Dinh Phung - Main

National Competitive Research Grants

CI = Chief Investigator , AI = Associate Investigator

Lead CI, ARC Discovery Grant, 2023 - 2026 ($440k), Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. Seek to provide a unified understanding of geometries of learning for fundamental machine learning tasks such as continual learning and robust ML.
CI, ARC Linkage Infrastructure, Equipment and Facilities Grant (ARC LIEF), 2023 - 2024 ($440k), Towards a Green and Sustainable Energy-efficient Metaverse. Seek to establish a world-class facility for research in green and sustainable energy-efficient metaverse technologies.
CI, NHMRC Project Grant, 2019-2021 ($324k), Using social media data to identify markers of depression risk among individuals: A longitudinal cohort study. Aim at individuals' social media and their mental health by analysing the 'what', 'how' and 'emotion' of online discussions.
CI, ARC Industrial Transformation Research Hub, 2017 - 2022 ($3m), ARC Research Hub for Digital Enhanced Living. CI among a long list of other academics from Deakin, Flinders, UNSW, USYD, 12 Partner Organizations and 6 international Higher Education Providers in Denmark, Ireland, Germany, and NZ. (Note*: withdrawn in 2019 due to relocation to Monash).
Sole CI (from 2017), ARC Discovery Grant, 2016 - 2019 ($410k), Nonparametric Bayesian Machine Learning for Modern Data Analytics. Seek to advance nonparametric machine learning and multilevel clustering using Bayesian nonparametrics and optimal transport theory.
CI, ARC LIEF Grant, 2016 - 2017 ($250k), Computational infrastructure for Developing Deep Machine Learning Models. Facilitate five NVIDIA DevCube deep learning servers for research (CI with I. Reid, S. Venkatesh, P. Corke, M. Bennamoun, S. Gould, A. Hengel, S. Shen, A. Dick, G. Carneiro, N. Suenderhauf and A. Mian).
Lead CI ARC Discovery Grant, 2015 - 2018 ($384k), Stay Well: Analyzing Lifestyle Data from Smart Monitoring Devices (Lead CI, with S. Venkatesh and M. Kumar). Seek to enrich Baysian nonparametric modelling theory to scale and deal with heterogeneous data structured over time and space.
CI, ARC Linkage Grant, 2014 - 2017 ($375k), Assistive Technologies for Autism Support (CI with Svetha Venkatesh and PI Silvana Gaglia - Autism West)
CI, ARC LIEF Grant, 2013 ($210k), Computational infrastructure for machine learning in computer vision (CI with Prof Anton, Prof Ian, Prof Venkatesh, Prof Vo, Prof Suter, Dr Stephen, Dr Simon, Dr Anthony and Dr Chunhua)
CI, ARC Linkage Grant, 2012 - 2015 ($495k), Robust and scalable change detection in geo-spatial data. Applied machine learning and nonparametric models to detect changes from images collected by aerial airplanes (CI with Svetha Venkatesh and DS. Pham)
AI, ARC Discovery Grant, 2011 - 2014 ($290k), Computational Tools to Analyse and Exploit the Social Media Revolution (AI with Svetha Venkatesh and Brett Adams).
CI, ARC Linkage Grant, 2011 - 2014 ($760k), Assistive Technologies for Autism Support Harnessing Social Media. Aim to apply machine learning and computer vision techniques to develop IT-based framework for early intervention in autism (CI with Svetha Venkatesh, Bett Adams and A. Krishna)
AI, ARC Discovery Grant, 2009 - 2012 ($310k), Surviving the Data Deluge: Scalable Feature Extraction, Discrimination and Analysis for Computer Vision Tasks Using Compressed Sensed Data (AI with Svetha Venkatesh, DS. Pham and A. Jain)
CI, ARC Linkage Grant, 2008 - 2012 ($483k), Blindness Support: Prevention and Localisation Assistance Systems for the Blind. (CI with Svetha Venkatesh, Brett Adams, Geoffrey West and Tanya Packer)
CI, ARC Linkage Grant, 2008 - 2011 ($760k), Smart Technologies for People with Vision Impairment and Blindness. Aim to develop indoor navigation technology using freely available WiFi and help the visually impaired people to navigate.
