Manan Suri in MIT Technology Review’s 2018 “Innovators Under 35 List”

Manan Suri of the Electrical Engineering Department at IIT Delhi has been named to MIT Technology Review’s prestigious annual list of Innovators Under 35 under the Inventor category. For over a decade, the global media company has recognized a list of exceptionally talented technologists whose work has great potential to transform the world. He is the sole recipient in this year’s list who is working in India.

The announcement was made on June 27.
Gideon Lichfield, editor-in-chief of MIT Technology Review, said: “MIT Technology Review inherently focuses on technology first - the breakthroughs and their potential to disrupt our lives. Our annual Innovators Under 35 list is a chance for us to honor the outstanding people behind those technologies. We hope these profiles offer a glimpse into what the face of technology looks like today as well as in the future.”

Past notable winners featured on the MIT 35 Innovator List
Each year since 1999, the editors of MIT Technology Review have selected exceptionally talented young innovators whose has the greatest potential to transform the world. Previous winners include Larry Page and Sergey Brin, the cofounders of Google; Mark Zuckerberg, the cofounder of Facebook; John Rogers, materials scientist at the University of Illinois; Jonathan Ive, the chief designer of Apple; Helen Greiner, the cofounder of iRobot; and Max Levchin, the cofounder of PayPal.

In an interview with Dr Vanita Srivastava, Prof Suri talks about the research for which he has been included in the prestigious list.

You have built a computer chip that can mimic a human brain. How did you get the idea?


We have worked on semiconductor hardware building blocks (device & circuits) that may be helpful in realizing future brain-inspired computing chips. The initial motivation was to learn from nature and see if we can emulate the energy efficiency of computations happening inside mammalian brains using nanoelectronic devices. Even though we know or understand very little about the brain, still the few insights that it provides are quite valuable for designing energy efficient computing systems. Specifically this sub-field of brain inspired computing is defined as Neuromorphic Computing.


What is the fundamental technology behind it? What were the major challenges?


Fundamental aspects in the flow of our research direction are following; (a) Memory and Computing are not separate or isolated tasks. Memory can Compute and Compute can Store! (b) Emerging semiconductor non-volatile memory (NVM) devices offer great promise for exploring such memory centric computing fields. There are a lot of challenges that need to be solved at different levels. One major challenge (in my personal opinion) is lack of standardization in the field. Another challenge was lack of relevant benchmarks to position against.


How will the neuromorphic systems evolve in the next few years? What are its major applications?


In my opinion, Neuromorphic systems will become more and more hardware centric, more application specific and customized over the next few years. The applications are tremendous. Since these systems have the potential to efficiently handle massive amounts of data, different forms of data, and even data fusion. Healthcare, Defense & Security, IoT, Industry 4.0, Analytics, Robotics, Smart-Cities and many more sectors can benefit from advances in Neuromorphic engineering.


Web links for this year’s innovator list: