Curriculum Vitae

Note

This is also available as a PDF, or on LinkedIn. My public work is available on GitHub or in the Projects section of this site.

Professional Summary

Passionate and curious interdisciplinary AI researcher and technical leader motivated by delivering real things out of impossible ideas. Drawing on a Ph.D. in research methods and approximately 35 publications across six fields.

My employment history has exposed me to a broad range of industries and academic fields, and a variety of statistical, numeric, and machine learning approaches.  I have experience leading interdisciplinary teams in creating novel software solutions to problems in business and research, have academic publications and patents in a variety of fields.  I have worked in various environments from small startups to large foreign enterprises.

Hire me if you want novelty, someone who can manage people smarter than himself, and a pragmatic approach to solving problems

Personal Details

Location: East Yorkshire, UK.

Please see the contact section for details on how to contact me.

Skills

AI Strategy & Leadership

  • Executive-level Technical Communication & Strategy
  • Interdisciplinary Team Leadership & Management
  • R&D Pipeline Management & Internal Innovation
  • Agile Development

Advanced Machine Learning & Modeling

  • Foundation Models & Behavioural Sequence Modeling
  • Time-Series Forecasting & Market Analysis
  • NLP & Word Sense Disambiguation
  • Agent-Based Modeling

Statistics & Research Methods

  • Applied Statistics & Experimental Design
  • Scientific Computing
  • Mixed-Integer Linear Programming & Economic Optimisation
  • Academic Research & Interdisciplinary Collaboration

Languages & Engineering

  • Python, R, Ruby
  • Large-scale Data Systems & Cloud Infrastructure
  • Platforms & Tools: Linux/UNIX, Git, Make, CMake

Relevant Employment

Kraken Technologies (formerly Upside Energy) (Aug 2016–Present)

  • Head of Behavioural Insight (Kraken Customer): Started the applied AI research team focused on behavioural sequence modelling and energy data systems. Directed the development of a proprietary foundation model for user behaviour, translating industry analysis into metrics for the KX team.
  • Internal R&D Lead (NeXt): Pitched and led an internal R&D initiative with a small team, pushing multiple projects to production including automated trading tools, AI asset optimisation explanations, and physically-informed grid optimisation. Delivered multiple PoCs into live product road maps.
  • Lead Data Scientist & DS Guild Leader (Kraken Flex): Defined the data science career ladder, acted as Guild Leader, and hired all data scientists until approximately 2023. Designed and developed energy trading tools. Worked with multi-billion-pound international clients on early business cases and project plans for business transformation. Developed commercial quoting tools using conventional operational research toolkit including stochastic mixed-integer linear programming and time-series forecasting.
  • Head of Data Science (Upside Energy): Hired and managed an initial team of data scientists. Developed the core optimiser algorithms and defined a low-level network protocol that remains in active use today.

W&P Academic Consultancy Ltd. (2016–2022)

  • Director/Co-founder: Manage and oversee the implementation of interdisciplinary projects focused on intelligence analysis and policymaking for government/security clients.
  • Developed agent-based models for the COVID-19 pandemic to inform the Luxembourg government’s response.

Lancaster University (2009–2016)

  • Lecturer (Digital Humanities), CASS (Oct. 2015–2016): Research into methods and applications of computational approaches to humanities.
  • Research Associate, NLID project, Security Lancaster (Oct. 2015–2016): Design and implementation of linguistic toolchains and analytical models.
  • Research Associate, SAMUELS project (Oct. 2014–Apr. 2015): Design and implementation of large-scale historical word-sense-disambiguation NLP toolchain.
  • Research Associate, CASS (Oct. 2014–Apr. 2015): Development of linguistic analysis tools.
  • Senior Research Associate, CASS (2013–2014): Design and implementation of ‘big data’ corpus construction & analysis tools.
  • Research Assistant, School of Computing and Communications (2013–2014): Development of NLP toolchain components; crowdsourced data acquisition & web scraping.
  • Teaching Assistant, School of Computing and Communications (2009–2016): Modules included Advanced Programming, Fundamentals of Computer Science, Languages & Compilation, Web Technologies, Operating Systems, Computer Networks.

Consultant, Momote ltd. (May–Oct 2008)

  • Development of web-based vehicle tracking software.

Education

Lancaster University, Ph.D — "Technological Advances in Corpus Sampling Methodology" 2010–2015

Lancaster University, MRes, Applied Social Statistics — "Folksonomies as Document Summary Engines" 2009–2010

Lancaster University, BSc (Hons), Computer Science Innovation — “Adapting Speculative Execution for High-level Distributed Processing” 2006–2009

Patents

Co-authored multiple patents relating to optimiser technology, energy data systems, and applied machine learning architectures developed during tenure at Kraken Technologies.

