Jiliang Hu

Ph.D. in Genetics and currently a Professor of Bioinformatics possessing extensive research experience in protein modification, proteomics, Bioinformatics and AI/ML, with proven expertise in large-scale biomedical data analysis including MS-based proteomics and Single-Cell Transcriptomics (scRNA-seq), coupled with proficiency in Linux and Python/R programming. Proficiency in applying ML/AI techniques to multi-omics datasets and protein analysis including AI-based protein structure prediction and protein design. Familiar with deploying LLMs on HPC servers and solving biomedical problems with AI agents. Proven wet-lab expertise in protein expression and purification and the development of protein biochemical assays. Publications in high-impact journals including Molecular Cell (Featured Article), Plant Physiology (ESI highly cited paper) and Cell Death & Disease. Having previously worked as a Postdoctoral Fellow at the Beatson Institute in the UK, I thrive in collaborative, international research environments. SKILLS & TECHNIQUESØ   Protein biochemistry & Proteomics: Highly experienced in MS-based quantitative proteomics and protein modification characterization (e.g., in pancreatic cancer models). Proficient in recombinant protein expression, protein purification (HPLC/Affinity Chromatography/SEC), and developing biochemical assays to investigate protein functions.Ø   Bioinformatics & AI/ML: Python/R programming, Linux/Bash scripting, SQL, Proteomics (Maxquant/Perseus), NGS and Transcriptomics, single-cell transcriptomics (Seurat/Scanpy), machine learning (Scikit-learn) and deep learning (PyTorch), Docker/Singularity/Conda, HPC platform, Cloud computing (AWS), deployment of LLMs on HPC servers (Ollama/vLLM/ OpenWebUI), Protein structure prediction and protein design (AlphaFold2/3, RFdiffusion, ProteinMPNN), LLM-based development environments (Gemini Code Assist), AI agent application (OpenClaw/Biomni).Ø   Professional Development & Certifications: Mathematics for Machine Learning Specialization (Linear Algebra, Multivariate Calculus, PCA) – ICL (2024); Statistics & Data Analysis in Public Health – ICL (2022); AWS Cloud Practitioner Essentials–AWS (2025); Fundamentals of Machine Learning, AI Use Cases, and Developing ML Solutions–AWS (2025); Regulatory Compliance: Research GDPR and Confidentiality–UK Biobank (2025);RESEARCH GRANTSØ   Principal Investigator (PI): General Program of the National Natural Science Foundation of China (NSFC). 2021-2025. Led the project design, experimental execution, and meticulous data management.