Curriculum Vitae

Education

• Ph. D. in Electrical Engineering, Stanford University, September 2006.

• M. S. in Electrical Engineering, Stanford University, June 2003.

• B. Tech (Hons) in Instrumentation Engineering, IIT, Kharagpur, India, June 2000.

Work Experience

• Professor of Intelligent Computing Systems, August 2023 onwards.

• Reader in Engineering, King's College London, January 2020 - July 2023. 

• Associate Professor, Department of Electrical and Computer Engineering, New Jersey Institute of Technology, January 2016 - December 2019.

• Associate Professor, Department of Electrical Engineering, IIT Bombay, September 2014 - November 2015.

• Assistant Professor, Department of Electrical Engineering, IIT Bombay, November 2012 - August 2014.

• Adjunct Associate Professor, Department of Electrical Engineering, Columbia University, NY. Spring 2012.

• Research Staff Member at IBM T. J. Watson Research Center NY. Oct 2006 - Oct 2012.

• Research Consultant at Department of Computer Science, IIT Kharagpur. July 2000 - July 2001.

• Research Intern at Quantum Science Research, HP Laboratories. Summer 2004.

• Summer Student at Indian Institute of Science, Bangalore. Summer 1998.

Awards and Distinctions

• Senior Member, US National Academy of Inventors.

• Senior Member, IEEE.

• IBM Faculty Award, 2019.

• Ramanujan Fellowship, Department of Science and Technology, Govt. of India, 2013-2015.

• IBM Research Division Award for proof-of-concept demonstration of neuronal computation chips, 2012.

• Four High Value Patent Awards from IBM, 2012.

• Master Inventor at IBM Research, 2011.

• Co-author of one of 20 most downloaded articles of Journal of Vacuum Science & Technology since publication in 2010.

• IBM Technical Accomplishment Award for contributions to Enterprise Innovations forNon-volatile Memory, 2010.

• Commendation & Award from CEO, for “critical contribution to IBM’s success”, 2009.

• IBM Technical Accomplishment Award for contributions to SyNAPSE project, 2009.

• 13 IBM Invention Achievement Plateau awards. A plateau recognizes 4 patent filings.

• Institute Silver Medal for highest GPA in Instrumentation Engineering at IIT Kharagpur, 2000.

• Best Project Award in Instrumentation Engineering at IIT Kharagpur, 2000.

• J. C. Ghosh Memorial Award for academic excellence at IIT Kharagpur, 1999.

• Certificate of Merit in Physics (top 0.1% in the National College Exam), 1996.

Tutorials

1. B. Rajendran,  O. Simeone, A. Pantazi and Y. Sandamirskaya, Spiking Neural Networks - Algorithms, Circuits, and Systems based on CMOS and emerging devices, Tutorial at IEEE International Symposium on Circuits and Systems, 2021.

2. K. Parhi, B. Yuan, N. Shanbhag, A. Sebastian, and B. Rajendran,  Energy-Efficient AI: System Architectures and Computational Models based on CMOS and Beyond-CMOS Devices, IEEE International Symposium on Circuits and Systems, 2019. 

3. Jae-sun Seo and B. Rajendran,  Towards the Ultimate Brain Computer – Hardware  Designs of Artificial \& Spiking Neural Networks, 30th  International Joint Conference on Neural Networks, 2017.

4. B. Rajendran, U. Ganguly and M. Suri, Neuromorphic Computing - Algorithms, Devices and Systems, 28th International Conference on VLSI Design, 2015.

5. B. Rajendran,  Machines that mimic the brain - Ideas and Implementations, IEEE INDICON, 2013.

6.  M. Qureshi, S. Gurumurthi &  B. Rajendran,  System Design with Phase Change Memory -- Fundamentals, Opportunities, and Challenges,  Second Annual Non-volatile Memories Workshop, 2011.

7. M. Qureshi, S. Gurumurthi & B. Rajendran,   Phase Change Memory - From Devices to Systems, The 43rd International Symposium on Microarchitecture 2010.

8. M. Qureshi, S. Gurumurthi & B. Rajendran,  Phase Change Memory -- A Systems Perspective,  Tutorial at High Performance Computer Architecture 2010.

Invited Talks

1. Bayesian AI accelerators based on nanoscale memristive devices, International Conference on Physical Computing, 2023.

2. Efficient and Reliable Neuromorphic AI, Aalborg University, 2023.

3. Next-generation Sustainable AI  with Nanoscale Hardware, Queen Mary University London, 2023.

4. Building efficient AI based on brain-inspired algorithms and hardware, Imperial College London, 2022.

5. Energy-efficient AI with nanoscale hardware systems, Newcastle University, 2022.

6. Building efficient AI hardware with imperfect nanoscale devices, Technische Universität Ilmenau, 2022.

7. A Desiderata for Brain-Inspired Computing Systems, KCL Workshop on "Building a Community in AI Hardware: Lights, Neuromorphic and Beyond", 2022.

