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Visvesh Sathe

  • Assistant Professor

Visvesh Sathe joined the University of Washington Department of Electrical Engineering in 2013. Prior to joining the faculty at the UW, he served as a Member of Technical Staff in the Low-Power Advanced Development Group at AMD, where his research focused on inventing and developing new technologies for next-generation microprocessors. Sathe led the research and development effort at AMD that resulted in the first-ever resonant clocked commercial microprocessor. In addition, several of his other inventions have been adopted for use in future-generation microprocessors. His doctoral thesis was selected as the best dissertation for 2007 in electrical engineering and computer science at the University of Michigan, Ann Arbor, and was also nominated for the university’s Rackham Graduate School Distinguished Dissertation Award.

Sathe’s group conducts research over a variety of areas covering circuits and architectures for low power computing and biomedical systems.  He serves as a member of the Technical Program Committees of the Custom Integrated Circuits Conference and has previously served as a guest editor for the Journal of Solid-State Circuits.

Research Interests

  • Ultra low-power biomedical sensing, recording and computation
  • Next generation clocking architectures for computing and communication
  • Supply conversion, distribution and regulation
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                    [post_content] => [caption id="attachment_10991" align="alignleft" width="458"] From left: Dr. Anthony Smith and Professor Visvesh Sathe[/caption]

Brain computer interfaces (BCIs) offer a direct communication pathway between the brain and external technologies. BCIs are of significant research interest for their potential role in repairing human cognitive or sensory-motor functions for conditions like stroke and paralysis.

Although BCIs present great opportunities for brain to device connectivity, there are several challenges in application: next-generation BCIs require a large number of neural recording and stimulation electrodes for broad and dense coverage. Existing recording electronics techniques are unable to scale to these large counts without a prohibitive increase in silicon-die area. Further, BCIs generate large stimulation artifacts, obscuring important signals shortly after stimulation.

In an article, entitled “A Scalable, Highly-Multiplexed Delta-Encoded Digital Feedback ECoG Recording Amplifier with Common and Differential-Mode Artifact Suppression,” UW researchers present a system that addresses these challenges, increasing channel recording density by ten times current state-of-the-art systems.

“The focus of the effort was on developing architectural techniques that could be leveraged to allow us to design high-density recording electronics,” UW electrical engineering Assistant Professor and PI on the project Visvesh Sathe said. “The system allows for highly multiplexed recording channels, exploiting the inherent structure in neural signals to achieve high precision recording using simple, robust circuits. The system also suppresses, for the first time, both common-mode and differential-mode artifacts.”

The system is useful for a variety of bio-potential signal acquisition applications, offering support to researchers when signals from the human body have to be read. This process expands to numerous medical applications, including nervous system diseases like Alzheimer’s and Parkinson’s.

"This work is a first step toward a realistic Bidirectional Brain Computer Interface on a single chip,” senior author on the paper Anthony Smith (Ph.D. ’17) said. “The next step will be integrating this system with the CMOS-compatible stimulation platform that has also been developed at UW and adding on-chip computation to enable closed-loop operation."

Additional authors on the paper include UW electrical engineering graduate student John Uehlin, UW physiology and biophysics Research Associate Steve Perlmutter and UW electrical engineering Associate Professor Chris Rudell.

