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Photo of Ben-Yakar, Adela

ben-yakar@mail.utexas.edu
512-475-9280
Office Location: ETC 7.132

Adela Ben-Yakar

Professor

Mr. N Doug Williams Memorial Centennial Fellow in Engineering

Department Research Area:
Biosensors and Instrumentation
Imaging and Image-Guided Interventions

 

Research Focus

Dr. Adela Ben-Yakar is Harry Jr. L. Kent Endowed Professor in Departments of Biomedical Engineering, Mechanical Engineering, and Electrical and Computer Engineering at The University of Texas at Austin. Dr. Ben-Yakar received her Ph.D. from Stanford University in Engineering and completed postdoctoral work at Stanford and Harvard Universities in Physics. She is the Fellow of the SPIE, Optica, and AIMBE and the recipient of the Fulbright Scholarship, Zonta Amelia Earhart Award, NSF Career Award, Human Frontier Science Program Research Award, and NIH Director’s Transformative Award.

Dr. Ben-Yakar’s research focus is in the areas of ultrafast laser microsurgery, nonlinear imaging, endoscopy, high-speed nonlinear microscopy for brain imaging, high-throughput optical and microfluidic systems for high-content screening of model organisms and organoids with application in the areas of nerve regeneration, neurodegenerative diseases, spine surgery, and cancer diagnostics. Her research group has published in high impact journals such as Nature, Nature Methods, Nature Communications, Scientific Reports, Nano Letters, etc. She has eight issued and seven pending patents. Together with her group members, she co-founded vivoVerse, which provides cost effective and rapid testing of drugs and chemicals using a high-throughput microfluidic imaging platform integrated with AI-enabled data analytics.

Research Interests
  • Development of novel technologies for therapeutic and diagnostic applications of ultrafast lasers
    • Ultrafast laser microsurgery and endoscopy for clinical translation
    • Two-photon microscopy and endoscopy for cancer diagnosis
  • Development of ultrafast microscopy systems
    • LEAD (Line Excitation Array Detection) 3D-imaging flow cytometry imaging at 0.8 million frames per second
    • Two-photon LEAD microscopy for brain imaging at 100,000 frames per second
  • High-throughput microfluidic systems for high-content screening of model organisms and organoids
  • Machine learning as applied to biomedical optical microscopy
  • Femtosecond laser microdissection for single cell isolation and single cell RNA-sequencing
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