Summary
Manh Nguyen is a doctoral candidate in AI with nine years of industry and research experience focused on speech and multimodal technologies. He has led work on explainable AI for speech pathology assessment, producing a new state-of-the-art system for head and neck cancer evaluation and first-author papers at LREC-COLING ’24 and SLT ’24. His research blends practical privacy-preserving techniques—such as federated learning with Wav2Vec 2.0 used in ICASSP ’23—with efforts to model and incorporate inter-rater variability for more robust clinical assessments. He has international research exposure through a JSALT workshop and a visiting stint at Johns Hopkins developing multimodal audio–text–image models toward universal audio generation. Comfortable moving from prototype to deployed systems, he also has commercial AI experience building recommendation, image-recognition and distributed-training solutions for clients in Japan. Seeking postdoctoral or research-oriented industry roles, he brings a rare combination of clinical-focused evaluation expertise, XAI, and privacy-aware speech technology.
9 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Information and Communication Technology, 13.64/20, Bachelor's degree, Information and Communication Technology, 13.64/20 at University of Science and Technology of Hanoi
Master's degree, Artificial Intelligence, Master's degree, Artificial Intelligence at Università di Trento
High School Diploma, Physics, High School Diploma, Physics at Chu Van An National High School
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at Avignon Université
French, English, Vietnamese