AI Agent Researcher · TaoTian Group @ Alibaba
AI Agent · Time-Series Forecasting · LLMs · Multilingual NLP · RLHF Alignment
I am an AI Agent Researcher at Alibaba TaoTian Group, building predictive AI Agents for logistics & supply-chain optimization. Previously at Tencent Hunyuan, where I worked on MMLU, CMMLU and other benchmark improvements, and Baidu ERNIE Core Team, where I focused on multilingual capabilities and LLM Arena rankings.
I hold an MSc in Computer Science from the University of Glasgow (USNews #62), where I worked with Prof. David Manlove (University of Oxford) on efficient text search algorithms. My research interests lie at the intersection of AI Agents, scalable LLM training, alignment techniques, and multilingual NLP.
Joined Alibaba TaoTian Group as AI Agent Researcher, working on AI Agent applications for logistics and supply-chain optimization.
ERNIE EB5 tied #2 globally on LMArena (China #1), surpassing DeepSeek – Text Arena win rate 86.4%, multilingual avg accuracy 92%.
Vision-Arena: EB5-VL achieved +25.5% win rate vs baseline, tied #1 industry-wide.
Patent filed: "A Multi-Agent and LLM Collaborative Multi-Dimensional Text Quality Scoring System" (First Inventor, under review).
Paper "Evaluation and Optimization of Efficient Text Search Algorithms" submitted to ICASSP 2026 (First Author, under review).
Paper "Price-Aware Dynamic Heterogeneous Hypergraph Network for Next Basket Recommendation" published at ICASSP 2025 (Second Author).
AI Agent for time-series forecasting, combining foundation models (TimeGPT/TimesFM-style) with LLM reasoning for accurate predictions across diverse domains.
Designing modular agent frameworks with episodic/semantic memory and hierarchical planner-executor-reflector patterns for supply-chain optimization.
AI Agent for photo compliance detection and physical defect inspection on second-hand products.
ICASSP 2026 · Oct 2025
Evaluated 7 classical string-matching algorithms on large corpora; proposed a suffix-tree-based algorithm combined with Ukkonen's construction, achieving ~5.2× speedup on large-scale datasets. Targeted human gene sequence search with 40% speed improvement on 3 billion sequences.
ICASSP 2025 Second Author · Mar 2025
Proposed a dynamic heterogeneous hypergraph network that incorporates price signals into next-basket recommendation, capturing complex item correlations and temporal purchase dynamics.
· Nov 2025
· Jul 2024
Co-Inventor · Jun 2024
TaoTian Group — AI Agent Researcher
ERNIE Foundation Model Core Team — Research Scientist (Senior)
Hunyuan Text-to-Text Pipeline Team — Research Scientist
Hunyuan Strategy Group 4 — Research Scientist
Research Assistant Intern
Yoho Department — Software Engineer
Reconstructed classification tasks into QA framework across multiple 7B models. Structured prompt templates for complex user behavior recognition. AUC 0.9923, Recall 98.83% on CERT dataset. LoRA/P-tuning on ~0.01% parameters: training time −30%, compute −50%.
Collaborated with Prof. David Manlove (University of Oxford). Evaluated 7 classical algorithms (KMP, BM, suffix tree, Ukkonen, etc.) on 1M+ samples from NLTK corpora. Proposed suffix-tree + Ukkonen approach: ~5.2× speedup. Gene sequence search: 40% faster on 3B sequences, 5× on 20M test set at 100% accuracy.
Classified central neuropathic pain in spinal cord injury patients. Integrated variance thresholding, chi-square, RFE, and local linear embedding with KNN and SVM on 5,000 EEG samples. KNN accuracy 69.4%→77.8% (+8.4 pts); SVM accuracy 94.4% with mitigated overfitting.
Applied BERT-based data augmentation (~25% of dataset) to whole-slide imaging. Evaluated K-Means, Louvain, PCA, and UMAP approaches. Contributed to a related conference paper draft.
Enhanced Llama2 7B-Chat for a tourism-domain dialogue system with fine-tuning, retrieval augmentation, and domain-specific knowledge injection.
MSc in Computer Science
Research collaboration with Prof. David Manlove (University of Oxford) on efficient text search algorithms.
BEng in Software Engineering