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Dr Vu Nguyen

Work Experience

Education

Awards

  • 2nd Winner, AutoML competition, Jul 2022
  • Best Paper Award, PLOS Computational Biology, Jul 2022
  • Selected as a Postdoc-NeT-AI Fellow, DAAD, Germany, Oct 2020
  • Young Investigator Training Program Grant, Italy, June 2019
  • Travel Grant EEML on Deep Learning and Reinforcement Learning, Romania, July 2019
  • Vice Chancellor Award for Outstanding Contribution, Deakin University 2017
  • Selected as Best Papers for KAIS - ICDM 2017
  • Best Poster Award, Bayesian Optimization of Superalloy Design. 4th World Congress on Integrated Computational Materials Engineering 2017
  • Best Paper Runner up Award and Best Poster Award - ACML 2016, Bayesian Nonparametric Multi-label Classification.
  • Heidelberg Laurate Forum 2015, Top 200 young scientist around the world to interact with the Laurates in Germany
  • First Prize in Student Research Competition 2011, University of Science, Vietnam National University HCM
  • Travel Grant - Machine Learning Summer School, Singapore, 2011.
  • Lawrence Sting Award and Scholarship Awarded for Vietnamese Outstanding Students, 2010

Invited Talks and Tutorials

  • Mar 22. Applied Machine Learning Conference Bayesian Optimization with Categorical and Continuous Variables.
  • Nov 21. ACEMS. Invited speaker and panel discussion Tales of the two worlds: Navigating between industry and academia.
  • Apr 21. Amazon - Indian Machine Learning. Advanced Bayes Opt for Machine Learning Hyperparameters Tuning.
  • Oct 20. ACML 2020 - Tutorial Recent advances in Bayesian optimization.
  • Jun 20. University of Liverpool, UK. Recent advances in Bayesian optimization.
  • Jun 20. Oxford-Man Institute 11st Machine Learning Workshop. Controlling quantum device measurement using DRL.
  • Jun 20. University of Twente, The Netheland. Recent advances in Bayesian optimization.
  • Jun 20. University of Glasgow, UK. Recent advances in Bayesian optimization.
  • Dec 19. VinAI Research, VN. Knowing the what but not the where in Bayesian optimization.
  • Nov 19. University of Oxford, Dept of Materials. DRL for controlling quantum device .
  • Aug 19. University of Melbourne, Aus. Machine learning for decision making under uncertainty.
  • Jun 19. University of Roma, Italy. Bayesian optimization for accelerating hyperparameter tuning.
  • May 19. University of Southampton, UK. Machine learning for decision making under uncertainty.
  • Apr 19. Oxford-Man Institute on Quantitative Finance. Deep reinforcement learning for marketing .
  • Oct 18. Credit AI, Australia. Bayesian optimization for experimental design .
  • Dec 17. Deakin-Defense Science Technology Workshop. Bayesian optimization for hyper-parameter tuning.

Grant and Funding

  • Google Cloud Platform Education Grant, Aug 2020-2021. $5000 USD
  • Young Investigator Training Program Grant, Italy, June 2019. €3000
  • NVIDIA, GPU Grant. 2019
  • Networked Quantum Information Technologies Hub (NQIT). Machine Learning for Quantum Technologies. 2018-2019. £105,978
    Named Researcher.
  • Telstra Grant - COE in Big Data and Machine Learning. 2016-2019. $1,600,000 AUD
    With PRADA team at Deakin University.

Teaching

  • Teaching Assistant. Course: Introduction to Programming. Undergraduate Course, Fall 2011. University of Science - VNU HCMC
  • Teaching Assistant. Course: Advanced Machine Learning. Master Course, Trinity Term 2019. University of Oxford
  • Guest Lecturer. Course: Introduction to Machine Learning. Undergraduate Course, Fall 2011. University of Science - VNU HCMC
  • Guest Lecturer. Course: Advanced Data Science. Undergraduate Course, Spring 2018. Deakin University
  • Lecturer. Course: Data Estimation and Inference. CDT AIMS. Postgraduate Course, Michaelmas Term 2019. University of Oxford
  • Senior Demonstrator. Course: Practical Gaussian Process and Bayesian Optimisation. Postgraduate Course, Hilary Term 2020. University of Oxford

Mentorship

  • Julian Berk. PhD at Deakin University. Associate Supervisor. 2017-2019.
    Topic: Methods for Improving Bayesian Optimization through Thompson Sampling.
  • Samuel Kessler. DPhil at University of Oxford. Informal Supervisor. 2019-2020
    Topic: Indian Buffet Neural Networks for Continual Learning.
  • Labiba Noorain. Master Thesis. University of College London. Co-supervisor. Jun 2020 - Oct 2020
    Topic: A machine learning approach for polymer nanoparticles and metal nanoparticles designed in antiviral drug delivery.
  • Xinglong Wang. Undergraduate - EUROP summer placement at University of Oxford. Main supervisor. Jun 2020 - Dec 2020
    Topic: Interpretable Gaussian Process.
  • Anshuman Shukla. ML Apprentice Program at Amazon. Main supervisor. Apr 2021 - Oct 2021
  • Xinqi Zhu . Applied Scientist Intern at Amazon. Main supervisor. Apr 2022 - Feb 2023
  • Alexander Soen. Applied Scientist Intern at Amazon. Main supervisor. Mar 2023 - Oct 2023
  • Yixin Liu. Applied Scientist Intern at Amazon. Main supervisor. Jul 2023 - Jan 2024

Publications

Professional Service

Technical Program Committee
  • NeurIPS '17,'19,'20
  • ICML '19,'20,'21
  • ICLR '19,'20,'21,'22
  • AAAI '20,'21,'22
  • AISTATS '20,'21,'22
  • IJCAI '18,'19,'20
  • ACML '18,'19,'20
  • ICDM '18,'19,'20
Senior Technical Program Committees / Area Chairs
  • AAAI '22
  • AISTATS '23, '24
Organizing Committees
  • Journal Track Co-chair ACML '23
  • AutoML workshop at ICML '24
  • Program Co-chairs ACML '24

References

    Available Upon Request