Enterprise AI · Strategy · Products · Leadership

Dr. Joyjit Chatterjee

Leading AI from
strategy to
enterprise value.

I lead AI solution development for global enterprises, bringing together business strategy, product thinking and research depth. My work spans R&D, manufacturing and procurement, with senior stakeholder engagement across Europe and North America.

Lead Data Scientist, EPAM Systems
Distinguished Visiting Fellow, Loughborough University

Joyjit standing beside the Forbes Under 30 Summit backdrop in Phoenix.View photograph ↗

Forbes 30 Under 30 Europe

Manufacturing
& Industry.

At the Forbes Under 30 Summit, Phoenix, 2026.

Explore recognition & contributions →
▶In conversationExplainable AI and the power of quiet thinking

Executive engagement & industry dialogue

AI in the conversations
that shape business.

International panels & talks ↓

Executive presentations & knowledge exchange

CIO & SVP engagement

Presented AI innovation outcomes to SVP leaders across quality, supply and R&D, and engaged the CIO through global AI forums and TechTalks at Reckitt.

Explore the context →

Invited panellist · 2024

CXO Group roundtable

Discussed next-generation AI products alongside industry leaders from Microsoft and Dell.

Explore the context →

Speaker · 2024

FMCG CQO roundtable

Presented AI for process verification to senior quality leaders from Unilever, ELC Europe, Sanofi, Haleon, Galderma and Kenvue.

Explore the context →

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.

Financial business cases reflect opportunities assessed in evaluations. Explore each case for contribution and supporting evidence.

Strategy & delivery · EPAM

Multi-million £AI engagements across Europe and North America

Enterprise AI strategy & delivery

AI/ML consulting across R&D, manufacturing, procurement and supply for Fortune 500 and FTSE 250 organisations.

Contribute to multi-million-pound engagements across Europe and North America, including generative and agentic AI.

Contribution & evidence

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.

  • Strategy & value discovery
  • Product development
  • Adoption & governance

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

Full responsibilities & project detail4 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.
Full career record →Experience & responsibilities ↗

GenAI / Procurement

2%of annual procurement spend: evaluated business case

GenAI negotiation intelligence

Game theory and conversational role-play simulations applied to enterprise procurement negotiations.

Business case equivalent to 2% of annual procurement spend.

Contribution & evidence

Worked with buyers and category managers, senior IT product owners and platform team stakeholders on a GenAI negotiation intelligence platform.

  • Game theory
  • Conversational role-play
  • Buyer & category engagement

Commercial and technology stakeholders

Buyers · Category managers · Senior IT product owners · Platform teams

Full responsibilities & project detail2 topics

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.

Product approach and stakeholder engagement

  • Used game theory and conversational role-play simulations within the negotiation intelligence platform.
  • Engaged buyers and category managers, senior IT product owners and platform team stakeholders.
Full career record →Project background ↗

AI product development · Reckitt × Hull

OutstandingThe highest Innovate UK KTP grade

AI-led R&D, from research to adoption

Turning AI research into a production application for healthcare product development, with cross-functional delivery and business adoption.

The Reckitt–Hull partnership received the highest KTP grade, Outstanding. Annual business case: $780k in testing costs and 10,000 laboratory hours.

Contribution & evidence

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.

  • Research
  • Production application
  • Business adoption
Full responsibilities & project detail4 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.
Presenting the Reckitt–Hull shelf-life prediction application at the University of Hull. The slide reports the scale of the research data and evaluation-based benefits.View presentation photograph ↗
Presenting the Reckitt–Hull shelf-life prediction application at the University of Hull. The slide reports the scale of the research data and evaluation-based benefits.
Full career record →University of Hull partnership story ↗

Operations & adoption · Reckitt

~30%Waste-reduction contribution in major UK factories

Manufacturing intelligence

Predictive and causal analytics for process verification, quality and operational planning.

Contributed to approximately 30% waste reduction in major UK factories. Annual business case for predictive analytics: up to £300k.

Manufacturing AI paper previewRelated paper · HAL preprintTrustworthy AI in factories · Read PDF ↗
Contribution & evidence

Connected manufacturing, quality and process data; supported causal AI adoption across factories; developed logistics and capacity-planning tools and engaged quality and IT leadership.

  • Process intelligence
  • Quality decisions
  • Operational improvement

Supporting a multi-billion-pound portfolio

Nurofen · Strepsils · Airborne

How Multimodal Data Can Enable Scalable and Trustworthy AI in Factories of The Future

Coauthored at Reckitt, this perspective proposes a shared data foundation across R&D, production, quality and supply chains. It connects equipment effectiveness and operational decisions with explainable AI, domain expertise and human oversight.

