Stanford University
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Mai Thy Truong, MD
Clinical Professor, Otolaryngology (Head and Neck Surgery)
Clinical Professor (By courtesy), PediatricsBioMai Thy Truong, MD, is a Clinical Associate Professor in the department of Otolaryngology – Head and Neck Surgery, division of Pediatric Otolaryngology at Stanford Children’s Hospital. She serves as the Clinic Chief and the Fellowship Director for the division. Dr. Truong oversees a dedicated Microtia and Atresia Clinic to provide care for all the reconstructive and hearing rehabilitative needs of children with microtia and canal atresia. Dr. Truong’s other clinical interests include Vascular Anomalies, Fetal Management of critical airway (EXIT procedure), as well as Congenital head and neck masses and fistulas. Her research has explored the social impact of microtia, 3D modelling in microtia repair, the treatment of complex vascular anomalies and pediatric sleep apnea.
Dr. Truong received her Bachelor of Science from the University of California, Los Angeles in Neuroscience, graduating with honors. She went on to medical school at the University of California, Irvine. Dr Truong completed her residency training at Stanford University Hospital in Otolaryngology, Head and Neck Surgery. She did her Fellowship in Pediatric Otolaryngology at Stanford Children’s Hospital. She completed post-graduate training in Auricular reconstruction, microtia repair, in Paris, France with the world renown plastic surgeon, Dr. Francoise Firmin. Dr Truong is proficient in Spanish and conversational in Vietnamese languages. Her personal interests include musical theater and Karaoke. She strongly believes in the importance of respect for all the diversity of humankind. She is a Bay Area Native and loves the uniqueness that each niche of the Bay Area has. -
Nhi Ngoc Truong
Research Intern, Program-Koyejo, O.
Staff, Program-Koyejo, O.BioNhi is an undergraduate researcher in the Stanford Trustworthy AI Research (STAIR) Lab, advised by Professor Sanmi Koyejo. She studies how we measure the reliability of AI systems, with a focus on the validity of AI benchmarks, meaning whether an evaluation really captures what it claims to and when its results can be trusted. Her current work looks at the assumptions built into widely used language model benchmarks and how to test them more carefully. Her earlier research on language models has appeared at leading natural language processing venues, including co-first-authored work at NAACL 2024 and an ICLR 2024 workshop. Outside of research, she plays in the symphonic band, badminton, and is taking up rock climbing.