CI, ARC Discovery Grant, 2007 - 2010 ($360k), Taming Media for the Masses: Computational Frameworks for Intelligent Digital Media Capture, Management, and Sharing (CI with Svetha Venkatesh and Brett Adams)

Industrially Competitive Research Grants

CI, Defense Advanced Research Projects Agency (DARPA), 2023 - 2026 ($6m), Dialogue Assistance for Negotiation in Cross-cultural Settings: A Neuro-Symbolic Computational Approach”.
CI, Australia's National Science Agency (CSIRO), 2022 - 2027 ($900k), Towards a Green and Sustainable Energy-efficient Metaverse. Funded under the "Next Generation Graduate Programs" to train 14 PhD in Quantum Technology, where I will be more involed in AI + Quantum.
CI, Defense Advanced Research Projects Agency (DARPA), 2019 - 2023 ($4.2m), Learning to Learn with Less Label. Funded under the “Learn with Less Label” program and the only university grant funded outside US.
CI, Asian Office of Aerospace Research and Development Grant (AOARD), 2019 - 2021 (104k), Optimal Transport Theory for Machine Learning with Limited and Less Labels. Seek to advance and apply the young mathematics of optimal transport for transfer learning, domain adaptation and generalisation.
Lead CI, Next Generation Technology Fund (DST Group), 2019 - 2022 ($372k), Towards Robust Learning Systems via Amortized Optimization and Domain Adaptation. Aim to develop techniques for reliable and trustworthy machine learning systems.
CI, Asian Office of Aerospace Research and Development Grant (AOARD), 2019 - 2021 (USD $80k), Deep Generative Models for Learning from Multiple High-Dimensional Data Sources. Seek to advance theoretical foundations of deep generative models to deal with multiple data sources.
Lead CI, MCWSRI Grant (DST Group), 2018-2019 ($60k), Generative Adversarial Networks for Behaviour Discovery. Apply GAN to generate novel tactical behaviour trajectories such as from air combat situation.
Lead CI, Next Generation Technology Fund (DST Group), 2017 - 2022 ($249k), Deep Learning for Cyber Security. This is a large joint project ($2m over 3.5 years) between Melbourne, Swinburne and Monash Uni. Aim to develop new deep embedding and time-series models for vulnerability discovery in binary code.
Sole CI, Asian Office of Aerospace Research and Development Grant (AOARD), 2016 - 2019 (USD $60k), Bayesian Learning with Unbounded Capacity from Heterogenous and Set-Valued Data. Seek to advance theoretical foundations of nonparametric machine learning using point processes/random finite set theory.
Lead CI, Innovation Small Grant (DST Group), 2016 - 2018 ($35k), Deep Anomaly Detection from Multiple Sensors and Application in Situation Awareness.
Sole CI, Adobe Collaboration Grant (Adobe), 2016 - 2017 (USD $21k), title. In the form of unrestricted gift.
Lead CI, Telstra Partnership Grant (Telstra), 2015 ($250k), Network Abnormality Detection. Aim to develop next-generation abnormality detection algorithms for network data. Also lay the foundation for the establishment of Telstra-Deakin Centre of Excellence in Big Data and Machine Learning in 2016 ($1.6m over 3 years).
CI, Helen M Foundation Grant, 2012 - 2015 ($130k), Therapy Outcomes by You (TOBY) Playpad randomised controlled trial to test the effectiveness of the application for early intervention in Autism. This grant is to support independent RCT and evaluation of the TOBY Playpad app; RCT in Victoria led by Prof. Dennis Moore (Monash), and RCT in Western Australia led by Prof. Andrew Whitehouse (Telethon Child Health Research Institute, Perth).
CI, Barwon Health Partnership Grant (Barwon Health), 2012 ($50k), Advanced Data Analytics for Care Management of Chronic Disease. Apply machine learning to analyse EMRs and manage health services.
AI, Industry Landgate Grant (Landgate, Western Australia), 2008 - 2009 ($160k), Investigation into Application of Clustering Techniques with Realestate Property Data. Aim to use data science techniques to cluster and understand real estate data.

