Homepage of Dr. Hung Le
About
I am Hưng, a research lecturer at Applied Artificial Intelligence Institute (A2I2), Deakin University.
My Research
My current research focus is machine learning, deep learning and artificial memory. Inspired by biological systems and traditional computer architectures, I am deeply passionate about advancing the capacity of neural networks for representational (the what) and functional (the how) learning in computer science. In particular, I am keen to invent new deep models with access to artificial neural memory and have created a body of work in advancing this area including multi-modal and generative memory, theoretical foundation for memory operations, general-purpose neural computers and memory-based reinforcement learning agents. Applications include health, dialog system, reinforcement learning, machine reasoning and natural language processing.
Current Projects
- Neural Memory Architecture
Construct cognitive architectures using deep neural networks - Lean Reinforcement Learning
Endow RL agents with memory to achieve sample-efficiency - Human-AI Symbiosis
Build trustworthy AI agents that are aware of human’s needs - Complex System Forcasting with Domain Knowledge
Advance time-series prediction with expert knowledgeNews
2024 Blog: I plan to transfer my blogs to Substack for ease of management
02/2024: I will deliver a tutorial at AAMAS 2024. The tutorial will be about exploration in RL.
12/2023: 1 paper accepted at AAMAS 2024
11/2023: 1 paper accepted at Transactions on Machine Learning Research journal
Older
2024 Spring Intake: I am looking for 1 PhD student (full scholarships) who want to work directly with me on neural memory or reinforcement learning topics. Ping me if you find it interesting.
09/2023: 1 paper accepted at ACML 2023 and another at Artificial Intelligence journal
08/2023: I will serve as Senior Program Committee at AAAI 2024
07/2023: My 2023 PhD scholarship was given to Hoang Nguyen and Dai Do
04/2023: 1 paper accepted at IJCAI 2023 and another at International Journal of Impact Engineering
01/2023: 1 paper accepted at ICLR 2023
12/2022: I have delivered AJCAI22 tutorial on Memory-based Reinforcement Learning
11/2022: 1 paper accepted at AAAI 2023
09/2022: 3 papers accepted at NeurIPS 2022 and another 2 at ICONIP 2022
07/2022: I will serve as Senior Program Committee at AAAI 2023
06/2022: 1 paper accepted at ECCV 2022
05/2022: 1 paper accepted at ICML 2022
03/2022: I was promoted to Research Lecturer Position (Permanent Track)
01/2022: 1 paper accepted at NAACL 2022
12/2021: 1 paper accepted at ICLR 2022
Past Topics
- Memory and Attention in Deep Learning (my PhD at Deakin University, 2017-2020) PhD. Thesis. My great supervisors: A/Prof. Truyen Tran and Prof. Svetha Venkatesh
- Graphical & Topic Model (when I did Master at HUST with A/Prof. Khoat Than, 2016-2017 dropout)
- Kalman Filter & Optimal Control (when I worked at Viettel R&D, 2015-2017)
- Fuzzy Logics (when I did Bachelor Honours at HUST with A/Prof. Khang Tran, 2015)