Download PDFAuthors & publication details →
Full responsibilities & project detail6 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.

Research contribution: trustworthy AI for manufacturing

  • Coauthored “How Multimodal Data Can Enable Scalable and Trustworthy AI in Factories of The Future” with Rajendra Shankaran and Nina Dethlefs, published as a HAL preprint in September 2024. The paper lists Reckitt affiliations for both industry coauthors and the University of Hull for Dethlefs.
  • Proposed a holistic manufacturing data model connecting R&D, production, quality and logistics to support equipment effectiveness, process verification, predictive stability and cost-to-serve decisions. The perspective emphasises domain-expert validation, explainability and human oversight.
Full career record →Experience & responsibilities ↗
Full experience & career history →

Stakeholder perspectives

Trusted to deliver.
Respected as a collaborator.

Anonymised summaries of feedback shared by senior stakeholders and collaborators. Individual perspectives, with names, client identities and project details omitted.

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 ↗
Joyjit Chatterjee standing in front of the British Data Awards 2026 backdrop.Enlarge image ↗

2026

British Data Awards 2026

At the British Data Awards 2026, as a finalist for Data Leader of the Year (Partner).

The virtual Green Talents award ceremony with Parliamentary State Secretary Michael Meister. Joyjit appears remotely on screen.Enlarge image ↗

2021

Green Talents: international recognition for sustainability research

The virtual Green Talents award ceremony with Parliamentary State Secretary Michael Meister. Joyjit appears remotely on screen. Image credit: BMBF / Hans-Joachim Rickel.

Receiving the University of Hull’s Best International Knowledge Exchange Activity award for KTP activity.Enlarge image ↗

2023

Research recognised for international knowledge exchange

Receiving the University of Hull’s Best International Knowledge Exchange Activity award for KTP activity.

Certificate of Excellence for the Reckitt–University of Hull KTP, graded Outstanding. Shared February 2024.View certificate ↗

Reckitt × University of Hull

Outstanding.
The highest KTP grade.

The Knowledge Transfer Partnership received Innovate UK’s Certificate of Excellence with the highest grade, Outstanding. My work connected AI research with practical R&D and manufacturing challenges at Reckitt.

Project completed in 2023. Certificate shared in February 2024.

View the recognition ↗
Explore the full recognition record: awards, citations & academic distinctions

A wider record of recognition.

  1. British Data Awards 2026 card naming Dr. Joyjit Chatterjee as a Data Leader of the Year (Partner) finalist.View award ↗
    2026

    British Data Awards: Data Leader of the Year (Partner) Finalist

    Named a finalist in the Data Leader of the Year (Partner) category.

    Recognition details →
  2. University of Hull Knowledge Exchange Awards 2023: winner, Best International KE Activity, for KTP activity.View award ↗
    Jun 2023

    Best International Knowledge Exchange Activity

    University of Hull award for global collaborations and impact in the KTP project

    Recognition details →
  3. Wiley recognition for Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines, published in Wind Energy.View award ↗
    Mar 2022

    Top-Cited Author

    Wiley Top-Cited Article recognition for 2020–2021 in the Wind Energy journal.

    Recognition details →
  4. Jan 2022

    UKRI Global Talent Endorsement

    Endorsed as Global Talent by UK Research and Innovation (UKRI).

    Recognition details →
  5. Amity Alumni Achiever Award for Outstanding Contribution in Education, presented at the Virtual Alumni Meet 2021.View award ↗
    Mar 2021

    Alumni Achiever Award

    Awarded by Amity University for Outstanding Contribution in Education.

    Recognition details →
  6. Amity Young Researcher Award plaque from the Amity–IEEE UK and Ireland international conference in London, 23–25 April 2019.View award ↗
    Apr 2019

    Young Researcher Award

    Amity Young Researcher Award, recognising early-career research contributions.

    Recognition details →
  7. Gold medal for first in academics, B.Tech Electronics and Communication Engineering, Amity University, 2014–2018 cohort.View award ↗
    2018

    Gold Medal & University Topper

    Gold medallist and first in the B.Tech Electronics & Communication Engineering programme at Amity University, with 9.68/10 CGPA.

