❖ With 7 years of experience in the field, I am a multifaceted professional who excels as an engineer, researcher, and educator.
❖ My engineering background includes hands-on involvement in various machine learning and AI projects across diverse domains, such as healthcare, defense, and fintech.
❖ As a researcher, I have a solid track record of publishing A/A* papers on cutting-edge topics, including Trustworthy Machine Learning and Generative AI, and I co-organize the Monash GenAI Reading Group to foster collaboration and knowledge sharing.
❖ In my role as an educator, I serve as the Head Teaching Associate at Monash and as a lecturer at VietAI, where I passionately engage students in the intricacies of ML/AI.
❖ I also contribute to the field through my ML/AI blog.
❖ Driven by a strong work ethic, I strive to balance these multiple roles while continuously seeking to enhance my productivity and impact.
Project list
Monash - Australia
Develop more robust and reliable generative models, particularly, erasing unwanted concepts from foundation models.
- Developing novel algorithms/methods.
- Benchmarking with state-of-the-art methods.
- Submitting papers to prestigious international conferences in Machine Learning, Al.
- Reporting to different stakeholders involved in this project.
- GenAl
Technologies: Deep Learning, PyTorch, Machine Learning
RapidAl - US
Detecting Gaze-Deviation on patients for early stroke alerting.
- Developing machine learning model to detect Gaze-Deviation for stroke detection (sample).
- Object detection
- Developing Neural Compression algorithms to reduce memory and computational cost of Deep Neural Networks developed on mobile hardware such as FPGAs (uncompleted patent).
- Improving Generative Adversarial Networks (GANs), esp. in the mode collapse problem.
- Developing ML modules to detect and track Undefined Flying Objects (i.e., Drones) in the Sky Surveillance - Flying Object Detection (SSFOD) project.
- Developing image retrieval modules handling large large-scale real-world dataset (appr. 200k images) in the Urban-area Scene Based Localization (USBL) project.
Technologies: Deep Learning, Computer Vision, Machine Learning
Education
Monash University
01/2019 - 01/2023
Computer Science
Techstacks
Others
Python, PyTorch, TensorFlow, C++, Machine Learning, Deep Learning, NLP, Computer Vision, Git, VS Code