About My Work
Vinu’s current research focuses on optimizing deep neural network based systems for performance and scalability. More broadly, His research is at the intersection of systems, programming languages and machine learning, to create a more efficient, performant, secure, privacy-preserving and correct software. His PhD research has been mainly focused on deep neural network compression for resource efficient inference and robustness. He is generously supported by a NVIDIA PhD fellowship, mentored by Saurav Muralidharan and Michael Garland, He developed Condensa: A Programming System for Model Compression and Optimization. He has considerable experience constructing tools capable of leveraging the power of GPUs for machine learning computing. He is also interested in applying machine learning to challenging problems within programming systems.
Vinu is a PhD candidate in Computer Science at the School of Computing at the University of Utah, Salt Lake City, working on efficient deep learning computing, robustness and security of deep learning algorithms, advised by Prof. Ganesh Gopalakrishnan. He is one of the five recipients of the NVIDIA Graduate fellowship, the recipients were selected based on their academic achievements and area of research. Prior to graduate studies, Vinu worked at ARM Inc. During his tenure at ARM, he was a recipient of the Bravo award for developing the programmer’s model for verifying real-time (‘R’) profile architecture which provides high-performing processors for safety-critical environments.
Vinu received his bachelor’s degree at the Department of Electronics and Communication Engineering from CMR Institute of Technology, Bangalore, affiliated to the Visvesvaraya Technological University and his Undergraduate research was on efficient double-precision floating point arithmetic on FPGAs at National Aerospace Laboratory, India.
In his spare time, He has committed to mentor the next generation of CS/AI researchers, helping bright undergraduates in STEM (School of Computing) bootstrap their research careers, using his research in AI for social good, (Project Cinchona)
About the Advice I received from the Pioneers.
In General, Don't Fall for Trendy Research Topics!
In Particular, A person’s success in life is determined by having a high minimum, not a high maximum. If you can do something really well but there are other things at which you’re failing, the latter will hold you back. But if almost everything you do is up there, then you’ve got a good life. And so I try to learn how to get through things that others find unpleasant.
In AI, Don't Do Paper-Deadline based Research driven by Stress.
About MUSIC, our Mind and SCIENCE
"I was very interested in music, and after I graduated from high school I was more focused on a possible music career. I did my undergraduate work at Bowling Green, where I majored in music and computer science, but I spent most of my time on music." -- Prof. Alex Aiken, Stanford.
As a young engineer at ARM, I was new to Compilers, and I was inspired by Prof. Alex's course, it motivated me to decide to go to graduate school to study Computer Science. It was my good fortune and coincidence that during my PhD work, I got to interact, work alongside, and know more about Prof. Alex and his team in the NVIDIA research lab, in Santa Clara. I would highly recommend, you check out this interview (top), and The Aiken/Widom Family Year Off (link) both very inspiring.
“Life without playing music is inconceivable for me.” “I live my daydreams in music, I see my life in terms of music.” “If I were not a physicist I would probably be a musician.” “Life is like a Piano, what you get out of it depends on how you play it.” -- Albert Einstein
About My Appetite for Wonder
“My principal interest is in figuring out what’s going on inside our heads, and I’m convinced that one of the defining features of human intelligence is that we can understand stories, Believing as I do that stories are important, it was natural for me to try to build systems that understand stories, and that shed light on what the story-understanding process is all about.”
In these days of publish or perish, I think many of us tend to loose our appetite for wonder, especially as young researchers trying to publish in top tier conferences, fighting for our papers, doing rebuttals, sinking deep into our own research and community. Every time I notice a reduction in my appetite for wonder I come here and watch one of these (click them to find out) and this takes be back to the very reason I wanted to be a research scientist as a kid.
About The 3 Lectures series that had a huge impact on My studies.
About the Probability of being Brilliant Every Single Day :)
About Rebuttals, Fighting for Papers and Healthy Competition in Scientific Research
Take a theatrical journey with physicist Brian Greene to uncover how Albert Einstein developed his theory of relativity. In this vivid play, science is illuminated on stage and screen through innovative projections and an original score. Official Site: https://www.pbs.org/wnet/light-falls/ Actor Michael Winther is Albert Einstein in "Light Falls: Space, Time, and an Obsession of Einstein." Greene wears several hats: He is a theoretical physicist, television host and Columbia University professor. And alongside his wife, journalist Tracy Day, Greene co-founded the World Science Festival 11 years ago.
About Getting a Ph.D. and my Inspiration.
Prof. Matt Might
Matt Might on Patient-Driven Precision Medicine.
Dr. Matt Might is a Professor of Internal Medicine and Computer Science and Hugh Kaul Endowed Chair in Personalized Medicine, Director, Hugh Kaul Precision Medicine Institute
He was a strategist in the Executive Office of the President at the White House for both the Obama and Trump administrations (March 2016 - January 2018) and was on the faculty in Computer Science at the University of Utah (July 2008 - July 2017, and my good fortune :)
Watching this (above) keynote and interacting with Prof. Might, in my early stages of graduate school at the University of Utah, impacted and inspired me a lot.
In medicine, his primary research area is precision medicine -- the use of data (particularly genomic data) to personalized treatments and optimize healthcare outcomes. He is particularly interested in drug repurposing. In computer science, his primary research area is static analysis of higher-order programs, although He also does work in functional programming, relational programming, parsing and purely functional data structures. His broader interests include language design, compiler implementation, security, program optimization, parallelism and program verification. More at http://blog.might.net/
Imagine a circle that contains all of human knowledge. By the time you finish elementary school, you know a little: By the time you finish high school, you know a bit more.
With a bachelor's degree, you gain a specialty. A master's degree deepens that specialty: Reading research papers takes you to the edge of human knowledge: Once you're at the boundary, you focus:
You push at the boundary for a few years, Until one day, the boundary gives way:
And, that dent you've made is called a Ph.D.
Of course, the world looks different to you now:
So, don't forget the bigger picture: Keep pushing.
About How I learned to Learn :)
About being "in the Zone".
- Comfort Zone
- This is where you are feeling safe and in total control.
- Low risk and low reward, At Home :) on your couch.
- Fear Zone
- Your self-confidence is Low
- You are finding excuses, and
- are easily affected by others opinions.
- Learning Zone
- Congratulations, you have crossed the Fear Zone.
- You have acquired new skills, and now in your extended Comfort Zone.
- You are solving problems and facing challenges.
- Growth Zone
- Yo! You are "in Zone", now You Grow, Conquer objectives.
- You are talking to experts in this area about your challenges, setting new goals.
- and You are finding new purpose and living your dream (also read my Footnote)
About How I learned to Speak :)
About Harbouring Embarrassing Secrets in Scientific Endeavours and Making Mistakes
It's okay not to understand stuff, and land up making mistakes. Newton was harbouring an embarrassing secret, He had no idea how Gravity works, and for 250 years scientists were content to look the other way when confronted with this mystery.
An unknown clerk working in the Swiss Patent office would change all that.... It doesn't matter who you are, where you come from, do not get bogged down by reviewers comments, you deserve to be here and help make progress, We do not understand several important things. Keep pondering!