    Recognition details →
  8. Amity University award for the best in human and traditional values, B.Tech Electronics and Communication Engineering, 2014–2018 cohort.View award ↗
    May 2018

    Shri Baljit Shastri Award

    Most coveted award of Amity University for Best in Human and Traditional Values

    Recognition details →
All awards & recognition →

Business, product & leadership development
Cambridge business CPD · Oxford AI Programme · Professional Agile Leadership · AI for Product Management

Courses & professional development →

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.

Joyjit standing beside the Forbes Under 30 Summit backdrop in Phoenix.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 ↗
Sharing AI shelf-life prediction research at the Hull KTP celebration, Aura Innovation Centre, March 2023.Explore ↗

Alumni feature · University of Hull

From a Hull PhD to enterprise AI leadership

Apr 2025

The university highlights my doctoral research, highly cited publications, Forbes recognition and journey through KTP work to EPAM. Photograph: presenting the KTP project in March 2023.

Read Hull’s feature ↗
Joyjit delivering a careers talk at the University of Hull, with an Alan Turing Institute and DAIM event banner.▶ Watch

Recorded 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 ↗
Newspaper feature titled Using AI to tackle the climatic challenges, with a portrait of Joyjit Chatterjee.Explore ↗

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 ↗
More press & media →

04 / Research & authorship

From new ideas
to shared knowledge.

All publications & PDFs →

Research with reach

Ideas others
build on.

Explainable AI, industrial decision support and the energy transition.

Explore Google Scholar ↗
Citations by year Google Scholar
62019
272020
392021
662022
1742023
2542024
2302025
1542026*

Snapshot: 3 November 2026. *2026 is a partial year.

Explore selected cited research
  1. This new conversational AI model can be your friend, philosopher, and guide, and even your worst enemy376 citations · Patterns
  2. Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future198 citations · Renewable and Sustainable Energy Reviews
  3. 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.

Wiley cover of Renewable Energy Transition with Artificial Intelligence, edited by Nina Dethlefs and Joyjit Chatterjee.

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 ↗
First page of the graph-grounded multimodal agent paperLatest 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

Verma, S., Chatterjee, J., Guo, J., Marar, A., Shankaran, R., Sharma, G., Guo, Z., Mehra, A.

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

Chatterjee, J., Gamtenadze, D., Marar, A., Agarwal, P.

05 / In the room

A voice in enterprise AI.
A contributor to its future.

Invited panels, executive roundtables and international talks connecting AI products, industrial operations and trustworthy innovation.

Oct 2024

Panel: Next Gen AI Products

CXO Group Roundtable Discussion (with Microsoft and Dell)

Event context & participants1 topic

Panel context

  • Invited panellist at the CXO Group roundtable alongside industry leaders from Microsoft and Dell.
Full event record →

2024

Panel: EthonAI Expert Roundtable "From Statistics to Causal AI"

With Bosch, Lindt, Infineon Technologies, SFS Group etc.

Event context & participants1 topic

Panel context

  • Invited panellist alongside industry leaders from Bosch, Lindt, Infineon Technologies and SFS Group.
Full event record →

2024

AI for Continued Process Verification at Reckitt

FMCG CQO Roundtable (Unilever, Sanofi, Haleon, Galderma, Kenvue etc.)

Event context & participants1 topic

Audience

  • Delivered a talk at the FMCG CQO Roundtable to quality leaders from Unilever, ELC Europe, Sanofi, Haleon, Galderma and Kenvue.
Full event record →

11 Jun 2025

Panel: The opportunities and challenges of generative AI in wind energy

IEA Wind Task 43 AGM + Technical Expert Meeting, Golden, Colorado, USA

Event context & participants1 topic

Organiser report and photograph

  • The IEA Wind Task 43 organiser report identifies Joyjit as a panel participant alongside representatives from Microsoft, NREL, Siemens and OST.
Full event record →

Apr 2020

Transparent, Accurate and Scalable AI for Intelligent Decision Support in O&M of Wind Turbines

Carnegie Mellon University (CMU) Symposium on AI and Social Good

Full event record →

Apr 2024

"AI for Predictive Stability" and "AI for Continued Process Verification"

Global QC Excellence Forum at Reckitt

Event context & participants1 topic

Audience

  • Presented to Reckitt global QC/QA teams, including the SVP and Global Head of Quality, at the Global QC Excellence Forum.
Full event record →

Let’s talk about useful AI.

Enterprise adoption, trustworthy systems, industrial applications and the journey from research to delivery.

Speaking & collaboration ↗
All talks & appearances →

Open original ↗