Institute of Automation, Chinese Academy of Sciences
Incoming Ph.D. Student Β· Supervisor: Prof. Kaiqi Huang
I'm an undergraduate student majoring in Communication Engineering at Tongji University, expecting to graduate in June 2027.
Incoming Ph.D. Student at the Institute of Automation, Chinese Academy of Sciences
Expected start: September 2027 Β· Supervisor: Prof. Kaiqi Huang
I explore simple, elegant ways to make AI models more capable. My interests span multimodal large language models, image/video generation, and embodied AI.
Incoming Ph.D. Student Β· Supervisor: Prof. Kaiqi Huang
B.Eng. in Communication Engineering
Major rank: 2/85
Research Intern
Research Intern
Research Intern
A local-first image conversion studio with editable SVG paths and native PowerPoint exports.
Citation-aware AI search with an arXiv paper radar and an integrated PDF reader.
An AI technical-interview practice app with follow-up questions and structured feedback.
Vitis HLS algorithm optimization for the AMD FPGA competition track on a Zynq-7000 target.
A maintained collection of reusable workflow skills for computer science and electrical engineering research.
* Equal contribution Β· Corresponding author indicated where applicable.

We study open-vocabulary audio-visual event localization when visual and audio teachers differ in reliability. OV-OrthKD places their supervision in separate orthogonal feature paths and uses text prototypes for open-vocabulary transfer.
ACM MM 2026

We study multi-teacher distillation for diabetic retinopathy screening. OrthKD transfers complementary feature-level knowledge from heterogeneous teachers to a 5.4M-parameter MobileNetV3 student.
IJCAI 2026

We convert images into grammar-constrained scene descriptions for text-only LLMs. On a stratified 5,000-image VQAv2 subset, DeepYOLO reaches 42.3% accuracy using 1/2.5 as many prompt tokens as the scene-graph baseline.
IJCNN 2026 Corresponding Author

Research on assessing whether generated images satisfy textual instructions, with a focus on reliable evaluation.
Preprint 2026

Research on evaluating the evidence used to explain neural-network behavior and the reliability of the resulting interpretations.
Preprint 2026

Research on how learning in visual understanding relates to image-generation behavior in multimodal models.
Preprint 2026

Research on identifying unreliable predicted physical fields efficiently, with a focus on neural operators and single-pass risk assessment.
Preprint 2026
Reviewer