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A/Prof. Sunil Gupta

STAFF PROFILE

Position

Associate Professor

Faculty

Applied Artificial Intel Inst

Department

A2I2P

Campus

Geelong Waurn Ponds Campus

Qualifications

Doctor of Philosophy, Curtin University, 2012

Biography

Dr. Gupta graduated with a PhD in computer science from Curtin University in Jan 2012. He completed his PhD in a period of 2.5 years receiving the Chancellor's Commendation for excellence for his exceptional doctoral work in Machine Learning and AI. Prior to his PhD, he completed a Master of Engineering degree in Signal Processing from Indian Institute of Science, Bangalore. Since completing his PhD, Dr. Gupta has been at Deakin University, where he works at the Applied Artificial Intelligence Institute (A2I2). His current research interests lie in broad areas of machine learning and artificial intelligence.

Read more on Sunil's profile

Research interests

Sample-efficient Machine Learning, Deep Learning, Bayesian Optimisation, Active Learning, Reinforcement Learning, Healthcare Analytics, Computer Vision, AI Safety and Assurance 

Knowledge areas

Machine learning, Transfer learning, Bayesian optimisation, Data mining, Pattern recognition, Deep learning, Active learning, Reinforcement learning, Healthcare data analytics, Computer vision, AI safety and assurance

Awards

  • Winner of the “Best Paper Award” at Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018.
  • 2017: Vice Chancellor’s Award for Outstanding Contribution through Innovation that spans the Value Promise
  • 2017: Best Student Paper Award at Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2017
  • 2017: Professional Poster Award for our superalloy design work at 4th World Congress on Integrated Computational Materials Engineering, 2017
  • 2016: Best Paper RunnerUp and Best Poster awards at Asian Conference on Machine Learning (ACML) 2016
  • 2016: Finalists INTEL Track 5 Student Paper Award at International Conference of Pattern Recognition (ICPR), 2016
  • 2015: Best Paper Award, at PAKDD 2015
  • 2014: Recipient of Best Papers of SDM, at SIAM Data Mining Conference 2014
  • 2012: Recipient of Chancellor’s Commendation for excellence for my PhD thesis at Curtin University
  • 2010: Recipient of KDD Travel Awards, ACM SIGKDD Data Mining Conference 2010
  • 2009: Recipient of CIPRS Scholarship, Curtin University, Australia, 2009

Publications

No publications found

Funded Projects at Deakin

Australian Competitive Grants

ARC Research Hub for Digital Enhanced Living

Prof Kon Mouzakis, Prof Svetha Venkatesh, Prof Anthony Maeder, Prof Alison Hutchinson, Prof Michael Berk, Prof Ralph Maddison, Prof Abbas Kouzani, Prof Rajesh Vasa, Prof Helen Christensen, Prof Patricia Williams, Prof John Yearwood, Prof Susan Gordon, Prof David Powers, A/Prof Niranjan Bidargaddi, A/Prof Santu Rana, A/Prof Truyen Tran, A/Prof Sunil Gupta, Dr Wei Luo, A/Prof Mohamed Abdelrazek, Dr Felix Tan, Prof Henning Langberg, A/Prof Lars Kayser, Prof Finn Kensing, Prof Freimut Bodendorf, Prof James Warren, Dr Roopak Sinha, Prof A Smeaton, Mr Fonda Voukelatos, Mr Jeffrey Fiebig, Mr John Fouyaxis, Dr Kit Huckvale, Prof John Grundy, Nicole Cockayne, David Varley, Dr Leonard Hoon, Dr Tanya Petrovich, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Prof Deborah Parker, Dr Scott Barnett, Ms Sharon Grocott, Dr Tom McClean, Mr Steven Strange, Prof Jean-Guy Schneider, Prof Nilmini Wickramasinghe, A/Prof Carsten Rudolph, Mr Fernando Escorcia, Dr Jordan Vincent, Dr Gnana Bharathy

ARC Industrial Transformation Research Hubs

  • 2021: $245,896
  • 2020: $385,381
  • 2019: $399,716
  • 2018: $449,083
  • 2017: $601,698

A Generic Framework for Verifying Machine Learning Algorithms

Prof Svetha Venkatesh, A/Prof Sunil Gupta, A/Prof Santu Rana, A/Prof Truyen Tran

ARC - Discovery Projects

  • 2021: $78,263

Other Public Sector Funding

Al Algorithmic Assurance

Prof Svetha Venkatesh, A/Prof Sunil Gupta, A/Prof Santu Rana, A/Prof Truyen Tran, Dr Anh Cat Le Ngo, Dr Phuoc Nguyen, Mr Stephan Jacobs, Dr Dang Nguyen

