Yu Zhang

Guildford, United Kingdom

School of Chemistry and Chemical Engineering

I am a PhD researcher in Chemical and Process Engineering at the University of Surrey, supervised by Prof. Tao Chen and Assoc. Prof. Dimitrios Tsaoulidis.

My research develops AI-driven modelling, optimisation and digital-twin methods for engineering and healthcare. I focus on data-efficient learning, interpretable models and scientific evidence extraction, with applications in dermal drug formulation and process systems.

Alongside my PhD, I work on clinical machine learning for IVF with Dr Xilu Wang and battery intelligence with Dr Kai Yang at Surrey.

Research interests

Machine learning · Digital twins · Bayesian optimisation · Active learning · Symbolic regression · Scientific LLMs · AI for engineering

Academic background

Previously, I earned an MEng in Control Science and Engineering from China University of Petroleum–Beijing and a BEng in Automation from Panzhihua University. I completed research placements at Jagiellonian University (2026) and West China Hospital, Sichuan University (2025).

My research and academic service include an oral presentation at CHISA 2026 and peer-review contributions. For a fuller record of positions, teaching, awards and scholarly service, see my academic CV.

news

Nov 03, 2026	Our co-authored paper, A Spectral-Continuity-Guided Bayesian Learning Framework for Infrared Spectroscopy-Based Soft Sensor Modeling, has been accepted by Measurement. Accepted on 3 November 2026; publication details are forthcoming.
Oct 27, 2026	SkinMiner: LLM-powered data mining to accelerate formulation design for skin products is available as an SSRN preprint. The manuscript is under review at International Journal of Pharmaceutics. Code
Oct 08, 2026	Our co-authored review, “Optimisation of Topical and Transdermal Pharmaceutical Formulations: Methods, Challenges and Opportunities”, has been accepted by SmartSys. Publication details are forthcoming.
Aug 24, 2026	Presented “LLM-powered multimodal agentic data mining for dermal formulation science” at the 28th International Congress of Chemical and Process Engineering (CHISA 2026) in Prague, Czech Republic. SkinMiner
Aug 03, 2026	Our domain knowledge constrained symbolic regression framework for interpretable dermal formulation optimisation is now published in Pharmaceutical Research. Paper

selected publications

Pharm. Res.

Domain Knowledge Constrained Symbolic Regression for Optimising Dermal Drug Formulations

Yu Zhang , Xilu Wang, Dimitrios Tsaoulidis,

Pharmaceutical Research, 2026

DOI Bib HTML

@article{zhang2026domain,
  title = {Domain Knowledge Constrained Symbolic Regression for Optimising Dermal Drug Formulations},
  author = {Zhang, Yu and Wang, Xilu and Tsaoulidis, Dimitrios and Chen, Tao},
  journal = {Pharmaceutical Research},
  pages = {1--18},
  year = {2026},
  doi = {10.1007/s11095-026-04170-9},
}

CHERD

Active learning-based adaptive optimisation for developing dermal drug formulations

Yu Zhang , Yongrui Xiao, Xilu Wang,

Chemical Engineering Research and Design, 2026

DOI Bib HTML Code

@article{zhang2026adaptive,
  title = {Active learning-based adaptive optimisation for developing dermal drug formulations},
  author = {Zhang, Yu and Xiao, Yongrui and Wang, Xilu and Tsaoulidis, Dimitrios and Chen, Tao},
  journal = {Chemical Engineering Research and Design},
  volume = {232},
  year = {2026},
  doi = {10.1016/j.cherd.2026.07.035},
}

AID

Autonomous AI-Driven Design for Skin Product Formulations

Yu Zhang , Yongrui Xiao, Chunlin Chen,

Advanced Intelligent Discovery, 2026

DOI Bib HTML

@article{zhang2026autonomous,
  title = {Autonomous {AI}-Driven Design for Skin Product Formulations},
  author = {Zhang, Yu and Xiao, Yongrui and Chen, Chunlin and Tsaoulidis, Dimitrios and Yang, Kai and Chen, Tao},
  journal = {Advanced Intelligent Discovery},
  pages = {e70100},
  year = {2026},
  doi = {10.1002/aidi.202500239},
}

CACE

An early decision-making algorithm for accelerating topical drug formulation optimisation

Yu Zhang , Yongrui Xiao, Dimitrios Tsaoulidis,

Computers & Chemical Engineering, 2025

DOI Bib HTML Code

@article{zhang2025early,
  title = {An early decision-making algorithm for accelerating topical drug formulation optimisation},
  author = {Zhang, Yu and Xiao, Yongrui and Tsaoulidis, Dimitrios and Chen, Tao},
  journal = {Computers \& Chemical Engineering},
  volume = {201},
  pages = {109224},
  year = {2025},
  doi = {10.1016/j.compchemeng.2025.109224},
}