About Me
During my undergraduate studies, I honed my skills through programming contests, Olympiads, voluntary presentations, and collaborative events, tutoring students as a teaching assistant, instructing online courses, and more. From developing embedded hardware systems and web/mobile apps to artificial intelligence applications, I pursued a broad understanding of Computer Engineering, culminating in my thesis "Model-Based Collaborative-Filtering Recommender System".
As a master's student in Computer Science, my journey continued as I delved deeper into deep learning, natural language processing, and audio pattern recognition. Actively engaging in advanced coursework and research, I graduated with honors (Cum Laude), completing a thesis entitled "Domain Generalization for Multimodal Audio-Textual Depression Detection".
Now, as a passionate Ph.D. candidate in Computer Science, I focus on the intersection of explainable deep learning and domain generalization for Health AI applications. Through this dedication, I strive to remain at the forefront of these rapidly evolving disciplines, and unlock innovative solutions that push the boundaries of AI for healthcare.