8. In-memory computing with beyond-CMOS devices for efficient AI hardware, University of Southampton, MINDS CDT seminar, 2022.

9. Building efficient AI hardware systems with memristive devices, Memristor 2021.

10. Neuromorphic Computing with Phase Change Devices, NeurONN Workshop on Neuromorphic Computing, 2021.

11. Designing efficient AI systems - a brain-inspired perspective, ARM Research, 2020.

12. Re-imagining System Design for Brain-inspired Computing, IEEE International System-on-Chip Conference, 2020.

13. Event-driven Learning with Non-von Neumann Memristive Architectures,  University College London, 2020.

14. Designing Learning Systems based on Nanoscale Devices, IEEE Electron Device Society Mini-Colloquium on Nanotechnology and Nanoelectronics, 2019.

15. Learning with Spiking Neural Networks, Asilomar Conference on Signals, Systems, and Computers, 2019.

16. Towards Computing at the Efficiency of the Brain, IEEE Non-Volatile Memory Technology Symposium, 2019. 

17. Building Next-generation AI systems: Co-optimization of Algorithms, Architectures, and   Nanoscale Memristive Devices, IEEE International Memory Workshop,  2019. 

18. Building Brain-like Computers - Reimagining Algorithms, Devices, and System Architecture,  Columbia University EE Department Seminar,  2019. 

19. Computing at the edge - What can we learn from the brain?, Xio Research,  2019. 

20. Bio-inspired Algorithms and  Nanoscale In-memory Computing Architectures for Information Processing, Workshop on Nanotechnology-Enabled Beyond-von-Neumann Computing, Army Research Laboratory, 2018.

21. Designing Systems Mimicking the Brain - Progress and Prospects, University of Southern California, 2018. 

22. Computing with Phase Change Memory, Memory Technology Technical Forum, 2018.  

23. Re-imagining System Design for Ubiquitous AI, Helmholtz Zentrum Berlin, 2018.

24. Learning in Spiking Neural Networks using Phase Change Memory Synapses, 14th International Conference on Modern Materials and Technologies, 2018.

25. Engineering Nanoscale Devices for Brain-inspired Computing, 20th Workshop on Dielectrics in Microelectronics, 2018.

26. Event-driven learning in Spiking Neural Networks, `From Neuroscience to Machine Learning' Workshop,  European Institute for Theoretical Neuroscience, 2018.

27.  Re-imagining System Design for Brain-inspired Computing, University College London, 2018.

28.  Hardware/Software Co-optimization for  Brain-inspired Learning Systems, King's College London, 2018.

29.  Supervised Learning in Spiking Neural Networks, Hardware and Algorithms for Learning On-a-chip Workshop, IEEE International Conference On Computer Aided Design 2017.

30.  Brain-inspired Learning Systems for Ubiquitous AI, UCLA (University of California Los Angeles) ECE Department Seminar, 2017.

31.  Towards Ubiquitous AI – Challenges & Recent Progress, Hosted by IEEE Princeton/Central New Jersey Section of Solid-State Circuits Society, 2017.

32.  Mimicking the Brain – Algorithms, Devices & Systems, Columbia University EE Department Seminar, 2017.

33.  Spiking Neural Networks - Algorithms, Hardware Implementations, and Applications, IEEE 60th International Midwest Symposium on Circuits and Systems, 2017.

34.  Synaptic Plasticity in a Memristive Device below 500mV, The 231st Meeting of the Electrochemical Society, 2017.

35.  Towards low-power synaptronic computing using RRAMs, The IEEE Non-Volatile Memory Technology Symposium, 2016.

36.  Intelligent Computing – Algorithms, Devices & Systems, New York University, 2016.

37.  Bio-inspired Algorithms for Learning & Adaptation, NJIT Math-Bio Seminar, 2016.

38.  Algorithms and devices for Brain-inspired learning, IBM Zurich Research  Laboratories, 2016.

39.  Brain-inspired learning - Algorithms and Devices, University of Notre Dame, 2016.

40.  Intelligent IoT – algorithmic & architectural lessons from the brain, The 48th Annual IEEE/ACM International Symposium on Microarchitecture, 2015.

41.  Engineering a world of trillion connected devices – what can we learn from the brain ?, Intel India Academic Forum 2015.

42.  New algorithms and devices for neuromorphic computing, IEEE International Conference on Emerging Electronics, 2014.

43.  Building computational systems inspired by the brain – recent progress and path forward, Universite de Cergy-Pontoise, Paris, France, 2014.

