Hi, I am Jiahao

Ph.D. student in Machine Learning at MBZUAI
Focused on Explainable AI and controllable generative models for biology
Experienced in protein design, spatial transcriptomics, and AI-driven analytics

Jiahao Zhang

Ph.D. Student in Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)

I am a Ph.D. student in Machine Learning at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), supervised by Lijie Hu. My research focuses on Explainable AI (XAI) and controllable generative models for biological research, including protein design and biomolecular modeling. I have worked extensively on AI applications in biology, from spatial transcriptomics analysis to AI-driven protein affinity design, as well as industry collaborations on large language model–powered analytics.

Research

Team Collaboration

Problem Solving

Skills

Python

Primary language for machine learning research and data analysis; clean, testable research code and reproducible experiments.

C++

Strong foundation in C++ for algorithmic problem solving, performance optimization, and system-level programming.

Java

Knowledge of Java for object-oriented programming, basic backend development, and algorithmic problem solving.

NumPy

Proficient in vectorized operations, numerical computations, and scientific computing workflows.

Pandas

Experienced in data manipulation, preprocessing, and exploratory data analysis with Pandas.

scikit-learn

Proficient in building and evaluating classical ML models, feature engineering, and model selection.

PyTorch

Deep learning framework expertise; experienced with diffusion models, GNNs, transformers, and distributed training.

Hugging Face Transformers

Fine-tuning and inference for LLMs; building RAG pipelines and integrating transformers into production workflows.

Git

Version control with Git; proficient in branching, PR review, and managing research codebases.

Linux

Daily OS for development; shell scripting, server management, and HPC cluster job scheduling.

Experiences

Laboratory of Cell Ethology, CIS, Westlake University

Jan 2025 - July 2025

Hangzhou, China

Interdisciplinary lab focused on computational biology, integrating AI methods with spatial transcriptomics to study tumor microenvironments.

Research Assistant

Jan 2025 - July 2025

Responsibilities:

Led development of TIC (Temporal and Causal Inference of Cellular States), a modular Python framework for spatial transcriptomics analysis in tumor microenvironments.
Integrated LLM-based cell type annotation, GNN feature extraction, pseudotime trajectory inference, and causal analysis of biomarker interactions during EMT.
Designed preprocessing and embedding pipelines, implemented graph-based pseudotime algorithms, and validated through downstream analysis.
Open-sourced and maintained TIC (v2.0.0) to ensure reproducibility and community adoption.

Representation Learning Lab, Westlake University

June 2024 - Dec 2024

Hangzhou, China

Research group focusing on machine learning methods for biological and chemical data, especially generative modeling.

Research Assistant

June 2024 - Dec 2024

Responsibilities:

Developed a RF-diffusion–inspired generative model to design proteins with controllable binding affinity for molecular circuits in synthetic biology.
Designed custom model architectures and training objectives for high/low protein affinity optimization.
Conducted model fine-tuning and experiments to enhance generation quality and functional performance.

AI Lab (Chaowei Xiao), University of Wisconsin–Madison

Oct 2023 - Dec 2023

Remote

Lab specializing in trustworthy AI, adversarial robustness, and AI for cybersecurity.

Research Assistant

Oct 2023 - Dec 2023

Responsibilities:

Developed a benchmark to evaluate AI models for detecting and repairing software vulnerabilities.
Conducted literature review to define evaluation metrics for vulnerability detection.
Designed and ran experiments on real-world vulnerability datasets.
Led data analysis to refine benchmark protocols and highlight improvement areas.

Grapedata / UC Berkeley Data Science Discovery Program

Jan 2024 - May 2024

Berkeley, CA

Industry-academia collaboration delivering AI-powered survey analytics solutions.

Data Science Research Intern

Jan 2024 - May 2024

Responsibilities:

Co-developed an AI-based QA system for B2B survey data, using RAG and zero-shot inference to generate actionable insights.
Designed a two-stage workflow to fine-tune GPT for robust QA and insight generation.
Resolved model tuning and data integration challenges to deliver a production-ready prototype.
Product commercialized at £10,000+ per unit; awarded the Cloud Computing Application Award.

Education

		Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Aug 2025 – Present Ph.D. in Machine Learning Extracurricular Activities: Research areas: Explainable AI (XAI); Controllable generative models for biology. Supervisor: Lijie Hu Research Focus: Explainable AI (XAI); controllable generation for protein/biomolecule design; trustworthy scientific AI.
		University of California, Berkeley Jan 2024 – May 2024 Visiting Student (Data Structures, Artificial Intelligence) Key Courses: Data Structures; Artificial Intelligence. Notes: Academic exchange semester; focus on applied AI and systems.
		Huazhong University of Science and Technology (HUST) Sept 2021 – June 2025 B.Eng. in Electronic Information Relevant Coursework: Probability Theory and Mathematical Statistics; Stochastic Processes; Computational Methods; Digital Circuits; Python Programming; Signals and Systems; Information Retrieval; Principles of Microcomputer; Data Structures.

Projects

Tumor Inference of Causality in EMT Progression

Developer 2025

A computational framework for analyzing cellular micro-environments using graph-based pseudotime analysis and causal inference to study EMT progression in tumors.

academic

Details

LLM-DepthEval Evaluating GPT-4o for Monocular Depth Estimation

Creator 2025

An experimental study on GPT-4o’s ability to perform monocular depth estimation without task-specific fine-tuning.

hobby

Details

Hi, I am Jiahao

Jiahao Zhang

Ph.D. Student in Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)

Skills

Python

C++

Java

NumPy

Pandas

scikit-learn

PyTorch

Hugging Face Transformers

Git

Linux

Experiences

Laboratory of Cell Ethology, CIS, Westlake University

Research Assistant

Responsibilities:

Representation Learning Lab, Westlake University

Research Assistant

Responsibilities:

AI Lab (Chaowei Xiao), University of Wisconsin–Madison

Research Assistant

Responsibilities:

Grapedata / UC Berkeley Data Science Discovery Program

Data Science Research Intern

Responsibilities:

Education

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)

Ph.D. in Machine Learning

Extracurricular Activities:

Supervisor:

Research Focus:

University of California, Berkeley

Visiting Student (Data Structures, Artificial Intelligence)

Key Courses:

Notes:

Huazhong University of Science and Technology (HUST)

B.Eng. in Electronic Information

Relevant Coursework:

Projects

Tumor Inference of Causality in EMT Progression

LLM-DepthEval Evaluating GPT-4o for Monocular Depth Estimation

Recent Posts

Hello MBZUAI

Achievements

Cloud Computing Application Award

Cloud Computing Application Award

Second Prize - College Student Mathematics Competition (Hubei Division)

Second Prize - College Student Mathematics Competition (Hubei Division)

Second Prize - Chinese Mathematics Competition

Second Prize - Chinese Mathematics Competition

Third Prize - China Undergraduate Mathematical Contest in Modeling

Third Prize - China Undergraduate Mathematical Contest in Modeling