The work is funded by the Center for Sensorimotor Neural Engineering (CSNE), a UW-based center established through the National Science Foundation Engineering Research Centers (NSF ERC) program.
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Rajesh Rao Chet Moritz Howard Chizeck Matt Reynolds Smith_Joshua__1457646140_128.95.215.177 Blake Hannaford Chris Rudell Visvesh Sathe
Rajesh Rao Chet Moritz Howard Chizeck Matt Reynolds Joshua Smith Blake Hannaford Chris Rudell Visvesh Sathe
To support the development of implantable devices that can restore movement, and improve the overall quality of life, for people with spinal cord injury or stroke, UW’s Center for Sensorimotor Neural Engineering (CSNE) has received $16 million in funding from the National Science Foundation. The funding, dispersed during the next four years, will allow researchers to continue their cutting-edge work, with the goal of having proof-of-concept demonstrations in humans within the next five years. Based at the UW, the CSNE is directed by EE Adjunct Faculty member Rajesh Rao, who is a UW professor of computer science and engineering. Founded in 2011, the CSNE is one of 17 Engineering Research Centers funded by the National Science Foundation. Core partners are located at the Massachusetts Institute of Technology and San Diego State University. A prime example of cross-campus collaboration, research is being undertaken by a multi-disciplinary team including several UW EE faculty members: Howard Chizeck, Blake Hannaford, Matt Reynolds, Chris Rudell, Visvesh Sathe and Joshua Smith. “UW is extremely fortunate to have visionary leaders in Director Rajesh Rao and Deputy Director Chet Moritz, who are spearheading the cutting edge research at CSNE,” said EE Chair Radha Poovendran. “Under their leadership, the CSNE is growing to be a place where fundamental and translation research for the benefit of society are fostered.” To restore sensorimotor function and neurorehabilitation, CSNE researchers are working to build closed-loop co-adaptive bi-directional brain-computer interfaces that can both record from and stimulate the central nervous system. The devices essentially form a bridge between lost brain connections, achieved by decoding brain signals produced when a person decides they would like to move their arm and grasp a cup. Specific parts of the spinal cord are then stimulated to achieve the desired action. By wirelessly transmitting information, damaged areas of the brain are avoided. Researchers are also working to improve current devices on the market, such as deep brain stimulators that are used to treat Parkinson’s disease. A challenge with current systems is that they are constantly “on” and may provide stimulation to patients when not needed, resulting in unintended side effects as well as reduced battery life. CSNE researchers are working to make these systems "closed-loop," turning them on only when the patient intends to move. 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2017-07-07 21:06:13 [post_content] => [caption id="attachment_10991" align="alignleft" width="458"] From left: Dr. Anthony Smith and Professor Visvesh Sathe[/caption] Brain computer interfaces (BCIs) offer a direct communication pathway between the brain and external technologies. BCIs are of significant research interest for their potential role in repairing human cognitive or sensory-motor functions for conditions like stroke and paralysis. Although BCIs present great opportunities for brain to device connectivity, there are several challenges in application: next-generation BCIs require a large number of neural recording and stimulation electrodes for broad and dense coverage. Existing recording electronics techniques are unable to scale to these large counts without a prohibitive increase in silicon-die area. Further, BCIs generate large stimulation artifacts, obscuring important signals shortly after stimulation. In an article, entitled “A Scalable, Highly-Multiplexed Delta-Encoded Digital Feedback ECoG Recording Amplifier with Common and Differential-Mode Artifact Suppression,” UW researchers present a system that addresses these challenges, increasing channel recording density by ten times current state-of-the-art systems. “The focus of the effort was on developing architectural techniques that could be leveraged to allow us to design high-density recording electronics,” UW electrical engineering Assistant Professor and PI on the project Visvesh Sathe said. “The system allows for highly multiplexed recording channels, exploiting the inherent structure in neural signals to achieve high precision recording using simple, robust circuits. The system also suppresses, for the first time, both common-mode and differential-mode artifacts.” The system is useful for a variety of bio-potential signal acquisition applications, offering support to researchers when signals from the human body have to be read. This process expands to numerous medical applications, including nervous system diseases like Alzheimer’s and Parkinson’s. "This work is a first step toward a realistic Bidirectional Brain Computer Interface on a single chip,” senior author on the paper Anthony Smith (Ph.D. ’17) said. “The next step will be integrating this system with the CMOS-compatible stimulation platform that has also been developed at UW and adding on-chip computation to enable closed-loop operation." Additional authors on the paper include UW electrical engineering graduate student John Uehlin, UW physiology and biophysics Research Associate Steve Perlmutter and UW electrical engineering Associate Professor Chris Rudell. The work is funded by the Center for Sensorimotor Neural Engineering (CSNE), a UW-based center established through the National Science Foundation Engineering Research Centers (NSF ERC) program. [post_title] => UW team achieves a factor of 10 performance improvement for BCI Recording Systems [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => researchers-advance-state-of-the-art-neural-recording-for-bci-applications [to_ping] => [pinged] => [post_modified] => 2017-07-18 14:02:00 [post_modified_gmt] => 2017-07-18 21:02:00 [post_content_filtered] => [post_parent] => 0 [guid] => http://www.ee.washington.edu/?post_type=spotlight&p=10990 [menu_order] => 33 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [1] => WP_Post Object ( [ID] => 1407 [post_author] => 15 [post_date] => 2015-12-11 00:58:54 [post_date_gmt] => 2015-12-11 00:58:54 [post_content] =>
