Kallol Roy

About

Kallol Roy is currently working as an Assistant Professor at Institute of Computer Science, University of Tartu, Estonia. His research interests are Deep Learning, Computer Vision, AI accelerator, and electromagnetics.

He worked as a postdoctoral researcher at Packaging Research Center, Georgia Institute of Technology, Atlanta, USA and Statistical Artificial Intelligence Lab, Ulsan National Institute of Technology, South Korea and at Department of Mathematics, Indian Institute of Science Bangalore. He did his Bachelors in Electrical Engineering from Indian Institute of Technology (IIT K), Kanpur and Ph.D. in Electrical Communication Engineering from Indian Institute of Science (IISc) Bangalore.

He is a recipient of APS-IUSSTF Physics Student Visitation Award, 2012 Microsoft Travel Award, Sterlite Best Paper Award at Photonics 2010, IIT Guwahati, MHRD Scholarship, Government of India 2007, Jawaharlal Nehru Scholarship, Steel Authority of India Limited, 2000.

The current project running in the lab is: Machine learning to predict future crimes.

Areas of Interest

Deep Learning
Semi-Supervised Learning
Ethical AI
Computer Vision
Non-Convex Optimization

Institutions & Positions

Dec 2019 - Now Assistant Professor of Artificial Intelligence
University of Tartu, Estonia
Mar 2018 - Oct 2019 Postdoctoral Researcher
Georgia Institute of Technology, Atlanta, USA
Aug 2015 - Dec 2017 Postdoctoral Researcher
Ulsan National Institute of Science and Technology, South Korea
Apr 2014 - Jul 2015 Postdoctoral Researcher
Indian Institute of Science, Bangalore, India
Oct 2013 - Mar 2014 Visiting Researcher
Poonaprajna Institute of Scientific Research, Bangalore, India
Oct 2012 - Dec 2012 Visiting Researcher
Indiana University - Purdue University, Indianapolis, USA
Jan 2012 - Jul 2012 Visiting Researcher
Indian Association for Cultivation of Science (IACS), Kolkata, India
May 2006 - Jul 2006 Visiting Researcher
SN Bose National Center for Basic Science, Kolkata, India
Jan 2005 - Jul 2005 Postdoctoral Researcher
Indian Institute of Technology, Kanpur, India

Education

Jun 2014 Ph.D. Electrical Communication Engineering
Indian Institute of Science (IISc), Bangalore, India
May 2005 B.Tech. Electrical Engineering
Indian Institute of Technology (IIT K), Kanpur, India

Teaching

LTAT.02.001 Neural Networks
MTAT.03.317 Special Course in Machine Learning: Neural Network Training Dynamics
MTAT.03.238 Algorithmics

RESEARCH GROUP

Current

Modar Sulaiman
PhD Student
Thesis Title: Artificial intelligence bias to predict future criminals
University of Tartu, Estonia
Email
Anneli Kruve-Viil
Industrial Master's Student
Thesis Title: Machine Learning for Chemical Synthesis Design
University of Tartu, Estonia
Email

Alumni

Alka Patel
M.Tech. Graduate Student, 2017, (External Supervisor)
Thesis Title: Bayesian Machine Learning for Cyber Security
School of Electronics (Mobile Computing Technology)
Devi Ahilya Vishwavidyalaya, Indore, India
Email

PROJECTS

Artificial Intelligence to Predict Future Criminals
Deep Learning for Symbolic Mathematics
Machine Learning for Circuits Design
Machine Learning for Early Detection of Parkinsons Disease

Honours & Awards

2012 APS-IUSSTF Physics Student Visitation Award
2012 Microsoft Travel Award
2010 Sterlite Best Paper Award at Photonics 2010, IIT Guwahati
2007 MHRD Scholarship, Government of India
2000 Jawaharlal Nehru Scholarship, Steel Authority of India Limited

R&D related Managerial and Administrative Work

2018 − 2019 Program Coordinator, Center for Advanced Electronics through Machine Learning
CAEML, UIUC, School of Electrical and Computer Engineering
Georgia Institute of Technology, USA
2018 − 2019 Program Coordinator, Common Heterogeneous Integration and IP Reuse Strategies
CHIPS, DARPA
Georgia Institute of Technology, USA
2015 − 2017 Research Coordinator, Statistical Artificial Intelligence Lab (SAIL)
School of Electrical and Computer Engineering
Ulsan National Institute of Science and Technology (UNIST)
Ulsan, South Korea
2009 − 2012 Program Coordinator, Center for Advanced Electronics through Machine Learning
CAEML, UIUC, School of Electrical and Computer Engineering
Georgia Institute of Technology, USA

Publications

Google Scholar Profile

2021

Schierholz, Morten; Sanchez-Masis, Allan; Carmona-Cruz, Allan; Duan, Xiaomin; Roy, Kallol; Yang, Cheng; Rimolo-Donadio, Renato; Schuster, Christian (2021). SI/PI-Database of PCB-Based Interconnects for Machine Learning Applications [Masinõpperakenduste PCB-põhiste ühenduste SI / PI-andmebaasv]. IEEE Access, 9, 34423−34432. DOI: 10.1109/ACCESS.2021.3061788.
R Trinchero, M Ahadi Dolatsara, Kallol Roy, M Swaminathan, FG Canavero (2021). Inverse Modeling for the Design of High-Speed Digital Links via LS-SVM Regression,. 5th Workshop on Uncertainty Modelling for ElectroMagnetic Applications (UMEMA 2020). IEEE, 2 [forthcoming].

