Walter Scott Jr. College of Engineering Professor (CV, Google Scholar)
IEEE Fellow, AAIA Fellow, ACM Distinguished Member
ACM SIGDA Vice Chair, Conference Chair
Director of Embedded, High Performance, and Intelligent Computing (EPIC) Lab
Department of Electrical and Computer Engineering
Departments of Computer Science, Systems Engineering (Joint appointments)

Office: B119 Engineering         Email: sudeep@colostate.edu
Phone: 970-491-0254                Fax: 970-491-2249

Office Address: 1373 Campus Delivery, Colorado State University
Fort Collins, CO 80523-1373

Sudeep Pasricha is a Walter Scott Jr. College of Engineering Professor in the Department of Electrical and Computer Engineering, the Department of Computer Science, and the Department of Systems Engineering at Colorado State University. He is Director of the Embedded, High Performance, and Intelligent Computing (EPIC) Laboratory and the Chair of Computer Engineering.

Short Bio: Prof. Pasricha received the B.E. degree in Electronics and Communication Engineering from Delhi Institute of Technology, India, in 2000, and his Ph.D. in Computer Science from the University of California, Irvine in 2008. He joined Colorado State University (CSU) in 2008. Prior to joining CSU, he spent several years working in STMicroelectronics and Conexant Inc. His research focuses on the design and application of innovative software algorithms (particularly AI and machine learning), hardware architectures, and hardware-software co-design techniques for energy-efficient, fault-tolerant, real-time, and secure computing. He has co-authored seven books, multiple patents, and published more than 300 research articles in peer-reviewed journals and conferences, workshops, and books. He has given multiple invited keynotes at IEEE and ACM conferences on a variety of topics that span optical computing, AI acceleration with silicon photonics, machine learning for IoT applications, sustainable datacenters, and robust chip-scale networks. His research has been funded by various sponsors including NSF, SRC, AFOSR, DOE, ORNL, DoD, Fiat-Chrysler, HPE, and NASA. He has served as General Chair and Program Committee Chair for multiple IEEE and ACM conferences, and also served in the Editorial board of multiple IEEE and ACM journals. He is a Fellow of the IEEE, Fellow of AAIA, Distinguished Member of the ACM, and an ACM Distinguished Speaker.

Research Interests: Prof. Pasricha’s research efforts span multiple computing scales, from computing chips to embedded/IoT/cyber-physical systems and high performance datacenters. Specific search focus areas include: 1) electronic design automation (EDA) and architectures for AI/ML acceleration and emerging manycore computing (silicon photonic and advanced electronic network-on-chip design, memory architectures, resource management, 3D ICs); 2) energy-efficient, secure, fault-tolerant, and real-time embedded and IoT systems, (across the domains of automotive, medical, and mobile applications); and 3) AI/ML driven resource management for high performance computing (exascale datacenters and supercomputers). Some details of ongoing research projects on these themes can be found here. A brief 5 minute overview of the EPIC lab can be found here. Selected videos from various projects can be found here. Prof. Pasricha’s academic lineage can be found here.

Awards: Prof. Pasricha has received 17 Best Paper Awards and Nominations at various IEEE and ACM conferences, including at DAC, ASPDAC, NOCS, GLSVLSI, IGSC, SLIP, AICCSA, and ISQED. Other notable awards include: 2022 ACM Distinguished Speaker, 2019 George T. Abell Outstanding Research Faculty Award, the 2016-2018 University Distinguished Monfort Professorship, 2016-2019 Walter Scott Jr. College of Engineering Rockwell-Anderson Professorship, 2018 IEEE-CS/TCVLSI mid-career research Achievement Award, the 2015 IEEE/TCSC Award for Excellence for a mid-career researcher, the 2014 George T. Abell Outstanding Mid-career Faculty Award, and the 2013 AFOSR Young Investigator Award.

Professional Service: Prof. Pasricha is currently the Vice Chair and Conference Chair of ACM SIGDA and a Senior Associate Editor for the ACM Journal of Emerging Technologies in Computing (JETC). He is in the Steering Committee of multiple conferences and journals, including IEEE Transactions on Sustainable Computing (TSUSC), IEEE/ACM Design Automation Conference (DAC), and IEEE/ACM Embedded Systems Week (ESWEEK). He is currently an Associate Editor for IEEE Transactions on Computers, ACM Transactions on Embedded Computing Systems (TECS), and IEEE Design & Test of Computers (D&T). He has served as Associate Editor for other journals in the past, including IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) and IEEE Consumer Electronics (CM). He has also served as the General Chair and Technical Program Chair for various IEEE/ACM conferences, and been part of the Organizing Committee of several IEEE/ACM conferences such as DAC, ESWEEK, ICCAD, GLSVLSI, NOCS, RTCSA, ICESS, etc. He holds an affiliate faculty member position at the Center for Embedded and Cyber-Physical Systems at UC Irvine. For professional service, he has received the 2019 ACM SIGDA Distinguished Service Award, the 2015 ACM SIGDA Service Award, and the 2012 ACM SIGDA Technical Leadership Award.

