Dr. Yurii Vlasov is a John Bardeen Endowed Chair in Electrical and Computer Engineering and Physics at the University of Illinois at Urbana-Champaign. He is tenured with the departments of Electrical and Computer Engineering, Physics, Materials Science and Engineering, and Bio-Engineering, as well as Carle Illinois College of Medicine. At the UIUC he established the Integrated Neurotechnology lab devoted to development of advanced engineering approaches aimed at reverse engineering of the brain circuits. The major themes include development of silicon-based nanofluidic and nanophotonic neural probes, in-vivo neurobiological experiments with massive recording and manipulation of brain activity, and, lastly, development of machine-learning algorithms to analyze large neural datasets.
Prior to joining the UIUC in 2016, Dr. Vlasov held various research and managerial positions at the IBM T.J. Watson Research Center in N.Y. where he led broad company-wide efforts in integrated silicon nanophotonics and more recently in neuromorphic computing architectures. He initiated the Silicon Nanophotonics project in 2001 and managed it for over 15 years from its early fundamental research stage up to commercial manufacturing of optical transceivers for large-scale datacenters and supercomputers. The technology has been fully qualified and deployed for commercial production at GlobalFoundries.
Prior to joining IBM in 2001, Dr. Vlasov developed semiconductor nanophotonics at the N.E.C. Research Institute in Princeton, N.J. and at the Strasbourg IPCMS Institute in France. For over a decade, he was also a Research Scientist with the Ioffe Institute of Physics and Technology in St. Petersburg, Russia working on optics of nanostructured semiconductors. He received his M.S. from the University of St. Petersburg (1988) and Ph.D from the Ioffe Institute (1994), both in physics.
Dr. Vlasov is a member of the National Academy of Engineering and a Fellow of the APS, the IEEE, and the OSA. He has published over 300 papers, filed over 100 patents, and delivered over 100 invited, plenary and tutorial talks. He received the IBM CEO Corporate Award, the Best of IBM Award, and several IBM Outstanding Technical Achievement Awards, as well as was named Scientist of the Year by the Scientific American journal. Dr. Vlasov and his work has been covered in numerous major newspapers, including New York Times, Forbes, Wall Street Journal, and others. It has been featured on television news programs including The Tonight Show, ABC, CBS, etc. It has also been highlighted in review columns on Science Daily, Scientific American Journal, New Scientist, etc.
Our goal is to understand basic principles of cortical computations, from the circuit to systems levels. We focus on understanding how the ethologically-relevant features of a sensory scene are extracted from the raw sensory flow, where this information is parsed, and how it guides complex behavior.
One of our major projects is focused on primary (S1 or barrel cortex) and secondary (S2) somatosensory cortices in rodents that process information from their whiskers. We combine electrophysiology and optogenetics to record neural activity while animals actively navigate in virtual reality and solve behavioral tasks. Correlations of brain activity with animal behavior and choices provide insights on mechanisms of cortical processing.
- Electophysiology with multi-electrode silicon probes to record from a massive number of neurons across many brain regions simultaneously in alive and behaving animals.
- Behaviorial paradigms in virtual reality to study neural circuits in almost natural environment while mice are engaged in goal-directed behavior. Virtual reality systems allow full control over behaviorial tasks and quantitative measurements of resulting behavior.
- Optogenetics to identify and record activity of specific cell types during behavior and for manipulating neural circuits to reverse-engineer their functionality.
- Neuroanatomy leveraging new viral, genetic, and computational tools to provide insights into brain circuits functionality.
- Machine learning based analytical methods to extract dynamical patterns of neural activity that are correlated with animal behavior and choice.
N.Sofroniew, Y.Vlasov, S. Hires, J.Freeman, K.Svoboda, “Neural coding in barrel cortex during whisker-guided locomotion”, eLife;4:e12559 (2015))
Additional Campus Affiliations
John Bardeen Chair, Electrical and Computer Engineering
Professor, Electrical and Computer Engineering
Professor, Micro and Nanotechnology Lab
Professor, Materials Science and Engineering
Professor, Biomedical and Translational Sciences
Professor, Beckman Institute for Advanced Science and Technology
Brenden, C. K., Iyer, H., Zhang, Y., Kim, S., Shi, W., & Vlasov, Y. A. (2023). Enhancement of faradaic current in an electrochemical cell integrated into silicon microfluidic channels. Sensors and Actuators B: Chemical, 385, Article 133733. https://doi.org/10.1016/j.snb.2023.133733
Ding, Y., & Vlasov, Y. (2023). Pre-neuronal processing of haptic sensory cues via dispersive high-frequency vibrational modes. Scientific reports, 13(1), Article 14370. https://doi.org/10.1038/s41598-023-40675-8
Shi, W., Bell, S., Iyer, H., Brenden, C. K., Zhang, Y., Kim, S., Park, I., Bashir, R., Sweedler, J., & Vlasov, Y. (2022). Integrated silicon microfluidic chip for picoliter-scale analyte segmentation and microscale printing for mass spectrometry imaging. Lab on a chip, 23(1), 72-80. https://doi.org/10.1039/d2lc00688j
Zhang, Y., Li, K., Zhao, Y., Shi, W., Iyer, H., Kim, S., Brenden, C., Sweedler, J. V., & Vlasov, Y. (2022). Attomole-Level Multiplexed Detection of Neurochemicals in Picoliter Droplets by On-Chip Nanoelectrospray Ionization Coupled to Mass Spectrometry. Analytical Chemistry, 94(40), 13804-13809. https://doi.org/10.1021/acs.analchem.2c02323
Zhang, Y., Kim, S., Shi, W., Zhao, Y., Park, I., Brenden, C., Iyer, H., Jha, P., Bashir, R., Sweedler, J. V., & Vlasov, Y. (2022). Droplet-assisted electrospray phase separation using an integrated silicon microfluidic platform. Lab on a chip, 22(1), 40-46. https://doi.org/10.1039/d1lc00758k