Artificial Intelligence Engineer | Problem-solving • Decision Intelligence • Practical Systems
Senior AI/ML leader with 9.4 years delivering practical solutions across pharma, chemicals, materials, manufacturing, and consumer goods. Focused on problem framing, algorithm development, uncertainty-aware modelling, and end-to-end delivery.
Delivered projects to enterprise clients including Rolls-Royce, BAT, NASA, voestalpine, and FUCHS (many clients under NDA). Built AI platforms from research through production, with expertise in ML for sparse, noisy, high-dimensional industrial data and modern tooling including LLMs.
Bridge technical depth (PhD, 20+ peer-reviewed publications, chartered engineer) with commercial acumen and hands-on implementation.
Algorithm Development • Conformal Prediction • Uncertainty Quantification • Bayesian Optimization • Active Learning • Deep Learning • Federated Learning • Adaptive Experimental Design
LangChain/LangGraph • RAG Systems • Multi-Agent Architectures • MCP Protocol
Python (NumPy, Pandas, SciKit-Learn, PyTorch, TensorFlow) • Docker • MCP (Model Context Protocol) • REST APIs • FastAPI • Backend Development • Full-Stack Product Building • SQL • GCP/Vertex AI • Git • CI/CD
Materials Science • Pharmaceuticals • Chemicals • Manufacturing • Formulation Development • Process Safety • Experimental Design (DoE)
Technical Pre-Sales • Enterprise Delivery • Stakeholder Management • C-Suite Communication • Thought Leadership • Training & Workshops
Intellegens | Cambridge, UK | May 2024 - Present
Leading agentic AI development and enterprise adoption—combining technical innovation with strategic client partnerships across pharma, chemicals, and materials.
Key Achievements:
- Architected agentic AI platform - multi-agent architectures, LangGraph, MCP integration for autonomous R&D workflows
- Led cross-functional team of ML engineers, implementing agile sprints
- Delivered technical demonstrations across pharma, chemicals, manufacturing, food, and materials sectors
- Conducted training and workshops for enterprise clients (voestalpine webinar)
- Delivered webinar "Can Agentic AI Transform Chemicals & Materials R&D?"
- Authored blog series on agentic AI for R&D
- Presented at AIChE Spring Meeting 2024 on ML applications in process safety
Technical Highlights: LangGraph • Multi-Agent Systems • RAG • MCP Protocol • Gemini/LLM Integration • Prompt Engineering • Full-Stack Development
Intellegens | Cambridge, UK | May 2023 - May 2024
Led high-impact ML consultancy for Fortune 500 clients. Built and scaled solutions for sparse, noisy industrial data.
Key Achievements:
- Collaborated with DOW on adaptive experimental design (book chapter)
- Implemented Reinforcement Learning for up to 50% reduction in hyperparameter optimization time
- Established LLM-based Q&A document search framework, improving internal data retrieval
Technical Highlights: Reinforcement Learning • LLMs • Bayesian Methods • Neural Networks
Intellegens | Cambridge, UK | September 2022 - May 2023
Developed production ML systems and pioneered explainable AI tools.
Key Achievements:
- Delivered Yili case study on food formulations optimization
- Conducted AM optimization webinar with Lawrence Livermore National Lab
- Developed edge computing algorithm reducing model size by 14,000x whilst maintaining 70% accuracy
- Innovated TensorFlow model that improved core temperature prediction accuracy by 40%
Technical Highlights: TensorFlow • Edge Computing • Explainable AI • Uncertainty Quantification
Intellegens | Cambridge, UK | July 2021 - September 2022
Early team member post-spin-out from Cambridge's Cavendish Lab. Built foundational ML solutions for enterprise clients.
Key Achievements:
- Published OCAS case study on steel PSP modeling
- Published AMRC case study on composite manufacturing optimization
- Delivered webinar with Lucideon on materials and process development
- Devised advanced automated data clustering using Bayesian methods and Kullback-Leibler divergence
Technical Highlights: Active Learning • Gaussian Processes • Bayesian Methods • Feature Engineering
University of Leicester | Leicester, UK | September 2016 - June 2021
Doctoral research sponsored by Rolls-Royce plc, applying machine learning and statistical modeling to aerospace materials challenges.
