Annual procurement / business case
Context & contribution
Contributed to a GenAI negotiation intelligence platform for a global consumer goods company. Evaluation demonstrated savings potential equivalent to 2% of annual procurement spend.
AI leadership · Products · Innovation
Dr. Joyjit Chatterjee
Research depth.
Enterprise impact.
I connect AI strategy, product development and delivery to turn complex enterprise challenges into practical solutions.
Lead Data Scientist, EPAM Systems
Distinguished Visiting Fellow, Loughborough University
01 / Enterprise AI
From ambition
to application.
Shaping AI opportunities, building products and helping organisations use them. Work spanning R&D, manufacturing, procurement and supply.
Manufacturing / annual business case
Context & contribution
Up to £300k per year demonstrated in evaluation of predictive analytics for continued process verification at Reckitt.
R&D / annual business case
Context & contribution
Approximately $780k and 10,000 lab hours per year demonstrated in evaluation of AI-assisted shelf-life prediction.
Manufacturing waste reduction
Context & contribution
Contributed to waste reduction in major UK factories through data-led continuous improvement and manufacturing analytics.
Innovate UK KTP rating
Context & contribution
Certificate of Excellence for the Reckitt–University of Hull Knowledge Transfer Partnership.
Financial figures describe annual business cases assessed in evaluations. Open each figure for scope and contribution.
01Shape the opportunity
Use cases, value & feasibility
02Build the product
Models, experience & deployment
03Enable adoption
People, governance & operations
04Develop capability
Teams, mentoring & knowledge
01
Strategy & delivery · EPAM
Shaping AI opportunities into deliverable programmes
AI/ML consulting across R&D, manufacturing, procurement and supply for Fortune 500 and FTSE 250 organisations.
Direct client delivery at EPAM
Reckitt · Syngenta Group
Pre-sales and use-case discovery support
Qatar Airways · Unilever · Barry Callebaut · Brussels Airport Company · Cleveland Clinic Abu Dhabi · Adidas · Co-op · Currys · PPG Industries
My contribution
Connect use-case discovery and RFP responses with project planning, proof of value and governance. Help assemble delivery teams, mentor data scientists and align senior stakeholders and domain experts.
Value & outcomes
Contribute to multi-million-pound engagements across Europe and North America, including generative and agentic AI.
Explore clients, projects & responsibilities4 topics
Client delivery and opportunity development
- Direct client delivery projects for Reckitt and Syngenta Group.
- Supported the EPAM team with pitching and identifying ML and GenAI use cases for Qatar Airways, Unilever, Barry Callebaut, Brussels Airport Company, Cleveland Clinic Abu Dhabi, Adidas, Co-op, Currys and PPG Industries.
- Supported pre-sales through solution pitches, RFP responses for new and existing accounts, and project planning.
AI strategy, products and delivery
- Lead AI/ML solution development across R&D, manufacturing, procurement and supply services for Fortune 500 and FTSE 250 organisations within the UK and Western Europe AI/ML Consulting team.
- Contribute to multi-million-pound data science engagements across Europe and North America, working with cross-functional global teams, client senior leadership and subject-matter experts.
- Identify suitable business use cases, data streams, modelling approaches and governance strategies for decision support, cost efficiency and speed to market.
- Work across strategy and governance, proof of concept, proof of value and end-to-end AI consulting, including GenAI engineering, data analytics and data science.
Teams and knowledge sharing
- Conduct technical and project interviews to help hire and assemble business analysts, data scientists and data engineers for client projects.
- Mentor data scientists and senior data scientists.
- Author articles for EPAM’s Supply Chain Management community, co-organise educational AI workshops for clients and review editorial content for the GenAI-X community.
Technology and implementation
- LLMs, retrieval-augmented generation (RAG), agentic AI, LangChain, PhiData, CrewAI and Azure OpenAI Service.
- Python, Retool, Postman, pgAdmin and APIs for end-to-end AI/ML and GenAI solutions.
02
GenAI / Procurement
Negotiation intelligence at enterprise scale
A GenAI platform for a global consumer goods company, supporting procurement negotiations.
My contribution
Contributed to the negotiation intelligence platform, connecting generative AI with a high-value enterprise decision process.
Value & outcomes
Business case equivalent to 2% of annual procurement spend.
Business-case figures reflect evaluation-based opportunities. Scope and assumptions are in the project details.