44.  Building Intelligent Computational Systems – What can we learn from nature?, Colloquium at the ECE department, National University of Singapore, 2014.

45.  Bio-inspired computational systems – Prospects and Challenges, Invited talk at 27th International Conference on VLSI Design, 2014.

46.  Learning from biology – a path to novel computational systems ?, Invited talk at Samsung India Research Network Meeting, 2013.

47.  Can silicon machines match the efficiency of the human brain?, Invited talk at 26th International Conference on VLSI Design, 2013.

48.  Phase Change Memory Devices for Cognitive Computing, Talk hosted by IEEE Electron Devices Society, IEEE Circuits and Systems Society and New Jersey Institute of Technology, 2012.

49.  Phase Change Memory Devices for Cognitive Computing, Smart Materials and Systems Seminar Series, Mechanical and Aerospace Engineering Department, Polytechnic Institute of New York University, 2011.

50.  Phase Change Memory – Panacea or Pipedream?, ECE Colloquium, Electrical & Computer Engineering Department, Carnegie Mellon University, 2010.

51.  Emerging Memory Technologies – Just hype or is there real hope?, Plenary talk at International Workshop on Physics of Semiconductor Devices 2009.

52.  Phase Change Memory – Just hype or is there real hope?, ECE Colloquium, Electrical & Computer Engineering Department, University of Connecticut, 2008.

53.  Phase Change Memory – Opportunities and Challenges, International Workshop on Physics of Semiconductor Devices 2007.

54.  Sequential 3D IC Fabrication – Challenges and Prospects, VLSI Multi-level Interconnect Conference 2006.

Service

• Technical program committee member of IFIP/IEEE Conference on Very Large-Scale Integration,   VLSI-SoC 2023.

• Chair of the sub-committee on Neuromorphic Device Technology, Circuits and Systems, 6th   IEEE International Conference on Emerging Electronics, 2022.

• Co-chair of the sub-committee on Artificial Intelligence and Quantum Technologies, IEEE International Conference on Electronics, Circuits and Systems (ICECS) 2022.

• Technical program committee member of Non-Volatile Memories Workshop 2021.

• Member of the subcommittee on "Disruptive Technologies - IoT, AI/ML, Neuromorphic & Quantum Computing''  of the 5th IEEE Electron Devices Technology and Manufacturing (EDTM) Conference, 2021.

• Technical program committee member of  IEEE International Conference On Computer Aided Design 2019.

• Technical program committee member of 77th Device Research Conference, 2019.

• Lead organizer of the 3-day Materials, Devices and Systems for Machine Learning and Neuromorphic Computing Symposium at the MRS Spring Meeting, 2018.

• Organized a short course (with Davood Shahrjerdi, NYU) on the topic Memory Devices for the Next 10 Years at 75th Device Research Conference, 2017

• Moderated the rump session (with Rashmi Jha, Univ of Cincinnati) on the topic Neuromorphic computing – Do devices matter? at 75th Device Research Conference, 2017

• Technical Program Committee (TPC) of 75th Device Research Conference, 2017.

• TPC of 8th Annual Non-Volatile Memories Workshop, 2017

• External Review Committee of 23rd International Symposium on High Performance Computer Architecture (HPCA), 2017.

• Chair of Session on Neuromorphic Computing at IEEE Non-Volatile Memory Technology Symposium, 2016.

• Publicity Chair, IEEE/ACM International Symposium on Microarchitecture (MICRO) 2015.

• Technical Program Committee Member, 28th Conference on VLSI Design, 2015.

• Technical Program Committee Member, National Conf. on Communication, 2015.

• Technical Program Committee Member, IEEE International Conference on Technology for Education, T4E 2014.

• Session Chair on Informatics theme at the inauguration of Center for Urban Science and Engineering (CUSE), IIT Bombay, 2013.

• Technical Program Committee Member, VLSI Design 2014.

• Program Committee Member, Non-Volatile Memories Workshop, 2014.

• Member of Technical Advisory Board, MonolithIC 3D Inc.

• Program Committee Member, 3rd Annual Non-Volatile Memories Workshop, 2012.

• Program Committee Member, 2nd Annual Non-Volatile Memories Workshop, 2011.

• Member of ITRS (International Technology Roadmap for Semiconductors) group on Emerging Research Devices, 2010. 

• Program Committee Member, VLSI Multi Level Interconnect Conference, 2006.

• Member, Panel Discussion on 3D ICs, VLSI Multi Level Interconnect Conference, 2006.

• Reviewer for IEEE Transactions on Electron Devices, IEEE Electron Device Letters, IEEE Transactions on Neural Networks and Learning Systems, ISCA, HPCA, Micro.