2020

Schierholz, Morten; Yang, Cheng; Roy, Kallol; Swaminathan, Madhavan; Schuster, Christian (2020). Comparison of Collaborative versus Extended Artificial Neural Networks for PDN Design. 2020 IEEE 24th Workshop on Signal and Power Integrity (SPI). IEEE, 1−4. DOI: 10.1109/SPI48784.2020.9218157.

2019

R. Trinchero, M. Ahadi Dolatsara, K. Roy, M. Swaminathan, F. G. Canavero (2019). Design of High- Speed Links via a Machine Learning Surrogate Model for the Inverse Problem. The IEEE Electrical Design of Advanced Packaging and Systems (EDAPS), December 16-18. 2019. IEEE, 3.
Kallol Roy, Majid Ahadi Dolatsara, Hakki M. Torun, Riccardo Trinchero, Madhavan Swaminathan (2019). Inverse Design of Transmission Lines with Deep Learning. IEEE Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS), October 6-9, 2019. 4. IEEE, 3.
Jinwoo Kim, Gauthaman Murali, Heechun Park, Eric Qin, Hyoukjun Kwon, Venkata Chaitanya Krishna Chekuri, Nihar Dasari, Arvind Singh, Minah Lee, Hakki Mert Torun, Kallol Roy, Madhavan Swaminathan, Saibal Mukhopadhyay, Tushar Krishna and Sung Kyu Lim (2019). Architecture, Chip, and Package Co-design Flow for 2.5D Integration of Reusable IP Chiplets. ACM Design Automation Conference, 2019. ACM, 6. DOI: 10.1145/3316781.3317775.

2018

Kallol Roy, Hakki Torun Mert, Madhavan Swaminathan (2018). Preliminary Application of Deep Learning to Design Space Exploration. IEEE Electrical Design of Advanced Packaging and Systems Symposium (EDAPS), 2018. IEEE, 3.

2017

Ramesh Patel, Kallol Roy, Jaesik Choi, Ki Jin Han (2017). Tractable Bayesian Learning for Automated Design of Electromagnetic Structures. 21st International Conference on the Computation of Electromagnetic Fields (Compumag2017). IEEE, 2.
Ramesh Patel, Kallol Roy, Jaesik Choi, Ki Jin Han (2017). Generative Design of Electromagnetic Structures through Bayesian Learning. vol. 54, 4.
Kallol Roy, Jaesik Choi (2017). Searching for Local Symmetry with Topological Features in Graphs. The First International Workshop on Machine Learning for Artificial Intelligence Platforms (MLAIP), Nov 2017. Seoul, South Korea: ACML, 1.

2016

Kallol Roy, Anh Tong, Jaesik Choi (2016). Searching for Topological Symmetry in Data Haystack. 11.

2015

Roy Kallol (2015). Quantum Algorithmic Engineering with Photonic Integrated Circuits. Germany: LAP LAMBERT Academic Publishing.

2012

Kallol Roy, Biswajit Das, R. Srikanth, Bimalendu Dev, T. Srinivas (2012). Dynamical Decoherence Control of Atomic Spin Ensemble. 23rd International Conference on Atomic Physics (ICAP 2012) Ecole Polytechnique Palaiseau, France. ICAP, 1.

2011

Kallol Roy, R.Srikanth, T.Srinivas (2011). Decoherence Suppression by Parallelism in a Trapped Ion System. Current Developments in Atomic, Molecular, Optical and Nano Physics (CDAMOP 2011), New Delhi, India. CDAMOP, 4.
Kallol Roy, R.Srikanth, T.Srinivas (2011). Decoherence Suppression By Parallelization Of Quantum Circuits. International Conference on Theoretical and Applied Physics (ICTAP 2011), IIT Kharagpur, India. ICTAP, 1.

2010

Kallol Roy, Akshata Shenoy H., R. Srikanth, E. S. Shivaleela, T. Srinivas (2010). Kolmogorov Complexity Approach to Decoy-Based Quantum Cryptography. Photonics 2010, IIT Guwahati, India. SPIE, 1.

COLLABORATORS

Ryan Walsh, Barrow Neurological Institute, USA
Christian Schuster, Technical University Hamburg, Germany
Pooyan Jamshidi, University of Southern California, USA
Purushothama Rao Tata, Duke University, USA
Babak Kateb, Society for Brain Mapping, USA