Awards and Fellowships

National Competitive Grant (~ $18.5m) 2023, 2022, 2019, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2009, 2008, 2007
Australian Museum Eureka Prize for Excellence in Data Science, Finalist, 2020 (click here for more information)
Runner-up Best Student Machine Leaning Paper Award, Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint, The European Conference on Machine Learning and European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2018.
Best Application Paper Award, Energy-Based Localized Anomaly Detection in Video Surveillance, The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2017.
Honorable Mention Application Paper, Animal Recognition and Identification with Deep Convolutional Neural Networks for Automated Wildlife Monitoring, The International Conference on Data Science and Advanced Analytics (DSAA), 2017.
Best Runner-up Student Paper Award, Effect of Social Capital on Emotion, Language Style and Latent Topics in Online Depression Community, The IEEE International Conference on Computing and Communication Technologies (RIVF), 2016.
Finalist Best IBM Track 1 Student Paper Award, MCNC: Multi-channel Nonparametric Clustering from Heterogeneous Data, The International Conference on Pattern Recognition (ICPR), 2016.
Best Paper Award, Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning, The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2015 (with S. Gupta, S. Rana and S. Venkatesh)
Victorian International Education Awards, 2013 (member of TOBY India team) (see news).
Researcher of the Year Award (member of TOBY team), Smart Geelong Network, 2012 (see news)
Curtin Commercial Innovation Award (with S. Venkatesh and S. Greenhill), Curtin University, 2011 (watch this video for more information).
Early Career Research and Development Award, Curtin University, 2010.
Runner-up Best Paper Award, Ordinal boltzmann machines for collaborative filtering, The International Conference on Uncertainty in Artificial Intelligence (UAI), Canada, 2009. (with T. Tran and S. Venkatesh)
Curtin Research Targeted Fellowship, (4 years), Curtin University, 2006-2010.
International Research Fellowship, AI Center, SRI International, Menlo Park, 2006.


Dinh Phung, PhD Professor (Machine Learning) Monash University, Australia E:dinh.phung@monash.edu T:+61 3 9905 6955 Home News Research Projects/Grants Supervision Tutorials & Talks Data & Codes Research Lab Publications Preprints Selected Papers By Years By Topics All Papers Teaching Contact Disclaimer: This page, its content and style, are the responsibility of the author and do not necessarily represent the views, policies or opinions of Monash University.	National Competitive Research Grants CI = Chief Investigator , AI = Associate Investigator Lead CI, ARC Discovery Grant, 2023 - 2026 ($440k), Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. Seek to provide a unified understanding of geometries of learning for fundamental machine learning tasks such as continual learning and robust ML. CI, ARC Linkage Infrastructure, Equipment and Facilities Grant (ARC LIEF), 2023 - 2024 ($440k), Towards a Green and Sustainable Energy-efficient Metaverse. Seek to establish a world-class facility for research in green and sustainable energy-efficient metaverse technologies. CI, NHMRC Project Grant, 2019-2021 ($324k), Using social media data to identify markers of depression risk among individuals: A longitudinal cohort study. Aim at individuals' social media and their mental health by analysing the 'what', 'how' and 'emotion' of online discussions. CI, ARC Industrial Transformation Research Hub, 2017 - 2022 ($3m), ARC Research Hub for Digital Enhanced Living. CI among a long list of other academics from Deakin, Flinders, UNSW, USYD, 12 Partner Organizations and 6 international Higher Education Providers in Denmark, Ireland, Germany, and NZ. (Note: withdrawn in 2019 due to relocation to Monash). Sole CI* (from 2017), ARC Discovery Grant, 2016 - 2019 ($410k), Nonparametric Bayesian Machine Learning for Modern Data Analytics. Seek to advance nonparametric machine learning and multilevel clustering using Bayesian nonparametrics and optimal transport theory. CI, ARC LIEF Grant, 2016 - 2017 ($250k), Computational