Scholar
Tuan Dung Nguyen
Google Scholar ID: mmy1v8oAAAAJ
University of Pennsylvania
Citations & Impact
Citations
1,556
H-index
9
i10-index
9
Publications
20
Co-authors
6
list available
Publications
Resume (English only)
Academic Achievements
- 1. Paper accepted at AAAI 2024: 'On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods', selected for oral presentation
- 2. Paper accepted at ICWSM 2024: 'Measuring Moral Dimensions in Social Media with Mformer', selected for spotlight presentation
- 3. Released AstroLLaMA, a language model for astronomical research
Research Experience
- 1. M.Phil. student at the Computational Media Lab, Australian National University
- 2. Visiting student at the Mathematics and Computer Science Division, Argonne National Laboratory
- 3. Teaching assistant at the 2024 Summer Institute in Computational Social Science, University of Pennsylvania
- 4. Presented a talk titled “How Aligned are Humans and Language Models on Common Sense?” at the Generative AI and Social Science Research Workshop, Yale University
- 5. Delivered a talk titled “Science Meets AI: Lessons from the Exploration of LLMs in Astronomical Research” at the Planet+AI consortium
- 6. Co-released AstroLLaMA-chat, a conversational LLM based on earlier work at UniverseTBD
- 7. Published multiple papers, including those accepted at AAAI 2024 and ICWSM 2024
Education
- 1. Ph.D. student at the Department of Computer and Information Science, University of Pennsylvania, advised by Duncan Watts (Computational Social Science Lab)
- 2. M.Phil. student at the Computational Media Lab, Australian National University, jointly advised by Lexing Xie (School of Computing) and Colin Klein (School of Philosophy), thesis on large-scale studies of online discussions to uncover popular topics of contemporary moral concern
- 3. B.S. in computer science at the School of Computing and Information Systems, University of Melbourne, worked with Charl Ras (School of Mathematics and Statistics) on designing resilient network embeddings
Background
- Ph.D. student in computational social science, interested in developing computational and human-in-the-loop methods to study individual and collective human behavior, such as moral decision-making and judgment, stance toward socially significant issues, and commonsense intelligence. Also interested in mathematical optimization, particularly in the context of machine learning, including designing personalized and communication-efficient algorithms for federated learning.
Miscellany
- Other interests include mathematical optimization, especially in the context of machine learning, and designing personalized and communication-efficient algorithms for federated learning.
