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Matthew Ishahak
Assistant Professor, Chemical, Environmental and Materials Engineering
Matthew Ishahak is an assistant professor in the Department of Chemical, Environmental and Materials Engineering at the University of Miami College of Engineering. He earned a bachelor's degree, master's degree and doctorate in biomedical engineering from the University of Miami. His doctoral research focused on engineering microfluidic systems known as organs-on-chips to replicate human biology and model disease. He was the inaugural Rita Levi-Montalcini Postdoctoral Fellow at the Washington University School of Medicine in St. Louis Center for Regenerative Medicine, where he applied next-generation sequencing and genetic engineering to study human stem cell-derived organoids.
Ishahak's research focuses on applying synthetic biology and bioengineering to advance understanding of human development and disease progression. His work combines stem cell biology, tissue engineering and multi-omic bioinformatics to study organoid-based model systems. His laboratory develops brain, kidney and pancreatic organoids to investigate diseases including cancer and diabetes. A central component of his research is the use of multi-omics to construct gene regulatory networks and perform in silico genetic perturbation experiments, helping identify drivers of cell fate and disease.
His research has been published in leading journals, including Nature Communications, Nature Cell Biology, Advanced Science, Cell Reports and Science Advances. Ishahak is also committed to mentoring students at all levels, with a particular focus on supporting underrepresented minorities in STEM fields.
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Seung Ho (Steve) Woo
Assistant Professor, Industrial and Systems Engineering
Seung Ho (Steve) Woo is an assistant professor in the University of Miami Department of Industrial and Systems Engineering. He earned a Ph.D. in industrial engineering from Purdue University in 2026 and a B.S.E. and M.S.E. in industrial and operations engineering with higher honors from the University of Michigan, Ann Arbor.
His research focuses on the intersection of AI-driven predictive modeling and next-generation simulation paradigms, particularly exploring their economic and societal implications. His work leverages advanced methodologies on AI and decision-making algorithms for risk analysis of complex systems, integrating predictive modeling, deep learning, reinforcement learning, and agent-based simulation. His work aims to construct robust predictive models for critical challenges in crisis management, infrastructure resilience, advanced manufacturing, healthcare, and supply chain operations.
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