Thang M. Pham

Auburn, Alabama, USA

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I recently completed my Ph.D. in Computer Science at Auburn University advised by Prof. Anh Nguyen, and I am actively seeking full-time research/engineering positions in machine learning and artificial intelligence. My doctoral work has contributed to advancing language models’ capabilities in understanding texts and images, with findings that have been recognized by MIT Technology Review and published in top-tier conferences including ACL, NAACL, or EACL. My current research interests are efficient small language models, model optimization, retrieval-augmented generation (RAG), and multi-agent systems.

During my Ph.D., I completed three research internships at Adobe Research working with Trung Bui, Franck Dernoncourt and David Seunghyun Yoon, where I developed efficient small language models for mobile devices, instruction-following and human preference datasets for image editing, and creating a dataset benchmark for semantic similarity and search. Before my Ph.D., I spent 6 years in industry roles, including 2.5 years as a Research Engineer at National Institute of Advanced Industrial Science & Technology (AIST) collaborating with Makoto Miwa and Mohammad Golam Sohrab to build deep learning systems in biomedical text mining. I also worked as a Software Engineer for 3.5 years, developing over-the-top mobile applications for distant communication. I completed my Honors Bachelor’s Degree in Computer Science at the University of Science (HCMUS) in Vietnam, where my thesis focused on scene text detection and recognition.

news

Nov 23, 2024 [new] 🎉 Excited to share that SlimLM on document assistance for mobile devices has been featured in VentureBeat: “Goodbye cloud, Hello phone: Adobe’s SlimLM brings AI to mobile devices” and Gadgets360!
Aug 03, 2024 🎓 Proud to announce that I completed my Ph.D. from Auburn University. War Eagle! 🦅
Jun 24, 2024 🎯 Joined Adobe Research for my third internship on efficient LLMs for mobile devices on document assistance tasks.
Mar 13, 2024 🎖️ Our work PEEB on part-based explainable and editable image classification has been accepted to Findings of NAACL 2024!
Sep 04, 2023 🎯 Joined Adobe Research for my second internship on LLM-based agents for image editing.
Apr 13, 2023 🏆 Received Graduate Student Council Travel Fellowship from Auburn University.
Apr 06, 2023 🏆 Honored to receive the Diversity & Inclusion Award at EACL 2023.
Jan 21, 2023 🎖️ Our work PiC on phrase understanding and semantic search has been accepted to EACL 2023!

Sep 21, 2022 🎖️ Our work Double Trouble on explaining and improving attribution methods was accepted as an oral presentation at AACL-IJCNLP 2022.
May 17, 2021 🎯 Joined Adobe Research for my first internship on phrase similarity and semantic search.
May 06, 2021 🎖️ Our work Out of Order on explaining and improving language models was accepted to Findings of ACL 2021.
Aug 19, 2019 🎓 Started my Ph.D. journey at Auburn University!