I build multimodal and multi-agent LLM systems with applications in affective computing and social intelligence.
I am a CS (Artificial Intelligence) M.S. graduate from USC Viterbi.
I worked as a graduate researcher at the
Intelligent Human Perception Lab, USC ICT
with Prof. Mohammad Soleymani and
Ashutosh Chaubey, focusing on benchmarking and improving multimodal LLMs for paralinguistic understanding.
I also worked at the Melady Lab
with Prof. Yan Liu and
Wei Yang
on multi-agent collaboration and reinforcement learning.
Adversarial benchmark to evaluate language dominance on audio LLMs' paralinguistic understanding, with controlled linguistic-acoustic contradiction (2k clips, 10 tasks). Proposed PCLM, a novel layer fusion strategy improving baselines by 48% coupled with DPO.
Knowledge corruption attacks against GraphRAG achieving up to 70% attack success rate with GPT-4o-mini. Developed a benchmark with highly inter-connected named-entity graphs and an extensive per-question indexing pipeline.
Fusion-based audio-textual speech emotion captioning with early, late, and X-Norm fusion strategies. X-Norm achieved 20%↑ GPT-evaluated match rate over early/late baselines using prefix-conditioned decoders with a pretrained LLM.
More details on CV.