Dan Ley

Dan Ley

PhD Student

Harvard University


Currently, I’m a PhD student at Harvard, supervised by Hima Lakkaraju, researching post-hoc explanations in AI. I previously worked within JPMorgan AI Research under the direction of Daniele Magazzeni and Saumitra Mishra, where I researched new global counterfactual explanations methods and their impact in assessing model fairness.

I’m a graduate of the Cambridge MEng, where I was supervised by Adrian Weller and Umang Bhatt. My research centered around providing meaningful explanations for uncertainty estimates within deep learning, as part of the broader field of explainable AI.

Outside of work I’ve been a regular footballer for the University of Cambridge, and coached the Corpus Christi College team. I currently play for MIT FC in the BSSL.

Download my CV for further details.

  • Explainable AI
  • Algorithmic Recourse
  • Deep Learning
  • MEng in Explainable AI, 2021

    University of Cambridge

  • BA in Computer Engineering, 2020

    University of Cambridge


JPMorgan Chase & Co
AI Research Scientist Intern
Oct 2021 – Present Canary Wharf, London, UK (Work From Home Hybrid)
  • Explainable AI research on global counterfactual explanations, implementing a state-of-the-art (NeurIPS) method and identifying inefficiencies, proposing a modified method that executes 8 times faster when achieving the same level of performance
University of Cambridge
Research Assistant
Jun 2020 – Sep 2020 Cambridge, Cambridgeshire, UK (Work From Home)
  • Continuation of MEng research on explaining uncertainty in deep learning
  • Training models in PyTorch for generation of counterfactual explanations
  • Exploring the notion of a distribution over counterfactual explanations for a single input
  • Finalising AAAI'22 submission
JPMorgan Chase & Co
Software Engineer Intern
Jul 2020 – Aug 2020 Bournemouth, Dorset, UK (Work From Home)
  • Object-oriented programming in a finance setting using Python (testing with pytest), Flask, sklearn, tensorflow and SQL
  • Planned a solution for a disaster relief charity to port 40% of in-person training to online training and initiated contact with a software-service company to discuss technical and financial details of our solution (£200k+ annual savings proposed)
Imagination Technologies
Hardware Engineer Intern
Jul 2019 – Sep 2019 Kings Langley, Hertfordshire, UK
  • Co-inventor on 3 separate pending patent applications for arithmetic hardware designs with improved PPA (Power, Performance, Area) over industry standards; worked with the datapath team in an R&D environment
  • Learnt to rapidly interpret code from past/current team members and make changes (Linux, Python, Perforce, VHDL)


University of Cambridge
Master of Engineering - MEng (Double First)
Sep 2017 – Jul 2021 Cambridge, Cambridgeshire, UK
  • 1st Year: Class I (87%, 12th of 324)

  • 2nd Year: Class I (83%, 12th of 310)

  • 3rd Year: Pass (COVID/No Classing)

  • 4th Year: Honours Pass with Distinction

  • Masters Project in Explainable AI

  • Outstanding Project Award for top 5% of students in Information Engineering

  • 1st paper accepted to ICLR workshops (first-author, travel award)

  • 2nd paper accepted to ICML workshops (first-author)

  • Combined paper submitted to NeurIPS conference (under review)

  • Specialisation of Computer and Information Engineering

  • Dewhurst Scholarship for First and Second Year Results

Exeter Mathematics School
A Levels (4A*s)
Sep 2015 – Jul 2017 Exeter, Devon, UK (Work From Home)
  • 4A*s: Mathematics, Furthermathematics, Physics and Chemistry
  • College Award for Academic Excellence in Mathematics
  • Senior Team Mathematics Challenge Regional Winners and National Final Competitors
  • British Mathematical Olympiad Qualification through Senior Mathematical Challenge
Queen Elizabeth's School
GCSEs (13 A*s)
Sep 2010 – Jul 2015 Crediton, Devon, UK
  • 13 A*s: Double Maths, Double English, Triple Science, Statistics, Astronomy, Spanish, French, History, Geography
  • School Award for Highest Academic Achievement



Passive Fluency


Full Fluency


Level B2