Albert Tuan - MACHINE LEARNING

Albert Tuan

4.9

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Albert Tuan

4.9

Gender

Male

Main expertise

Machine Learning AI Deep Learning Data Scientists Computer Vision Neural Network Python PyTorch Image Processing Software NLP Data Algorithm

Introduction

Albert Tuan is a versatile professional with 7 years of experience, excelling as an engineer, researcher, and educator. His engineering background is marked by active participation in diverse machine learning and AI projects within domains such as healthcare, defense, and fintech. As a researcher, Albert has an impressive record of publishing A/A* papers on pioneering topics like Trustworthy Machine Learning and Generative AI, and he co-organizes the Monash GenAI Reading Group to promote collaboration and knowledge exchange. In his educational role, he serves as the Head Teaching Associate at Monash and lectures at VietAI, engaging students in the complexities of ML/AI. Additionally, he contributes to the field through his ML/AI blog. Albert is driven by a strong work ethic, striving to balance his multiple roles while continuously enhancing his productivity and impact.

Project list

Monash Project - Australia

The project focuses on enhancing generative models to be more robust and reliable, specifically working on erasing unwanted concepts from foundation models.

Developing novel algorithms and methods. Benchmarking with state-of-the-art methods. Submitting papers to prestigious international conferences in Machine Learning and AI. Reporting to different stakeholders involved in the project. General administrative and project management tasks.

Technologies: Diffusion Models, Pytorch

RapidAI - US

A project focused on detecting Gaze-Deviation in patients to provide early alerts for potential strokes.

Developing machine learning models to detect Gaze-Deviation for stroke detection. Conducting object detection tasks.

Technologies: Semantic segmentation, Pytorch

Trusting Social - Facial Recognition Project - Vietnam

Developed face matching and recognition algorithms used in a credit scoring system, enhancing the accuracy and reliability of identity verification.

Developing face matching and face recognition algorithms for the credit scoring system. Object detection.

Technologies: Semantic segmentation, Pytorch

Temasek Laboratory - Singapore

The project involves developing neural compression algorithms for mobile hardware, improving GANs, and implementing machine learning modules for detecting and tracking drones. It also focuses on large-scale image retrieval for urban scene localization.

Developing neural compression algorithms to reduce memory and computational costs of Deep Neural Networks on mobile hardware like FPGAs (patent pending). Improving Generative Adversarial Networks, with a focus on addressing the mode collapse problem. Developing machine learning modules to detect and track undefined flying objects, like drones, in the Sky Surveillance - Flying Object Detection project. Developing image retrieval modules for handling large-scale datasets (approximately 200k images) in the Urban-area Scene Based Localization project.

Technologies: Generative Adversarial Networks (GANs), Object Detection, Model Compression, Image Retrieval

Project list

Education

Expertise