Research labs at Illinois Institute of Technology .

Amir Mostafaei Research Group

Metal additive manufacturingBinder jettingMicrostructure

Amir Mostafaei · Associate Professor

Printing a metal part is only the beginning of controlling its performance. Mostafaei investigates laser powder bed fusion and binder jetting, studying how processing choices affect microstructure and material properties. His interests span structural alloys, shape memory materials, lightweight metals, biomaterials, and composites. Research uses data analysis, micro computed tomography, and dynamic synchrotron imaging to examine manufacturing processes and outcomes. Postprocessing and corrosion studies connect the printed structure to its behavior in demanding environments, helping address material design and reliability questions in additive manufacturing.

CMIndependently curated · Unclaimed

Carrie M. Hall Research Group

Engine controlAlternative fuelsHydrogen fuel cells

Carrie M. Hall · Professor

Cleaner transportation requires understanding how energy systems behave and how to control them. Hall researches models and control methods for advanced engines and automotive powertrains. Her work considers alternative liquid and gaseous fuels, advanced combustion approaches, and hydrogen fuel cell systems, with energy efficiency and lower emissions as central motivations. These interests connect combustion and control engineering to transportation technologies. She also mentors Illinois Tech’s EcoCAR team, where students develop automotive systems and implement them in a Cadillac LYRIQ as part of a university engineering challenge.

CLIndependently curated · Unclaimed

Chun Liu Research Group

Nonlinear partial differential equationsComplex fluidsMultiscale modeling

Chun Liu · Chair and Professor of Applied Mathematics

Complex fluids and biological transport processes require mathematical descriptions that connect behavior across scales. Liu investigates nonlinear partial differential equations, variational methods, and multiscale modeling to address these systems. His listed projects include moving interfaces, diffusion, ionic fluids, and ion channels. Research connects the mathematical structure of models with applications in biophysics and materials science. These directions examine how continuum descriptions represent systems with interacting components, linking foundational questions about equations to physical problems involving flow, charge transport, and material organization.

GPIndependently curated · Unclaimed

Georgia Papavasiliou Research Group

Hydrogel biomaterialsTissue engineeringVascular regeneration

Georgia Papavasiliou · Professor of Chemical Engineering, Department Chair

An engineered tissue needs an environment that helps cells organize and develop. Papavasiliou designs synthetic hydrogel scaffolds whose stiffness, degradation, and biochemical composition can be adjusted to influence cell behavior and vascular growth. Her research includes scaffolds containing cells and material gradients for regenerating complex tissue interfaces. Other projects develop nanoparticle emulsions for targeted drug delivery and models that connect polymer structure to therapeutic diffusion. The work combines biomaterials design with tissue engineering, examining how material properties shape biological responses.

MBIndependently curated · Unclaimed

Machine Learning Laboratory

Interactive machine learningActive learningExplainable AI

Mustafa Bilgic · Professor of Computer Science, Department Chair

Machine learning becomes more useful when people can interact with it and understand its reasoning. Bilgic directs the Machine Learning Laboratory, studying active learning, interactive learning, and explainable AI. His interests include learning from rationales, probabilistic graphical models, and statistical relational learning. The group also investigates interpretability, robustness, and model stability. This research connects the way a system acquires information with the way its predictions can be examined, addressing questions about how human feedback and structured relationships contribute to learning.