Note for Graduate Students:

I have multiple PhD positions available in my lab. In particular, I am looking for students to work on projects related to deep machine learning for sustainable datacenters, silicon photonic accelerators, chip-scale network and memory architectures, mobile indoor navigation, automotive security and environment perception, and multicore security. See here for more details. 

Recent News (~past year):

  • Feb 2024: I will be giving a talk on scalable machine learning acceleration at the 3D Workshop at IEEE/ACM DATE 2024
  • Feb 2024: I will be talking about challenges with artificial intelligence in IoT platforms at IEEE/ACM DATE 2024
  • Jan 2024: Mirza’s paper accepted in IEEE Photonics Technology Letters
  • Dec 2023: Stephen’s paper on GPU optimization of ray tracing accepted in IEEE TAP journal
  • Dec 2023: I have been invited to serve as an Associate Editor for IEEE Transactions on Computers
  • Dec 2023: I have been selected as a Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA)
  • Dec 2023: I have been selected as an IEEE Fellow (class of 2024)
  • Dec 2023: Danish’s paper accepted in IEEE Journal of Indoor and Seamless Positioning and Navigation
  • Nov 2023: Danish’s paper on adversarial security for indoor localization accepted at IEEE/ACM DATE 2024
  • Nov 2023: Febin and Amin’s paper on optical main memory accepted at IEEE/ACM DATE 2024
  • Oct 2023: Our IEEE IGSC 2023 paper on realizing sustainable data centers receives the Best Paper Award
  • Oct 2023: Keynote on “The past, present, and future of green and sustainable data centers” at IEEE IGSC 2023
  • Oct 2023: Invited panelist on the future of NSF computing systems research at the 2023 NSF Annual CSR PI Meeting
  • Oct 2023: Invited panelist on the session on post-Moore technologies at the 2023 NSF Annual CSR PI Meeting
  • Oct 2023: I am organizing a panel on sustainable computing at the 2023 NSF Annual CSR PI Meeting
  • Sep 2023: Our work on hybrid machine learning techniques for sustainable datacenters accepted at IEEE HiPC 2023
  • Sep 2023: Panelist at the IEEE/ACM NOCS symposium on interconnects in the post-Moore era
  • Aug 2023:Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems‘ published by Springer
  • Aug 2023: Ebad’s work on photonic networks for 2.5D machine learning acceleration accepted at NoCArc 2023
  • Aug 2023: Our joint work on sustainable datacenters with HPE and Ph.D student Sirui Qi accepted at IEEE IGSC 2023
  • Aug 2023: I gave a talk on low power machine learning at IEEE ISLPED 2023
  • Aug 2023: Kamil’s work on reinforcement learning for networks-on-chip to appear at IEEE/ACM NOCS 2023
  • Aug 2023: Amin’s paper on photonic neural networks accepted at the IEEE Photonics Conference (IPC) 2023
  • Jul 2023: Congratulations to Dr. Ninad Hogade for defending his Ph.D dissertation!
  • Jul 2023:Machine Learning for Indoor Localization and Navigation‘ published by Springer
  • Jul 2023: Salma and Febin’s paper on graph neural networks acceleration accepted at IEEE/ACM ESWEEK 2023
  • Jul 2023: Danish’s paper on federated learning for localization accepted at IEEE/ACM ESWEEK 2023
  • Jun 2023: Amin’s paper on numerical modeling for optical phase change memories accepted in NUSOD 2023
  • Jun 2023: Our work on machine learning acceleration with emerging technologies to appear in ISLPED 2023
  • May 2023: Danish’s paper on stacked autoencoders for localization accepted in IEEE Embedded Systems Letters 2023
  • May 2023: Article on ethics in computing accepted in IEEE Design & Test 2023
  • May 2023: Congrats to Salma for passing her M.S. thesis defense!
  • Apr 2023: My undergraduate senior design team wins best project (automotive security) at CSU Engineering Days 2023
  • Mar 2023: Salma and Febin’s paper on Transformer neural network accelerators accepted at ACM GLSVLSI 2023
  • Mar 2023: My paper on embedded ethics in computing education accepted at ACM GLSVLSI 2023
  • Mar 2023: I am leading a special session on optical computing that has been accepted at ACM GLSVLSI 2023
  • Mar 2023: Dylan’s paper on drone swarm management accepted in the Journal of Supercomputing, 2023
  • Feb 2023: Abhishek and Febin’s paper on fast object detectors for automotive systems accepted at IEEE/ACM DAC 2023
  • Feb 2023: Danish and Saideep’s paper on vision transformers for localization accepted at IEEE/ACM DAC 2023
  • Jan 2023: I will be giving an invited BMAC seminar on ‘Machine Learning for Indoor Navigation with IoT Devices’
  • Jan 2023: Sanmitra’s paper accepted in IEEE JSTQE 2023 journal.

Older News Items can be found here


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