I am Jiahao Zhang (张家豪), a first-year PhD student in the Machine Learning Department at MBZUAI.

Research Interest. I study Explainable AI (XAI) as an interactive toolkit to understand and steer model behavior, and to build human-actionable interfaces for reasoning and control.

I use AI for Science as a rigorous stress test: scientific problems provide external, verifiable constraints (simulation/experiments), enabling a closed loop of explain -> intervene -> validate, so XAI improves not only interpretability but also reliability and real-world effectiveness.

PhD Supervisor: Prof. Lijie Hu
Secondary Supervisor: Prof. Kun Zhang

🔥 News

2026.05: 🎉 Our paper Bayesian Gated Non-Negative Contrastive Learning was accepted to ICML 2026 (with Peng Cui, co-first; Lijie Hu, corresponding).
2026.04: 📝 Submitted our manuscript Solar-driven evapofiltration enables co-production of lithium and freshwater from extreme brines to Nature Sustainability.
2026.03: 🚀 Launched AgentReviewers (agentreviewers.com) — a submission and peer-review platform built for AI-generated papers — and open-sourced Agent Kernel.
2026.02: 🎉 Our paper Controlling Repetition in Protein Language Models was accepted as an ICLR 2026 Poster.
2025.08: 🎉 I joined MBZUAI as a phd student in Machine Learning Department, new start point here!

📝 Publications

Published

Controlling Repetition in Protein Language Models cover

Click cover to view abstract

Protein language models (PLMs) frequently collapse into pathological repetition during generation, which undermines structural confidence and functional viability. We present a systematic study of repetition in PLMs and propose Utility-Controlled Contrastive Steering (UCCS), which steers generation using contrastive sets that maximize repetition differences while controlling structural utility. Across ESM-3 and ProtGPT2 on CATH, UniRef50, and SCOP, UCCS reduces repetition without retraining while preserving foldability-related confidence.

Controlling Repetition in Protein Language Models

Published AI4Sci

ICLR 2026 · Poster

Jiahao Zhang^†, Zeqing Zhang^†, Di Wang, Lijie Hu^✉

PDF arXiv Code Project

Keywords: Protein Language Models, Reliable Protein Generation, Repetition Control

@misc{zhang2026controllingrepetitionproteinlanguage,
  title={Controlling Repetition in Protein Language Models},
  author={Jiahao Zhang and Zeqing Zhang and Di Wang and Lijie Hu},
  year={2026},
  eprint={2602.00782},
  archivePrefix={arXiv},
  primaryClass={q-bio.BM},
  url={https://arxiv.org/abs/2602.00782},
}

Bayesian Gated Non-Negative Contrastive Learning cover

Click cover to view abstract

Accepted to the Forty-Third International Conference on Machine Learning (ICML 2026). A Bayesian gated non-negative contrastive learning framework that improves the interpretability and reliability of learned representations. Full paper, arXiv preprint, and code release coming soon.

Bayesian Gated Non-Negative Contrastive Learning

Published XAI

ICML 2026

Peng Cui^†, Jiahao Zhang^†, Lijie Hu^✉

[Link] [ArXiv] [code]

Keywords: Contrastive Learning, Bayesian Gating, Non-Negative Representations, Interpretability

Under review

Solar-driven evapofiltration enables co-production of lithium and freshwater from extreme brines cover

Click cover to view abstract

Brines are an important lithium resource, but their utilization remains limited by poor lithium selectivity in highly saline, magnesium-rich environments and by freshwater scarcity in the arid regions where many such resources occur. Here we report evapofiltration, a separation strategy for simultaneous production of freshwater and lithium from extreme brines. The strategy is realized using an evapofiltration membrane that integrates a commercial nanofiltration membrane with a carbon-nanotube photothermal layer in a recirculating NF evaporator. In Dead Sea brine composition, the system driven by solar sustained freshwater production at 1.24 kg/m^2/h while achieving 320-fold lithium enrichment over four stages, ultimately yielding battery-grade Li2CO3 with 99.58% purity. An experimentally informed artificial-intelligence framework further integrates brine chemistry and local solar conditions to predict site-specific lithium and freshwater production from diverse brine resources worldwide. Evapofiltration therefore provides a promising route for integrated lithium recovery and freshwater generation from extreme brines in water-scarce regions.

Solar-driven evapofiltration enables co-production of lithium and freshwater from extreme brines

Under review AI4Sci

Submitted to: Nature Sustainability 2026

Honglang Lu, Jiahao Zhang, Xingxiang Li, Jing Li, Yishuo Huang, Xiaoqin Zhong, Lijie Hu, Jun Ma, Zongyao Zhou^✉

Code

Keywords: Brine Chemistry, Lithium Recovery, Solar Energy, Photothermal Membrane, Evapofiltration, AI for Science

Author marks: * indicates single first author, † indicates co-first authors, and ✉ indicates corresponding author.

🚀 Projects

AgentReviewers

Lead Active 2026-present Category: Agentic AI Topic: AI Paper Submission & Review

AI Agents Paper Review AI Generated Papers Web Platform

Submission and peer-review platform purpose-built for AI-generated papers, enabling agents to submit, review, and iterate on academic manuscripts in a structured loop.

Web

Agent Kernel

Lead Active 2026-present Category: Agentic AI Topic: Agent System Framework

AI Agents Framework Open Source LLM

An open-source kernel for building agent-based AI systems, providing composable skills, APIs, and runtime primitives for orchestrating LLM agents.

Web Code

GlobalBrine-LithiumModel

Lead Active 2025.12-present Category: AI4Sci Topic: Brine Chemistry & Lithium Selectivity

AI4Sci Geochemistry Machine Learning Web Platform

Predictive lithium selectivity platform for brine science with map-based exploration, single-point inference, and reproducible batch jobs.

Web Code

🛠 Open Source Tools

MEAP (Lead)
GitHub | TestPyPI

🎖 Honors and Awards

2026.02, MBZUAI Conference Travel Grant.
2024.05, Cloud Computing Application Award, UCB Data Science Discovery Program.
2023 - 2024, Undergraduate Academic Excellence Scholarship.
2023.03, Second Prize, College Student Mathematics Competition (Hubei Division).
2023.01, Second Prize, Chinese Mathematics Competition.
2022.09, Third Prize, China Undergraduate Mathematical Contest in Modeling.

📖 Educations

2025.08 - Present, Ph.D. in Machine Learning, MBZUAI, Abu Dhabi, UAE. Supervisor: Prof. Lijie Hu.
2021.09 - 2025.06, B.Eng. in Electronic Information, Huazhong University of Science and Technology (HUST), Wuhan, China.
2024.01 - 2024.05, Visiting Student, UC Berkeley, Berkeley, CA, USA.

💻 Internships

2025.01 - 2025.07, Research Assistant, Laboratory of Cell Ethology (CIS), Westlake University, Hangzhou, China.
2024.06 - 2024.12, Research Assistant, Representation Learning Lab, Westlake University, Hangzhou, China.
2024.01 - 2024.05, Data Science Research Intern, Grapedata (UC Berkeley), Berkeley, CA, USA.
2023.10 - 2023.12, Research Assistant (Remote), AI Lab (Chaowei Xiao), University of Wisconsin-Madison.

🧾 Services

Reviewer: ICML 2026
Reviewer: ACL Rolling Review (Jan 2026)
Reviewer: IEEE Computational Intelligence Magazine (IEEE CIM)