Rohan Dekate

PhD Student in Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Operator Learning, Scientific Machine Learning, Uncertainty Quantification, Bayesian Inverse Problems, Computer Vision, Computational Imaging, Numerical Optimization
  • dekate@purdue.edu
Shrenik Zinage

Shrenik Zinage

PhD Student in Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Scientific Machine Learning, Uncertainty Quantification, Causality, Digital Twins, Control
  • szinage@purdue.edu
Sreehari Manikkan

Sreehari Manikkan

PhD Student in Mechanical Engineering
  • School of Mechanical Engineering, Purdue University
  • Bayesian inverse problems, Dynamics discovery, Autonomous cyber physical systems, Digital twins
  • smanikka@purdue.edu

Wesley Holt

PhD Student
  • Mechanical Engineering
  • Scientific machine learning, Bayesian hierarchical modeling, information field theory, agentic AI, pharmacokinetic modeling
  • holtw@purdue.edu

Undergraduate Students

Aryan Goel

Aryan Goel

Undergraduate Research Assistant
  • School of Science, Purdue University
  • Computational graph frameworks, Domain-specific languages for AI
  • goel137@purdue.edu
Christian Riddle

Christian Riddle

Undergraduate Research Assistant
  • School of Mechanical Engineering, Purdue University
  • Causality, Scientific Machine Learning
  • riddle37@purdue.edu
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Darian Clarke Douglas

Undergraduate Research Assistant
  • College of Engineering, Purdue University
  • Extraterrestrial Habitats, Damage Prediction in Space, Category Theory
  • dougl154@purdue.edu
Hudson Schneider

Hudson Schneider

Undergraduate Research Assistant
  • Department of Agricultural and Biological Engineering, Purdue University
  • Bayesian computation, agentic AI, pharmacokinetic modeling and calibration, compartmental pharmacokinetic analysis
  • schne167@purdue.edu
Jonathan Baldini

Jonathan Baldini

Undergraduate Research Assistant
  • School of Mechanical Engineering, Purdue University
  • Uncertainty quantification, sensitivity analysis
  • jbaldin@purdue.edu
Jordan Reynolds

Jordan Reynolds

Undergraduate Research Assistant
  • Department of Mathematics, Purdue University
  • AI-assisted scientific software development, dynamical systems modeling, pharmacokinetic modeling workflows
  • reyno223@purdue.edu
Maurice Reimer

Maurice Reimer

Undergraduate Research Assistant
  • School of Mechanical Engineering, Purdue University
  • LLM agents
  • reimerm@purdue.edu
Rachel D'Souza

Rachel D’Souza

Undergraduate Research Assistant
  • Elmore Family School of Electrical and Computer Engineering, Purdue University
  • Optical/photonic device testing & lifetime measurements, Experimental design & quantitative data analysis, Proteomics data preprocessing & normalization (R), Statistical testing & biomarker discovery modeling, Computational biology visualization & interpretation, Scientific writing & research communication, Cross-disciplinary research integration
  • dsouza36@purdue.edu
Saivisvesh (Sai) Karthik

Saivisvesh (Sai) Karthik

Undergraduate Research Assistant
  • School of Biomedical Engineering, Purdue University
  • karthik9@purdue.edu
Sophia Vlachos

Sophia Vlachos

Undergraduate Research Assistant
  • School of Biomedical Engineering, Purdue University
  • svlachos@purdue.edu
Virginia Luo

Virginia Luo

Undergraduate Research Assistant
  • College of Science, Purdue University
  • luo590@purdue.edu