Publications

My work in research methods has led me to be a useful second author :-) I have published in multiple fields including epidemiology, NLP, cyber-security, environmental toxicology, AI, and energy.

For a full and up-to-date list, please view my Google Scholar Profile.

  • Antonopoulos, I., et al. “Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review,” Renewable and Sustainable Energy Reviews (2020).
  • Brezina, V., McEnery, T., Wattam, S. “Collocations in context: A new perspective on collocation networks,” International journal of corpus linguistics (2015).
  • Demmen, J., et al. “A computer-assisted study of the use of violence metaphors for cancer and end of life by patients, family carers and health professionals,” International Journal of Corpus Linguistics (2015).
  • Thompson, J., Wattam, S. “Estimating the impact of interventions against COVID-19: From lockdown to vaccination,” PloS one (2021).
  • Piao, S., et al. “A time-sensitive historical thesaurus-based semantic tagger for deep semantic annotation,” Computer Speech & Language (2017).
  • Whaley, P., et al. “Knowledge organization systems for systematic chemical assessments,” Environmental health perspectives (2020).
  • Alexander, J., Hardy, J., Wattam, S. “Characterising the physicality of everyday buttons,” Proceedings of the Ninth ACM International Conference on Interactive (2014).
  • Rayson, P.E., et al. “Towards interactive multidimensional visualisations for corpus linguistics,” Journal for language technology and computational linguistics (2017).
  • Bor, M.C., et al. “Adversarial machine learning in smart energy systems,” Proceedings of the Tenth ACM International Conference on Future Energy (2019).
  • Edwards, M., et al. “Sampling labelled profile data for identity resolution,” 2016 IEEE International Conference on Big Data (2016).
  • Whaley, P., et al. “Identifying assessment criteria for in vitro studies: a method and item bank,” Toxicological Sciences (2024).
  • Wattam, S., et al. “Experiences with parallelisation of an existing NLP pipeline: Tagging Hansard,” Proceedings of the Ninth International Conference on Language Resources… (2014).
  • Rayson, P., et al. “Large-scale time-sensitive semantic analysis of historical corpora,” Proceedings of the 36th Meeting of ICAME (2015).
  • Wattam, S.M. “Technological advances in corpus sampling methodology,” PQDT-Global (2015).
  • El-Haj, M., et al. “Creating and validating multilingual semantic representations for six languages: expert versus non-expert crowds,” Proceedings of the 1st Workshop on Sense, Concept and Entity Representations (2017).
  • Whaley, P., et al. “Using bench protocol platforms to improve compliance with systematic review guidance documents and reporting checklists: Proof of concept,” Evidence-Based Toxicology (2023).
  • Culpeper, J., et al. “Encyclopaedia of Shakespeare’s language,” (2021).
  • Alexander, M., et al. “Semantic tagging and Early Modern collocates,” Corpus Linguistics 2015 (2015).
  • Wattam, S., Rayson, P., Berridge, D. “Using life-logging to re-imagine representativeness in corpus design,” Corpus Linguistics 2013 abstract book (2013).
  • Whaley, P., et al. “Reconciling chemical flame retardant exposure and fire risk in domestic furniture,” PLoS one (2023).
  • Elizondo, S., et al. “A Smart Contracting Framework for Aggregators of Demand-Side Response,” AIM (2019).
  • Vidler, J., Wattam, S. “Keeping Properties with the Data CL-MetaHeaders-An Open Specification,” Proceedings of the Workshop on Challenges in the Management of Large Corpora… (2017).
  • Wattam, S., Rayson, P., Berridge, D. “Document Attrition in Web Corpora: an Exploration,” Proceedings of the Eighth International Conference on Language Resources… (2012).
  • Thompson, J., Wattam, S. “Lockdowns and Selection Pressure: A Modelling Study,” medRxiv (2023).
  • Whaley, P., Wattam, S. “Standards-Compliant General Protocol for Systematic Reviews,” (2022).
  • Wattam, S. “Trouble in Paradise: The flaws in Ubicomp’s practicalities,” (2009).

Teaching/Talks

  • S. Wattam, A. Moore, P. Rayson, “Web Scraping”, UCREL Summer School lectures and practicals.
  • S. Wattam & J. Vidler, “Automata in the Real World”, Maze solving using state machines: tools and practical tasks.
  • S. Wattam, "Version Control and Project Management at UCREL", Internal training documentation and talk.
  • S. Wattam, C. Ellis & contributors, "Maize", Maze generation and algorithmics.
  • S. Wattam & R. Larson, “Server Compromise Case Study”, Guest MSci lecture analysing an SSH break-in.
  • S. Wattam & C. Ellis, Computing Society Lectures, Topics: AI, Security.