infrastructure for Developing Deep Machine Learning Models. Facilitate five NVIDIA DevCube deep learning servers for research (CI with I. Reid, S. Venkatesh, P. Corke, M. Bennamoun, S. Gould, A. Hengel, S. Shen, A. Dick, G. Carneiro, N. Suenderhauf and A. Mian). Lead CI ARC Discovery Grant, 2015 - 2018 ($384k), Stay Well: Analyzing Lifestyle Data from Smart Monitoring Devices (Lead CI, with S. Venkatesh and M. Kumar). Seek to enrich Baysian nonparametric modelling theory to scale and deal with heterogeneous data structured over time and space. CI, ARC Linkage Grant, 2014 - 2017 ($375k), Assistive Technologies for Autism Support (CI with Svetha Venkatesh and PI Silvana Gaglia - Autism West) CI, ARC LIEF Grant, 2013 ($210k), Computational infrastructure for machine learning in computer vision (CI with Prof Anton, Prof Ian, Prof Venkatesh, Prof Vo, Prof Suter, Dr Stephen, Dr Simon, Dr Anthony and Dr Chunhua) CI, ARC Linkage Grant, 2012 - 2015 ($495k), Robust and scalable change detection in geo-spatial data. Applied machine learning and nonparametric models to detect changes from images collected by aerial airplanes (CI with Svetha Venkatesh and DS. Pham) AI, ARC Discovery Grant, 2011 - 2014 ($290k), Computational Tools to Analyse and Exploit the Social Media Revolution (AI with Svetha Venkatesh and Brett Adams). CI, ARC Linkage Grant, 2011 - 2014 ($760k), Assistive Technologies for Autism Support Harnessing Social Media. Aim to apply machine learning and computer vision techniques to develop IT-based framework for early intervention in autism (CI with Svetha Venkatesh, Bett Adams and A. Krishna) AI, ARC Discovery Grant, 2009 - 2012 ($310k), Surviving the Data Deluge: Scalable Feature Extraction, Discrimination and Analysis for Computer Vision Tasks Using Compressed Sensed Data (AI with Svetha Venkatesh, DS. Pham and A. Jain) CI, ARC Linkage Grant, 2008 - 2012 ($483k), Blindness Support: Prevention and Localisation Assistance Systems for the Blind. (CI with Svetha Venkatesh, Brett Adams, Geoffrey West and Tanya Packer) CI, ARC Linkage Grant, 2008 - 2011 ($760k), Smart Technologies for People with Vision Impairment and Blindness. Aim to develop indoor navigation technology using freely available WiFi and help the visually impaired people to navigate. CI, ARC Discovery Grant, 2007 - 2010 ($360k), Taming Media for the Masses: Computational Frameworks for Intelligent Digital Media Capture, Management, and Sharing (CI with Svetha Venkatesh and Brett Adams) Industrially Competitive Research Grants CI, Defense Advanced Research Projects Agency (DARPA), 2023 - 2026 ($6m), Dialogue Assistance for Negotiation in Cross-cultural Settings: A Neuro-Symbolic Computational Approach”. CI, Australia's National Science Agency (CSIRO), 2022 - 2027 ($900k), Towards a Green and Sustainable Energy-efficient Metaverse. Funded under the "Next Generation Graduate Programs" to train 14 PhD in Quantum Technology, where I will be more involed in AI + Quantum. CI, Defense Advanced Research Projects Agency (DARPA), 2019 - 2023 ($4.2m), Learning to Learn with Less Label. Funded under the “Learn with Less Label” program and the only university grant funded outside US. CI, Asian Office of Aerospace Research and Development Grant (AOARD), 2019 - 2021 (104k), Optimal Transport Theory for Machine Learning with Limited and Less Labels. Seek to advance and apply the young mathematics of optimal transport for transfer learning, domain adaptation and generalisation. Lead CI, Next Generation Technology Fund (DST Group), 2019 - 2022 ($372k), Towards Robust Learning Systems via Amortized Optimization and Domain Adaptation. Aim to develop techniques for reliable and trustworthy machine learning systems. CI, Asian Office of Aerospace Research and Development Grant (AOARD), 2019 - 2021 (USD $80k), Deep Generative Models for Learning from Multiple High-Dimensional Data Sources. Seek to advance theoretical foundations of deep generative models to deal with multiple data sources. Lead CI, MCWSRI Grant (DST Group), 2018-2019 ($60k), Generative Adversarial Networks for Behaviour Discovery. Apply GAN to generate novel tactical behaviour trajectories such as from air combat situation. Lead CI, Next Generation Technology Fund (DST Group), 2017 - 2022 ($249k), Deep Learning for Cyber Security. This is a large joint project ($2m over 3.5 years) between Melbourne, Swinburne and Monash Uni. Aim to develop new deep embedding and time-series models for vulnerability discovery in binary code. Sole CI, Asian Office of Aerospace Research and Development Grant (AOARD), 2016 - 2019 (USD $60k), Bayesian Learning with Unbounded Capacity from Heterogenous and Set-Valued Data. Seek to advance theoretical foundations of nonparametric machine learning using point processes/random finite set theory. Lead CI, Innovation Small Grant (DST Group), 2016 - 2018 ($35k), Deep Anomaly Detection from Multiple Sensors and Application in Situation Awareness. Sole CI, Adobe Collaboration Grant (Adobe), 2016 - 2017 (USD $21k), title. In the form of unrestricted gift. Lead CI, Telstra Partnership Grant (Telstra), 2015 ($250k), Network Abnormality Detection. Aim to develop next-generation abnormality detection algorithms for network data. Also lay the foundation for the establishment of Telstra-Deakin Centre of Excellence in Big Data and Machine Learning in 2016 ($1.6m over 3 years). CI, Helen M Foundation Grant, 2012 - 2015 ($130k), Therapy Outcomes by You (TOBY) Playpad randomised controlled trial to test the effectiveness of the application for early intervention in Autism. This grant is to support independent RCT and evaluation of the TOBY Playpad app; RCT in Victoria led by Prof. Dennis Moore (Monash), and RCT in Western Australia led by Prof. Andrew Whitehouse (Telethon Child Health Research Institute, Perth). CI, Barwon Health Partnership Grant (Barwon Health), 2012 ($50k), Advanced Data Analytics for Care Management of Chronic Disease. Apply machine learning to analyse EMRs and manage health services. AI, Industry Landgate Grant (Landgate, Western Australia), 2008 - 2009 ($160k), Investigation into Application of Clustering Techniques with Realestate Property Data. Aim to use data science techniques to cluster and understand real estate data. Awards and Fellowships National Competitive Grant (~ $18.5m) 2023, 2022, 2019, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2009, 2008, 2007 Australian Museum Eureka Prize for Excellence in Data Science, Finalist, 2020 (click here for more information) Runner-up Best Student Machine Leaning Paper Award, Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint, The European Conference on Machine Learning and European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2018. Best Application Paper Award, Energy-Based Localized Anomaly Detection in Video Surveillance, The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2017. Honorable Mention Application Paper, Animal Recognition and Identification with Deep Convolutional Neural Networks for Automated Wildlife Monitoring, The International Conference on Data Science and Advanced Analytics (DSAA), 2017. Best Runner-up Student Paper Award, Effect of Social Capital on Emotion, Language Style and Latent Topics in Online Depression Community, The IEEE International Conference on Computing and Communication Technologies (RIVF), 2016. Finalist Best IBM Track 1 Student Paper Award, MCNC: Multi-channel Nonparametric Clustering from Heterogeneous Data, The International Conference on Pattern Recognition (ICPR), 2016. Best Paper Award, Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning, The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2015 (with S. Gupta, S. Rana and S. Venkatesh) Victorian International Education Awards, 2013 (member of TOBY India team) (see news). Researcher of the Year Award (member of TOBY team), Smart Geelong Network, 2012 (see news) Curtin Commercial Innovation Award (with S. Venkatesh and S. Greenhill), Curtin University, 2011 (watch this video for more information). Early Career Research and Development Award, Curtin University, 2010. Runner-up Best Paper Award, Ordinal boltzmann machines for collaborative filtering, The International Conference on Uncertainty in Artificial Intelligence (UAI), Canada, 2009. (with T. Tran and S. Venkatesh) Curtin Research Targeted Fellowship, (4 years), Curtin University, 2006-2010. International Research Fellowship, AI Center, SRI International, Menlo Park, 2006.