  • 2021: $248,140
  • 2020: $208,820
  • 2019: $80,640

Defence Applied Al Experiential CoLab

Prof Svetha Venkatesh, A/Prof Sunil Gupta, A/Prof Santu Rana, A/Prof Truyen Tran

  • 2021: $100,000
  • 2020: $873,495

In relation to Assuring an off-the-shelf AI algorithm

A/Prof Sunil Gupta, A/Prof Truyen Tran, A/Prof Santu Rana, Prof Svetha Venkatesh, Dr Phuoc Nguyen, Mr Tiep-Trong Nguyen, Mr Stephan Jacobs

  • 2021: $83,034

Industry and Other Funding

ARC Research Hub for Digital Enhanced Living

Prof Kon Mouzakis, Prof Svetha Venkatesh, Prof Anthony Maeder, Prof Alison Hutchinson, Prof Michael Berk, Prof Ralph Maddison, Prof Abbas Kouzani, Prof Rajesh Vasa, Prof Helen Christensen, Prof Patricia Williams, Prof John Yearwood, Prof Susan Gordon, Prof David Powers, A/Prof Niranjan Bidargaddi, A/Prof Santu Rana, A/Prof Truyen Tran, A/Prof Sunil Gupta, Dr Wei Luo, A/Prof Mohamed Abdelrazek, Dr Felix Tan, Prof Henning Langberg, A/Prof Lars Kayser, Prof Finn Kensing, Prof Freimut Bodendorf, Prof James Warren, Dr Roopak Sinha, Prof A Smeaton, Mr Fonda Voukelatos, Mr Jeffrey Fiebig, Mr John Fouyaxis, Dr Kit Huckvale, Prof John Grundy, Nicole Cockayne, David Varley, Dr Leonard Hoon, Dr Tanya Petrovich, Matthew Macfarlane, Dr Anju Kissoon Curumsing, Prof Deborah Parker, Dr Scott Barnett, Ms Sharon Grocott, Dr Tom McClean, Mr Steven Strange, Prof Jean-Guy Schneider, Prof Nilmini Wickramasinghe, A/Prof Carsten Rudolph, Mr Fernando Escorcia, Dr Jordan Vincent, Dr Gnana Bharathy

  • 2021: $448,850
  • 2020: $553,025
  • 2019: $378,745

iCetana - Phase 1 Examine and compare state-of-art methods in background/foreground separation

Prof Svetha Venkatesh, A/Prof Santu Rana, A/Prof Sunil Gupta, Dr Budhaditya Saha

  • 2020: $50,000
  • 2018: $100,000
  • 2017: $200,000

Identification of Blood RNA Biomarkers to Measure Disease Progression in Parkinson's Disease.

A/Prof Sunil Gupta, Prof Svetha Venkatesh, Dr Thin Nguyen

  • 2021: $42,500
  • 2020: $42,500

Scale Faciliation CoLab

Dr Scott Barnett, Dr Yasmeen George, Mr Andrew Vouliotis, Dr Srikanth Thudumu, Dr Leonard Hoon, A/Prof Sunil Gupta, A/Prof Santu Rana, A/Prof Truyen Tran, Prof Rajesh Vasa, Prof Kon Mouzakis, Prof Svetha Venkatesh, Ms Rena Logothetis

  • 2021: $100,000

Other Funding Sources

The CRC-P for Advanced Hybrid Batteries

Prof Patrick Howlett, Prof Maria Forsyth, Dr Robert Kerr, Prof Svetha Venkatesh, A/Prof Sunil Gupta, A/Prof Santu Rana

  • 2021: $221,687
  • 2020: $170,546

Supervisions

Executive Supervisor
2020

Julian Maxwell Andrew Berk

Thesis entitled: A Distributional Approach towards Efficient and Versatile Bayesian Optimisation

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

Anil Ramachandran

Thesis entitled: Harnessing Auxiliary Knowledge Towards Efficient Bayesian Optimisation

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

2019

Thanh Dai Nguyen

Thesis entitled: Addressing Practical Challenges of Bayesian Optimization

Doctor of Philosophy (Information Technology), School of Information Technology

2016

Iman Kamkar

Thesis entitled: Building Stable Predictive Models for Healthcare Applications: A Data-Driven Approach

Doctor of Philosophy (Information Technology), School of Information Technology

Co-supervisor
2020

Majid Abdolshah

Thesis entitled: Multi-objective Bayesian Optimisation and Its Applications

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

Ang (Leon) Yang

Thesis entitled: Scalable Bayesian Optimization with Sparse Gaussian Process Models

Doctor of Philosophy (Information Technology), Applied Artificial Intel Ins

2019

Tinu Theckel Joy

Thesis entitled: Efficient Hyperparameter Tuning using Bayesian Optimization

Doctor of Philosophy (Information Technology), School of Information Technology

2018

Haripriya Harikumar

Thesis entitled: Machine learning to fight addiction using social media

Doctor of Philosophy (Information Technology), School of Information Technology

Associate Supervisor
2015

Cong Thuong Nguyen

Thesis entitled: Bayesian nonparametric learning of contexts and activities from pervasive signals

Doctor of Philosophy (Information Technology), School of Information Technology