Rajesh Rao Chet Moritz Howard Chizeck Matt Reynolds Smith_Joshua__1457646140_128.95.215.177 Blake Hannaford Chris Rudell Visvesh Sathe
Rajesh Rao Chet Moritz Howard Chizeck Matt Reynolds Joshua Smith Blake Hannaford Chris Rudell Visvesh Sathe
To support the development of implantable devices that can restore movement, and improve the overall quality of life, for people with spinal cord injury or stroke, UW’s Center for Sensorimotor Neural Engineering (CSNE) has received $16 million in funding from the National Science Foundation. The funding, dispersed during the next four years, will allow researchers to continue their cutting-edge work, with the goal of having proof-of-concept demonstrations in humans within the next five years. Based at the UW, the CSNE is directed by EE Adjunct Faculty member Rajesh Rao, who is a UW professor of computer science and engineering. Founded in 2011, the CSNE is one of 17 Engineering Research Centers funded by the National Science Foundation. Core partners are located at the Massachusetts Institute of Technology and San Diego State University. A prime example of cross-campus collaboration, research is being undertaken by a multi-disciplinary team including several UW EE faculty members: Howard Chizeck, Blake Hannaford, Matt Reynolds, Chris Rudell, Visvesh Sathe and Joshua Smith. “UW is extremely fortunate to have visionary leaders in Director Rajesh Rao and Deputy Director Chet Moritz, who are spearheading the cutting edge research at CSNE,” said EE Chair Radha Poovendran. “Under their leadership, the CSNE is growing to be a place where fundamental and translation research for the benefit of society are fostered.” To restore sensorimotor function and neurorehabilitation, CSNE researchers are working to build closed-loop co-adaptive bi-directional brain-computer interfaces that can both record from and stimulate the central nervous system. The devices essentially form a bridge between lost brain connections, achieved by decoding brain signals produced when a person decides they would like to move their arm and grasp a cup. Specific parts of the spinal cord are then stimulated to achieve the desired action. By wirelessly transmitting information, damaged areas of the brain are avoided. Researchers are also working to improve current devices on the market, such as deep brain stimulators that are used to treat Parkinson’s disease. A challenge with current systems is that they are constantly “on” and may provide stimulation to patients when not needed, resulting in unintended side effects as well as reduced battery life. CSNE researchers are working to make these systems "closed-loop," turning them on only when the patient intends to move. See Also: Seattle Times Article UW Today Article [post_title] => CSNE Receives $16 Million to Continue Developing Implantable Devices to Treat Paralysis [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => csne-receives-16-million-to-continue-developing-implantable-devices-to-treat-paralysis [to_ping] => [pinged] => [post_modified] => 2016-12-16 15:41:14 [post_modified_gmt] => 2016-12-16 23:41:14 [post_content_filtered] => [post_parent] => 0 [guid] => http://hedy.ee.washington.edu/?post_type=spotlight&p=1407 [menu_order] => 924 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) ) [post_count] => 2 [current_post] => -1 [in_the_loop] => [post] => WP_Post Object ( [ID] => 10990 [post_author] => 12 [post_date] => 2017-07-07 14:06:13 [post_date_gmt] => 2017-07-07 21:06:13 [post_content] => [caption id="attachment_10991" align="alignleft" width="458"] From left: Dr. Anthony Smith and Professor Visvesh Sathe[/caption] Brain computer interfaces (BCIs) offer a direct communication pathway between the brain and external technologies. BCIs are of significant research interest for their potential role in repairing human cognitive or sensory-motor functions for conditions like stroke and paralysis. Although BCIs present great opportunities for brain to device connectivity, there are several challenges in application: next-generation BCIs require a large number of neural recording and stimulation electrodes for broad and dense coverage. Existing recording electronics techniques are unable to scale to these large counts without a prohibitive increase in silicon-die area. Further, BCIs generate large stimulation artifacts, obscuring important signals shortly after stimulation. In an article, entitled “A Scalable, Highly-Multiplexed Delta-Encoded Digital Feedback ECoG Recording Amplifier with Common and Differential-Mode Artifact Suppression,” UW researchers present a system that addresses these challenges, increasing channel recording density by ten times current state-of-the-art systems. “The focus of the effort was on developing architectural techniques that could be leveraged to allow us to design high-density recording electronics,” UW electrical engineering Assistant Professor and PI on the project Visvesh Sathe said. “The system allows for highly multiplexed recording channels, exploiting the inherent structure in neural signals to achieve high precision recording using simple, robust circuits. The system also suppresses, for the first time, both common-mode and differential-mode artifacts.” The system is useful for a variety of bio-potential signal acquisition applications, offering support to researchers when signals from the human body have to be read. This process expands to numerous medical applications, including nervous system diseases like Alzheimer’s and Parkinson’s. "This work is a first step toward a realistic Bidirectional Brain Computer Interface on a single chip,” senior author on the paper Anthony Smith (Ph.D. ’17) said. “The next step will be integrating this system with the CMOS-compatible stimulation platform that has also been developed at UW and adding on-chip computation to enable closed-loop operation." Additional authors on the paper include UW electrical engineering graduate student John Uehlin, UW physiology and biophysics Research Associate Steve Perlmutter and UW electrical engineering Associate Professor Chris Rudell. The work is funded by the Center for Sensorimotor Neural Engineering (CSNE), a UW-based center established through the National Science Foundation Engineering Research Centers (NSF ERC) program. 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Representative Publications

