Alex Bui Email and Phone Number

- Generative AI models for Protein Structure Generation & Antibody design- LLMs & RAG-based systems for Pathology (Oncology) Diagnosis

• Research topics: LLM-based applications, Language Modeling, Computer Vision, eXplainable AI, Data Science, and Graph Analytics.• Publications: Author 15 papers and got four papers accepted at renowned conferences like IEEE ICDM 2023 (20% acceptance rate), PAKDD 2023 (17% acceptance rate), and PAKDD 2024- LLM Research: Worked on an NL-2-SQL project, focused on optimizing prompt tuning for translating natural language questions into SQL queries based on a data-driven approach and RAG; Researched soft-prompt tuning and fine-tuning techniques to enhance LLM capability of working with complex data like graphs.- Language Modeling: Researched advanced language models like Transformer, BERT, and GPT-2 and proposed a novel paraphrase generation algorithm based on GPT-2.- Computer Vision Research: Researched and applied object detection algorithms to tackle real-world applications like smart car parking systems and real-time social distancing alert systems.• AI-Based Music Annotation System: Developed an AI-driven system for annotating musical performances using React and Flask, implemented in SNU’s piano department, benefiting 100+ students and professors.• XAI Research: Research XAI algorithms, especially for GNNs, resulting in three top-conference publications and one journal paper.• Graph Database Project: Developed a private in-memory graph database, enhancing graph data processing efficiency and integrating with GNN computational operations.• Hotspot Analysis in Supply Chain Graph: Conducted advanced data analysis to identify hotspots in thesupply chain graph using k-core and PageRank algorithms with the Bloomberg dataset. This work is a part of a confidential project on stock movement forecasting.

- TA of the following courses at Graduate School of Data Science: - Explainable Artificial Intelligence (2021, 2022) - Machine Learning & Deep Learning for Data Science (2020, 2021) - Distributed Machine Learning Systems (2020)- I designed and delivered 10+ programming assignments for these courses. I also set up working environments for students to work with Hadoop, Spark, Horovod, and Ray.- I helped to develop comprehensive ML & DL projects for Graduate School of Data Science graduate qualifying exams, benefiting 200+ students.

- Seoul Urban Data Science: Conducted research on deep learning models for air quality forecasting and authored 2 papers, cited 140+ times.- I was the core team member participating in the AI track Zhongan Hackathon 2018. We got over 80 teams and ranked as the top five AI teams in the final round. Zhongan is an insurance company in China that hosted a hackathon gathering over 400 distinguished post-graduate students in AI & Blockchain.

- Traffic Flow Analysis: Developed a traffic flow visualization application based on Spark, Flask, and AngularJS.

- Developed 5+ web applications for marketing campaigns of big retail companies (e.g., Nam Duoc JSC), benefiting more than 10K customers.

- Led a team to develop a CRM software successfully deployed to our first customer, a telesales company- Led a team to develop a mobile application for salespeople in ERP solutions

- Developed games & applications using Javascript and HTML5- Participated in outsourcing projects