Explore the full work1 topic
Contribution and evaluated value
- Worked on a GenAI negotiation intelligence platform supporting procurement negotiations.
- Evaluation demonstrated savings potential equivalent to 2% of the company’s annual procurement spend. This represents potential benefits demonstrated in evaluation, not realised savings.
03
AI product development · Reckitt × Hull
From laboratory research to a production application
Shelf-life prediction for healthcare products, developed through an Innovate UK Knowledge Transfer Partnership.
My contribution
Led the AI workstream across models, interfaces and deployment, collaborating with R&D scientists, engineers and UI/UX specialists. Supported uptake through leadership engagement and skills transfer.
Value & outcomes
Outstanding KTP rating for the $200k jointly funded project. Annual business case: $780k in testing costs and 10,000 laboratory hours.
Business-case figures reflect evaluation-based opportunities. Scope and assumptions are in the project details.
Explore the full work4 topics
Partnership and recognised delivery
- Led the AI workstream in a $200k jointly funded Knowledge Transfer Partnership between Reckitt and the University of Hull, supported by Innovate UK and UKRI.
- The partnership received Innovate UK’s Certificate of Excellence with an Outstanding rating, the highest possible grade.
From research to a usable AI product
- Developed an AI application for decision support in shelf-life prediction of healthcare products, estimating active-ingredient overage early in development.
- Worked from model development through production application development, including accessible interfaces and user experience, collaborating with Reckitt’s Global Data Science team on cloud deployment.
- Combined laboratory data with chemistry knowledge to improve stability prediction and formulation optimisation, including limited-data settings, for pharmaceutical and nutraceutical products.
- Collaborated with R&D scientists, ML engineers, data scientists and UI/UX developers across North America and Europe to plan development and meet milestones and deliverables.
Evaluation and resource efficiency
- Evaluation demonstrated potential annual reductions of approximately $780k in stability-testing costs and 10,000 laboratory hours, with potential energy savings of more than 2,000 kWh per year.
- Helped reduce raw-material waste by predicting early which new formulations were likely to fail intended shelf-life specifications.
- Coauthored a poster accepted for Reckitt’s first Science Inside Symposium, organised by the Chief R&D Officer in Hull.
AI adoption and longer-term strategy
- Helped shape a long-term plan for intelligent data analysis in product design and testing, translating research into commercially useful corporate applications.
- Investigated explainable AI components to make predictions transparent and build understanding of the domain.
- Supported AI awareness and uptake through TechTalks with senior leadership including the CIO, presentations to the SVP IT&D R&D, and cohosting AI forums for the IT&D R&D group.
- Developed colleagues’ data and AI capabilities through learning sessions, specialist workshops and regular discussion.
04
Operations & adoption · Reckitt
Making manufacturing data useful for decisions
Predictive and causal analytics for process verification, quality and operational planning.
Supporting a multi-billion-pound portfolio
Nurofen · Strepsils · Airborne
My contribution
Connected manufacturing, quality and process data; supported causal AI adoption across factories; developed logistics and capacity-planning tools and engaged quality and IT leadership.
Value & outcomes
Contributed to approximately 30% waste reduction in major UK factories. Annual business case for predictive analytics: up to £300k.
Business-case figures reflect evaluation-based opportunities. Scope and assumptions are in the project details.
Explore the full work5 topics
Business scope and cross-functional delivery
- Worked with IT&D, R&D, Supply and Global Data Science teams across the UK, USA, India and Poland on pharmaceutical and nutraceutical brands including Nurofen, Strepsils and Airborne, supporting a multi-billion-pound portfolio.
- Presented AI innovation outcomes to the SVP Quality and SVP IT&D Supply, and engaged the CIO and Global Data Science team through Reckitt’s AI/ML Community of Practice.
Manufacturing quality, waste and operational performance
- Developed a scalable data model for Continued Process Verification (CPV), covering formulation and packaging, manufacturing stages, input raw-material attributes and finished-product outputs.
- Integrated SAP, environmental management, quality-control and historian process-parameter data with input from subject-matter experts across Europe and North America.
- Performed exploratory analysis, preprocessing, statistical analysis, nonlinear predictive modelling, root-cause analysis and causal inference. Evaluation demonstrated savings potential of up to £300k per year.
- Contributed to approximately 30% waste reduction in major UK factories and to the adoption of data-led continuous improvement in manufacturing and quality control.