Key Achievements:
- Published 16 peer-reviewed papers (4 as lead author) in Acta Materialia, Scientific Reports, Crystals
- Co-developed DenMap algorithm for automated microstructure recognition, adopted by international groups
- Certified AFHEA through 4 years teaching data analysis and simulation
- Led residential advisor team managing student welfare (2015-2017)
Publications highlight: "On the origin of mosaicity in directionally solidified Ni-base superalloys" (Acta Materialia, 2021)
-
BAT - Pharmacokinetics modeling (paper)
-
Zizo - Pharmacokinetics modeling (paper)
-
B-Secur - Pharmacokinetics modeling (paper)
-
Equivital - Core body temperature prediction (paper)
-
DOW - Adaptive experimental design (book chapter)
-
Photocentric - 3D printing materials ML pilot (partnership)
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Ansys - Integration partnership (partnership)
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PlantSea - Sustainable materials pre-sales (case study)
-
Avery Dennison - ML pilot (LinkedIn recommendation)
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FUCHS - Lubricant formulation development (case study)
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voestalpine - Advanced materials and AM optimization (webinar)
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Yili - Food formulation optimization (case study)
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OCAS/ArcelorMittal - Steel PSP modeling (case study)
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AMRC - Composite manufacturing optimization (case study)
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Lawrence Livermore National Lab - AM process optimization (webinar)
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Lucideon - Materials development (webinar)
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CPI - Battery industrialisation (webinar)
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Rolls-Royce - Nickel-base superalloy design (PhD thesis)
Additional enterprise clients across pharma, chemicals, and manufacturing under NDA.
Recent highlights — not exhaustive.
- "Talk Freely, Execute Strictly: Schema-Gated Agentic AI for Flexible and Reproducible Scientific Workflows" - arXiv Preprint, 2026
- "Building
Trustworthy AI Agents for Science: Lessons from NOA, a schema-gated
conversational research testbed" - Intellegens Technical Paper, 2026
- "Degrees of
Uncertainty: Conformal Deep Learning for Core Body Temperature
Prediction" - Communications Engineering, 2025
- "Rapid
Residual Stress Simulation in Additive Manufacturing through Machine
Learning" - Additive Manufacturing, 2025
-
"Adaptive Experimental Design" - The Digital Transformation of
Product Formulation, 2024
- "Quantifying Benefits of Imputation
over QSAR Methods" - J. Chemical Information & Modeling,
2024
- AIChE Global
Process Safety Conference 2025 - ML in Process Safety
- AIM 2025
Conference - Federated Learning in Materials Science
- User Group
Meeting 2025 - NOA Agentic AI System Demo
- AIChE Spring
Meeting 2024 - ML for Chemicals & Materials R&D
- "Can Agentic AI
Transform Chemicals & Materials R&D?" (2025)
- "Tracking LLMs in Materials Science"
(2024)
- "Revolutionizing
Energy Storage with AI" (2023)
- Multiple formulation development and DoE webinars (2021-2024)
- Targets Up Front for More Focused Adaptive Design
- Machine Learning for Oligonucleotides
- The Benefits of Accelerators for Science
- Federated Learning for Adaptive Design
- Calibrated Uncertainty for Rehabilitation
Total Publications: 20+ peer-reviewed papers | Citations: 290+ | Active Research Profile: Ongoing collaborations
PhD in Materials Science with Machine Learning
University of Leicester | September 2016 - June 2021
-
Sponsored by Rolls-Royce plc
- Thesis: "Patterns in Directionally
Solidified Alloys" (algorithmic microstructure analysis)
- Developed
image feature recognition tool (DenMap) for automated microstructure
analysis
- 16 publications during PhD, 4 as first author
- Advanced
training: Solidification Modeling (ESI Group, Switzerland)
MEng (Mechanical) with First Class Honours
University of Leicester | September 2011 - June 2016
Professional Certifications:
- Chartered Engineer
(CEng)
- Professional Member, Institute of Materials, Minerals and
Mining (MIMMM)
- Associate Fellow of Higher Education Academy (AFHEA)
-
Essential Management Skills Certificate
- IBM Data Science
Certificate
Continental Divide Trail (2017) — Hiked 3,100 miles from Mexico to Canada along the Rocky Mountains over 6 months, raising funds for MQ Mental Health and the University of Leicester's Widening Participation scheme. One of approximately 200 annual completions. [University feature | Trail journal]