  • V. S. Sathe, S. Arekapudi, A. Ishii, C. Ouyang, M. C. Papaefthymiou, S. Naffziger, “Resonant Clock Design for a Power-efficient, High-volume x86-64 Microprocessor”, IEEE Journal of Solid-State Circuits, Invited paper, Special Issue on ISSCC ‘14, vol. 48, no. 1, pp. 140–149, Jan. 2013.
  • S.K. Shin, J.C. Rudell, D.C. Daly, C.E. Muñoz, D.Y. Chang, K. Gulati, H.S. Lee and M.Z. Straayer, “A 12-bit 200 MS/s Zero-Crossing-Based Pipelined ADC with Early sub-ADC Decision and Output Residue Background Calibration,” Proc. IEEE J. Solid-State Circuits,” vol. 49, pp. 1366-1382, Jun., 2014.
  • V. S. Sathe, “Quasi-Resonant Clocking : A Run-time Control Approach for True Voltage-Frequency-Scalability,” IEEE ISLPED, La Jolla, 2014.
  • V. S. Sathe, Jae-sun Seo “Analysis and Optimization of CMOS Switched-Capacitor Voltage Converters,” IEEE ISLPED, Rome, Italy 2015
  • F. Rahman and V. S. Sathe, “Voltage-Scalable Frequency Independent Quasi-Resonant Clocking Implementation of a 0.7–1.2V DVFS System”, ISSCC 2016
  • W. A. Smith, B. Mogen, E. Fetz, V. S. Sathe and B. Otis, “Exploiting Electrocorticographic Spectral Characteristics for Optimized Signal Chain Design: A 1.08 μW Analog Front End with Reduced ADC Resolution Requirements”, to appear in Transactions in Biomedical Circuits and Systems 2016
Visvesh Sathe Headshot
Phone206-543-7635
sathe@uw.edu
Web PageClick Here
Mail
M314 EEB

Associated Labs

Research Areas

Education

  • Ph.D. Electrical Engineering, 2007
    University of Michigan, Ann Arbor
  • M.S. Electrical Engineering, 2004
    University of Michigan, Ann Arbor
  • B.S. Technology, 2001
    Indian Institute of Technology, Bombay