- Targeted the availability, quality and performance components of Overall Equipment Effectiveness through predictive maintenance, CPV, predictive stability and real-time insights, with an emphasis on reducing raw-material and packaging waste.
Operational tools and accessible insights
- Used open-source LLMs through Ollama and LangChain to turn complex manufacturing analytics into explanations accessible to subject-matter experts.
- Built models for Agile team capacity and resource planning using historical Program Increment data, user stories and feature counts.
- Developed a Cost-to-Serve logistics tool to identify shipment consolidation opportunities and convert Less than Truck Load (LTL) into Full Truck Load (FTL).
Adoption, proof of value and connected initiatives
- Led the IT&D contribution to adopting a causal-AI manufacturing analytics platform, supporting factory proof-of-value demonstrations, data transformations and strategic engagement with subject-matter experts.
- Expanded predictive stability analysis by connecting Ongoing Stability Studies data from SAP and QC Supply with the existing R&D model built using LIMS data.
- Initiated a predictive-maintenance proof of concept using factory condition-monitoring data.
- Supported manufacturing colleagues in encouraging augmented- and virtual-reality adoption for predictive maintenance and training operations and maintenance personnel.
Industry forums, responsible AI and mentoring
- Represented Reckitt at the FMCG CQO Roundtable alongside quality leaders from Unilever, ELC Europe, Sanofi, Haleon, Galderma and Kenvue.
- Joined the EthonAI expert roundtable “From Statistics to Causal AI” with industry leaders from Bosch, Lindt, Infineon Technologies and SFS Group.
- Presented at internal forums including the Global QC Excellence Forum and delivered talks in Global QC workshops.
- Contributed case studies for Responsible AI training, educated supply-chain colleagues through workshops, and mentored graduates and interns while delegating appropriate tasks.
AI strategy & value discoveryAI product developmentEnterprise delivery & adoptionTeams & stakeholder alignmentAgentic & generative AIExplainable AI & knowledge graphs
Full experience & career history →02 / Recognition & contribution
Recognised across
industry and research.
International recognition, invited academic service and contribution to the wider AI community.
Enterprise leadership
British Data Awards 2026
Finalist: Data Leader of the Year (Partner).
View details ↗Independent recognition
Forbes 30 Under 30 Europe
Manufacturing & Industry, 2022. Recognition for AI work in manufacturing and energy.
View details ↗Academic judgement
ETH Zurich
Invited expert on a Doctoral Examination (Aptitude Colloquium) committee.
View details ↗Research into impact
Loughborough University
Distinguished Visiting Fellow, contributing to research embedding and industry impact.
View details ↗Innovation evaluation
European Commission programme
External evaluator and reviewer for Horizon Europe’s NGI Search project, 2023.
View details ↗Sustainability research
Green Talents
One of 25 international awardees selected by Germany’s Federal Ministry of Education and Research in 2021.
View details ↗AI & leadership credentials
- Claude Certified Architect (Foundations)Anthropic · Aug 2026
- OpenAI Consultative Solutions PractitionerOpenAI · Aug 2026
- Professional Agile Leadership (PAL-1)Scrum.org · Dec 2025
- Google Cloud Generative AI LeaderGoogle Cloud · Jul 2025
Business, product & leadership development
Cambridge business CPD · Oxford AI Programme · Professional Agile Leadership · AI for Product Management
03 / In the public conversation
Watch. Listen.
Read a little deeper.
Recorded talks, interviews, published perspectives and profiles. Explore the work in my own words and through the organisations that feature it.
Explore ↗Recognition · Forbes
Forbes 30 Under 30 Europe
2022
Recognised in Manufacturing & Industry for AI work in manufacturing and energy. Photo: at the 2026 Under 30 Summit in Phoenix.
Read the Forbes profile ↗
▶ WatchPodcast · Low to Grow
Explainable AI and the Power of Quiet Thinking
Nov 2025
A conversation with Wenmiao Yu on explainable AI, practical enterprise adoption and reflective leadership.
Listen to the episode ↗
▶ WatchRecorded talk · Hull / Alan Turing Institute
From doctoral research to industry AI
Recording published Dec 2024
Sharing my career journey and perspective on working in data science and AI, at the University of Hull.
Watch the talk ↗
▶ WatchRecorded presentation · IEA Wind Task 43
Interactive decision support for wind turbines
11 Jun 2025
Research presentation on maintenance decision support, alongside participation in the meeting’s generative AI panel.
