Sparsh Mittal
Assistant
Professor (and IEEE senior member)
Department
of Electronics and Communications Engineering
Joint
faculty at Mehta Family School of Data Science and Artificial Intelligence
Indian
Institute of Technology, Roorkee, India.
Email: sparsh0mittal at gmail dot com;
sparshfec at iitr.ac.in (which is an alias of sparsh.mittal at ece.iitr.ac.in and sparsh.mittal at mfs.iitr.ac.in)
Profiles at Google
Scholar, Academia.edu,
ResearchGate, LinkedIn, PublicationsList
and ACM-Library
. ORCID: 0000-0002-2908-993X
Webpage of CANDLE
research lab [Refer this for most up
to date information about our research]
My talks on improving
clarity in paper-writing, making
technical figures, writing survey
papers and making presentations.
Research Interests
Processor architectures for machine learning,
neural network accelerators, autonomous driving vehicles, computer architecture
(CPUs and GPUs), VLSI, high-performance computing, approximate computing.
Awards and Honors
1.
In the Stanford's list of world's top researchers 2021, in the
field of Computer Hardware & Architecture, I am ranked as number 71 (for whole
career) and as number 3 (for year 2020). In 2020 list, I was ranked 107 (for
whole career) and as number 3 (for year 2019 alone).
2.
My research on mobile-phone usage detection was praised by
Education Minister of India (1, 2, 3).
It was covered by TOI,
HinduBusinessLine, TelanganaToday, Andhrajyothi
and many other media platforms.
3.
My research has been covered by several technical news websites,
e.g. Phys.org,
TheMemoryGuy, InsideHPC (1,
2,
3, 4,
5,
6,
7,
8), Primeur
Magazine, StorageSearch 1, StorageSearch
2, StorageSearch
3, Data-Compression.info,
TechEnablement, ScientificComputing, SemiEngineering (semiconductor engineering), ReRAM
forum and HPCWire (1,
2,
3,
4,
5).
4.
My opinion-articles in popular media: BusinessWorldEducation, Eduvoice
5.
My application for recruiting a student on Intel PhD fellowship
2018 was approved.
6.
Received Distinguished
Contribution rating at ORNL
based on 2013-2014 performance appraisal. This rating recognizes the top 10
percent of staff.
7.
Received Outstanding
Contribution rating at ORNL
based on 2014-2015 performance appraisal. Also received a performance award.
8.
Gave an invited presentation at Memory
for HPC Systems session at ISC,
Germany 2016. ISC is a top conference with 3000 attendees and bi-annual Top500
list is announced here.
9.
Best student paper candidate in SC 2014
10.
ECpE fellowship from
Electrical and Computer Engineering Department, Iowa State University, USA of
$2500 in 2008.
11.
Peer Research Award from Iowa State University, USA of $200 in
2013.
12.
Topper in Electronics batch of year 2008 in ECE department at IIT Roorkee
and received Institute Silver Medal for this.
13.
Institute Silver Medal for Best B.Tech project award in Electronics and Computer
Engineering (ECE) Department at IIT Roorkee.
14.
Sumer Chand Jain Scholarship of INR 10,000 from IIT Roorkee.
15.
Best Student Award from High School (named MHS, Jaipur, Rajasthan,
India) in 2004. Topper throughout school
Funded Proposals
2017/04:
SERB early career research (ECR) award, title: Secure and Reliable Non-volatile Memories for Ultra-low
Power Applications
2018/08:
SRC USA, title: Designing efficient hardware-accelerators for Autonomous
Driving Vehicles
Open-source software released
1.
DESTINY: DESTINY
is an acronym for 3D design-space exploration tool
for SRAM, eDRAM and non-volatile memory.
DESTINY can model:
* (2D/3D) SRAM and eDRAM
* (2D/3D, SLC/MLC) STT-RAM, ReRAM and PCM
* (2D, SLC/MLC) SOT-RAM, Flash, DWM
In its purpose, DESTINY is similar to CACTI, CACTI-3DD or
NVSim. Here are manual
and the JLPEA 2017 journal
paper. Source-code is available here. See its news
coverage on ReRAM
forum.
The proverb goes, write
your own destiny. Hence, we have
written our own [tool named] DESTINY. J
2.
Code and trained model of our WACV-2020
paper ULSAM: Ultra-Lightweight Subspace
Attention Module for Compact Convolutional Neural Networks
3.
Code and trained model of
our VLSID-2020 paper E2GC: Energy-efficient
Group Convolution in Deep Neural Networks
4.
Dataset and
trained models of our GOODTECHS-2020 paper Detecting Usage of Mobile Phones using Deep Learning Technique
5.
Both serial and parallel versions
of code of red-black SOR (successive over-relaxation) method in three
state-of-the-art languages, viz. Chapel (from Cray Inc.), D (also called dlang, from Digital Mars) and Go (also called golang, from Google) can be downloaded for academic use
from this
link. They were used in this
paper. Chapel version of the code has been incorporated in Chapel performance
test suite/examples.
Professional Background
Assistant
Professor at IIT Hyderabad (2016-2019)
Postdoctoral
research associate at Oak Ridge National Lab, USA (2013-2016)
PhD
from Iowa State University (ISU), Ames, Iowa, USA (2008-2013).
BTech from
Indian Institute of Technology (IIT) Roorkee, Uttarakhand,
India (2004-2008).
Office Address
S-303, ECE Building, IIT Roorkee, Roorkee, Uttarakhand 247667