- Invited talk, "Beyond Efficient Accelerators: System Design Challenges for Sustainable AI", Energy-Efficient AI Architectures Workshop, 69th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), Cincinnati, OH, August 2026.
- Invited Luminary talk, "Challenges of Computing System Design in the Generative AI Era", 37th International Conference on VLSI Design, Kolkata, India, January 2024.
- Keynote presentation, "Evolution of Computing Systems and Sustainability in the Generative AI era", Annual TxACE Symposium, University of Texas, Dallas, TX, October 2023.
- Invited Panel, "AI vs. AC: Will Artificial Intelligence's Expanding Energy Appetite Leave Enough to Keep Our Air Conditioners Running?", Annual TxACE Symposium, University of Texas, Dallas, TX, October 2023.
- Invited talk, "AI Hardware Innovations at IBM Research", SRC AI Hardware Research Program Annual review, September 2021.
Krishnan Kailas
Krishnan Kailas served as a Senior Research Scientist at IBM Thomas J. Watson Research Center,Yorktown Heights, New York, until recently. Over two decades at IBM Research, he led and contributed to several exploratory systems research projects to develop and bring emerging technologies into IBM products. Most recently, he worked on code translation and summarization systems using large-language models in the AI for Code research group. Prior to this, he led an exploratory project to define the architecture and compiler for analog AI accelerators for training deep neural networks at the IBM Research AI Hardware Center.
Dr. Kailas has contributed to the design and development of a wide spectrum of systems and research topics such as embedded real-time systems, hard real-time operating systems, VLSI design, temporal accuracy of microprocessors, high-speed network traffic shapers, VLIW architectures, binary translation systems, static (compiler) and dynamic (instruction scheduling unit) scheduling and resource allocation algorithms, computer architecture and microarchitecture, compilers and code generators, statically scheduled low-power DSP architecture exploiting fully-exposed pipelines, formal verification, performance modelling and analysis, full-system emulators and tools for IBM z mainframe processor design, computer architectures exploiting 3D integration, qubit control for quantum computing, and AI compute accelerators exploiting approximate digital and analog in-memory computing techniques. Many of his research contributions have been incorporated into IBM microprocessors and systems. Dr. Kailas is a recipient of several IBM Research division technical achievement awards, and the 2021 Mahboob Khan Outstanding Liaison award from the Semiconductor Research Corporation.
He received a Ph.D. from the University of Maryland, College Park, where his dissertation research focused on the microarchitecture and code generation issues of clustered ILP processors. Prior to graduate studies at Maryland, he worked at Bhabha Atomic Research Center designing real-time operating systems, application and system software, and hardware for embedded systems for real-time process control and instrumentation.
Dr. Kailas served as the IBM Research division's Campus Relationship Manager for University of Maryland College Park during 2005-2019. He has been a member of the technical advisory board (TAB) of GRC programs at Semiconductor Research Corporation (SRC) since 2016. He served as the vice-chair of the TAB for the SRC System-level Design (SLD) program (2018-2019), and the inaugural chair of the TAB for the AI Hardware research (AIHW) program (2019-2021). In addition, he has been an organizer for the IBM IEEE AI Compute Symposium.
Selected publications
Selected patents
Here're some of the research projects he has contributed to:
Contact: krish at e-kailas dot net | LinkedIn: @krishkailas