CV

Education

University of California, Los Angeles (UCLA) | 2021-Present
Ph.D. in Computer Science

Advisor: Aditya Grover

Hanoi University of Science and Technology (HUST) | 2015-2020
Bachelor in Information Systems

Thesis: Predictive Coding for Locally-Linear Control
Thesis advisor: Khoat Than
GPA: 3.65/4.00, graduated with Excellent Degree

Research experience

Research Intern | 2022
Microsoft Research, Autonomous Systems and Robotics Group

Supervisor: Jayesh Gupta, Ashish Kapoor
Research Topic: General-purpose Pretraining for Climate Modeling

AI Resident | 2019 - 2021
VinAI Research, Vietnam - website: www.vinai.io

Supervisor: Hung Bui
Research Topic: Representation Learning for Planning in Latent Space

Research Student | 2018 - 2019
Data Science Lab (DSLab), HUST - website: ds.soict.hust.edu.vn/

Supervisor: Khoat Than
Research Topic: Life-long Learning for Statistical Models

Publications

ClimaX: A Foundation Model for Weather and Climate
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta*, Aditya Grover*
International Conference on Machine Learning (ICML), 2023.
Best Paper at ICML Workshop on Synergy of Scientific and Machine Learning Modeling, Spotlight Oral at ICLR Workshop on AI and Climate Change.

Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling
Tung Nguyen, Aditya Grover
International Conference on Machine Learning (ICML), 2022.

Temporal Predictive Coding for Model-based Planning in Latent Space
Tung Nguyen*, Rui Shu*, Tuan Pham*, Hung H. Bui, Stefano Ermon
International Conference on Machine Learning (ICML), 2021.

Predictive Coding for Locally-Linear Control
Rui Shu*, Tung Nguyen*, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung H. Bui
International Conference on Machine Learning (ICML), 2020.

Infinite Dropout for training Bayesian models from data streams
Son Nguyen, Tung Nguyen, Linh Ngo, Khoat Than
IEEE International Conference on Big Data (Big Data), 2019.

Under Review

Synthetic Pretraining for Few-shot Black-Box Optimization | 2023
Tung Nguyen, Sudhanshu Agrawal, Aditya Grover

ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling | 2023
Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover

Reliable Conditioning of Behavioral Cloning for Offline Reinforcement Learning | 2022
Tung Nguyen, Qinqing Zheng, Aditya Grover

Projects

Representation Learning for Locally-Linear Control | 2020

Get familiar with the literature of Learning Controllable Embedding – an approach to the problem of control from high-dimensional observations
Replicate the results of Prediction, Consistency, Curvature (PCC) – the contemporary state-of-the-art method
Open the source code: github.com/VinAIResearch/PCC-pytorch

Honors and Awards

Amazon Student Doctoral Fellowship | 2022-2023
Department of Computer Science, UCLA
Each year 12 doctoral students who work in the field of AI are selected as Amazon fellows. Amazon fellows receive full funding for one academic year to pursue independent research projects.

Best Thesis Award | 2020
School of Information and Communication Technology, HUST
The best thesis was selected among over 400 graduation theses in the Fall Semester, 2020.

Academic Services

Reviewer
ICML (2021, 2022, 2023), Neurips (2021, 2022), ICLR (2022)

Teaching Assistant
CS161 Fundamentals of Artificial Intelligence – UCLA

Hold discussion sections and office hours

Technical Talk | 2020
AI Day 2020: Rising to the Challenges - website: ai2020.vinai.io

Present the work Predictive Coding for Locally-Linear Control at AI Day 2020 - the event which welcomed technical talks from top researchers around the world and attracted over 20,000 views online.
Slides: bit.ly/3kzVlCe
Talk: bit.ly/3f6fG10

Technical Talk | 2019
Data Science Lab (DSLab) – HUST

Present the line of work on Representation learning for control from high-dimensional observations.
Slides: bit.ly/3kAnZTy

Teaching Assistant | 2019
Data Science Laboratory (DSLab) – HUST

Run a seminar on fundamental machine learning models such as linear regressions, k-nearest neighbors, support vector machines and neural networks for new students
Help new students get hands-on experience with Tensorflow – a deep learning framework

Technical Skills

Programming Languages: Python, C/C++, Java, JavaScript
Libraries: Pytorch, Tensorflow, Numpy, Matplotlib
Developer Tools: Git

Certificates

TOEFL: 107 Overall, 29 Reading, 28 Listening, 27 Writing, 23 Speaking

Reinforcement Learning Specialization by University of Alberta

Deep Learning Specialization by deeplearning.ai