Towards More Human-Like Cross-Lingual Learning
Research reflections based on my dissertation proposal, “Towards More Human-Like Cross-lingual Transfer Learning” (USC, 2023).

I'm a machine learning researcher with a PhD in Computer Science from USC, specializing in Natural Language Processing. I'm currently a Generative AI Research Collaborator at Meta Superintelligence Labs, where I focus on LLM evaluation, post-training data quality, and improving model reliability.
My background combines academic research in areas like meta-learning and continual learning with industry experience at Meta and Microsoft, where I've worked on model evaluation, personalized recommendation systems, and improving AI performance.
What motivates me most is bridging research and real-world impact. I'm particularly interested in developing more intuitive, human-centered approaches to AI evaluation, incorporating human feedback to make AI systems more natural and reliable, and making these technologies accessible to people across different languages and communities.
Research reflections based on my dissertation proposal, “Towards More Human-Like Cross-lingual Transfer Learning” (USC, 2023).
Based on my research on cross-lingual continual learning and the corresponding chapter of my dissertation proposal.
An accessible introduction to the few-shot and meta-learning thread of my dissertation research.
If a borderless world is an impossible fantasy, reducing borders between languages at least is not out of reach. With over 6,500 spoken languages around the globe, creating a unique customer service experience for everyone is a challenge faced by...