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McKelvey School of Engineering

Brown School

ESE Seminar: Badri Roysam

Thursday, November 9, 2023 | 1:30 PM - 2:30 PM

Preston M. Green Hall, Rodin Auditorium, L0120
135 N Skinker Blvd, St. Louis, MO 63112, USA

Comprehensively Profiling and Exploring Multiplexed Immunofluorescence Images of Brain Tissue for Driving Therapeutics Development


Abstract: Brain tissue is multiscale-complex, intricate, and importantly, delicate. A brain injury can unleash a complex web of pathological alterations in all types of brain cells at multiple scales, ranging from individual cells to multi-cellular niches to the layered brain cytoarchitecture. Additional alterations result from secondary injuries, regenerative processes, inflammation, tissue remodeling, drug treatments, and drug side effects. Many of these alterations can be subtle and/or latent, only discernible by sensing changes in cell morphology, cyto- or myelo-architecture, or the expression patterns of molecular markers. Some alterations can be in brain regions that are distant from the injury/damage site. For rational therapeutics development, we need the ability to reveal these changes in a comprehensive manner.

In this talk, I will describe a comprehensive approach to pathological brain tissue mapping for. The idea is to replace the many low information content assays with a single comprehensive assay based on highly multiplexed imaging of brain sections employing 10 – 100 molecular markers, sufficient to capture all the major brain cell types, and their functional states, over extended brain regions. Analyzing these multiplex images is challenging due to their complexity, variability, and size. Training deep neural networks for conducting these tasks ordinarily requires significant human labor. I will describe a combination of fully automated signal reconstruction, scalable cell detection and phenotyping, and high-dimensional data analysis approaches to generate quantitative readouts of cellular alterations at multiple scales ranging from individual cells to multi-cellular units, large cellular ensembles (e.g., cortical layers), and atlas-defined brain regions. I will conclude with early results from a visual search engine that can learn the characteristics of one or more multiplex image datasets, and provide the ability to profile them driven by visual prompts.

Event Type



McKelvey School of Engineering


Science & Technology

Electrical & Systems Engineering


Event Contact

Aaron Beagle | abeagle@gmail.com

Speaker Information

Badri Roysam

University of Houston, Cullen College of Engineering, Department of Electrical and Computer Engineering

Hugh Roy and Lillie Cranz Cullen University Professor and Chair

Hosted by: Bruno Sinopoli


Bio: Badri Roysam is the Hugh Roy and Lillie Cranz Cullen University Professor, and Chair of the Electrical and Computer Engineering Department at the University of Houston. From 1989 to 2010, he was a Professor at Rensselaer Polytechnic Institute in Troy, New York, USA, where he directed the Rensselaer unit of the NSF Engineering Research (ERC) Center for Subsurface Sensing and Imaging Systems (CenSSIS ERC), and co-directed the Rensselaer Center for Open Source Software (RCOS). He received the Doctor of Science degree from Washington University, St. Louis, USA, in 1989. Earlier, he received his Bachelor’s degree from the Indian Institute of Technology, Madras, India in 1984.

Badri’s research is focused on the applications of multi-dimensional image processing, machine learning, artificial intelligence, bioinformatics, and high-performance computing to problems in fundamental and clinical biomedicine. His work is informed by diverse applications in cell-based cancer immunotherapy, drug discovery for traumatic brain injury, retinal diseases, neural implants, learning and memory impairments, binge alcohol, tumor cell phenotyping, stem-cell biology, stroke research, and neurodegenerative diseases.

Publications: https://scholar.google.com/citations?user=JL4E0ZoAAAAJ&hl=en

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