Watch the presentation ↗Interview · IEEE Spectrum
AI’s Benefit to Solar and Wind Power Isn’t Hot Air
Jun 2022
Contributing a research perspective on trust, data and the practical use of AI in renewable energy.
Read the interview ↗Coauthored perspective · World Economic Forum
Who gets to benefit from AI?
Apr 2022
With Nina Dethlefs, on the unequal global adoption of AI. Originally published by The Conversation and republished by the World Economic Forum.
Read the article ↗Profile · Education Times
Using AI to tackle the climatic challenges
Jul 2021
A profile of my research in applying AI to energy and climate challenges.
Read the profile ↗Research film · Green Talents
Explainable AI for a sustainable future
2021
My research introduction for the German government’s Green Talents award, on trustworthy AI for wind energy.
Watch the introduction ↗Research poster · WindEurope
Knowledge graphs for wind-energy operations
2026
Coauthored research for WindEurope 2026. The poster was presented by collaborator Idris Alugo, as credited by the Loughborough research group.
Read the research poster ↗04 / Research & authorship
From new ideas
to shared knowledge.
Research with reach
Ideas others
build on.
Explainable AI, industrial decision support and the energy transition.
Explore Google Scholar ↗Snapshot: 3 November 2026. *2026 is a partial year.
Explore selected cited research
- This new conversational AI model can be your friend, philosopher, and guide, and even your worst enemy376 citations · Patterns
- Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future198 citations · Renewable and Sustainable Energy Reviews
- Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines90 citations · Wind Energy
Google Scholar citation counts, observed 3 November 2026.
More reach & metric definitions
40,151 ResearchGate reads ↗, observed 3 November 2026. Reads include views of publication summaries, figures and full texts or downloads, not unique readers.
The h-index is the number of papers with at least that many citations. The i10-index counts papers with at least ten citations. Platforms have different coverage; their figures are not combined.
Co-editor with Nina Dethlefs · Wiley · 2025
Renewable Energy Transition with Artificial Intelligence
Challenge-driven Solutions
Bringing academic and industry perspectives together on AI for the energy transition. I co-edited the volume and coauthored its opening chapter on operational, engineering and socioeconomic adoption challenges.
Explore at Wiley ↗
Latest paper · GLOW at ISWC 2026Read the full paper ↗conference · Oct 2026
Graph-Grounded Multimodal Agent for Trustworthy Power-Line Operations and Maintenance
GLOW workshop at ISWC, Bari, Italy
Read full details1 topic
Presentation and publication context
- Presented as a talk at the GLOW workshop at ISWC 2026, Bari.
conference · May 2026
Structuring the Last Mile with ReActV: Tool-Augmented Delivery Planning with Verification
ABIS workshop at ACM Web Science 2026; ACM Web Science Conference Companion
05 / In the room
Ideas shared.
Conversations continued.
From university lecture halls and research workshops to industry panels and international forums. Select a photograph to take a closer look.
View photo ↗25 Oct 2026
Knowledge graphs for power-line inspection
Presenting research on a graph-grounded multimodal agent for trustworthy power-line operations and maintenance at the GLOW workshop, ISWC 2026, Bari.
Original post / source ↗View photo ↗Apr 2026
Part of the Forbes Under 30 community
At the Forbes Under 30 Summit in Phoenix, Arizona, as a Forbes 30 Under 30 Europe lister.
Original post / source ↗
View photo ↗5 Mar 2026
Trustworthy AI starts with domain knowledge
A guest lecture at Loughborough University on knowledge representation and reasoning for safety-critical engineering.
Original post / source ↗
View photo ↗19 Oct 2026
AI, mobility and public trust
An invited guest at a House of Lords evidence session on the legal and ethical frameworks for autonomous vehicle technology.
Original post / source ↗
View photo ↗Nov 2025
GenAI meets the wind industry
An invited talk for Queen Mary University of London on generative AI, knowledge graphs and Wind Task 43, at the London City Institute of Technology campus.
Original post / source ↗View photo ↗11 Jun 2025
Generative AI and the future of wind energy
A panel discussion at the IEA Wind Task 43 Annual General Meeting in Golden, Colorado, alongside participants from Microsoft, NREL, Siemens and OST. Photograph: IEA Wind Task 43.
Original post / source ↗Let’s talk about useful AI.
Enterprise adoption, trustworthy systems, industrial applications and the journey from research to delivery.