Artificial Intelligence Researcher
Artificial intelligence explicability, visualisation and interpretation of deep learning models; deep learning and computer vision for medical applications; neural network architecture design.
5+ years in Python, plus various machine learning and data handling libraries including Numpy, Pandas, Pytorch and TensorFlow.
- Jessica Cooper, In Hwa Um, Ognjen Arandjelović, David J Harrison. Hoechst Is All You Need: Lymphocyte Classification with Deep Learning. Under review
- Jessica Cooper, Ognjen Arandjelović and David Harrison. Believe The HiPe: Hierarchical Perturbation for Fast and Robust Explanation of Black Box Models. Under review
- Jessica Cooper, Neofytos Dimitriou and Ognjen Arandjelović. The science that informs government policy, its quality and ethical implications – a lesson from the UK’s response to 2020 CoV-2 outbreak. Accepted/In press: Journal of Bioethical Inquiry.
- Jessica Cooper and Ognjen Arandjelović. Learning to Describe: A New Approach to Computer Vision Based Ancient Coin Analysis. SCI: Machine Learning and Vision for Cultural Heritage.
- Jessica Cooper and Ognjen Arandjelović. Understanding Ancient Coin Images. INNS Big Data and Deep Learning 2019.
- Jessica Cooper. Weakly Supervised Deep Learning of Artistically Depicted Concepts on Ancient Coins. MSc Dissertation.
May 2019 – Present
Research Scientist, Centre for AI Research in Digital Diagnostics, School of Medicine, University of St Andrews
- Researching the application of deep learning to digital pathology and diagnostics.
September 2018 – Present
Machine Learning Research Consultant, Predict Mobile
- Building machine learning models to predict call and data usage for business telecoms.
Machine Learning Research Consultant, 3etage
- Preliminary research and data exploration to assess potential applications of machine learning to client data assets.
July 2018 – September 2018
St Andrews: CAPOD Mentor for Computer Science Taught Masters
- Mentored students, helping them prepare for the MSc Advanced Computer Science programme.
June 2018 – July 2018
St Andrews: Fast Track Deep Learning Organiser
- Organised a deep learning lecture course in partnership with Neofytos Dimitriou for postgraduate students in the School of Computer Science.
April 2018 – October 2018
AI Safety Research Camp: Outside Research Coordinator
- Helped to organise a non-profit research accelerator, liaising with the outside academic community to understand priority research areas in AI safety and interviewing applicants.
February 2018 – April 2018
AI Safety Research Camp: Artificial Intelligence Safety Researcher
- Worked with Karol Kubicki, Gavin Leech and Tom McGrath, implementing DQN and IRL agents to explore AI safety in gridworlds, extending existing work.
- Wrote new stochastic and dynamic environments for Deepmind’s pycolab engine to explore side-effects problems. Code.
January 2018 – August 2018
University of St Andrews: AGI Forum
- Organised a weekly Artificial General Intelligence academic reading group, facilitating interdisciplinary discussion of AI research with staff and students from computer science, medicine, neuroscience, psychology, maths and philosophy.
January 2018 – September 2018
Effective Altruism: Society St Andrews Committee Member
- Assisted with running the society and organising EA events within St Andrews, focusing mainly on promoting discussion of AI safety and ethics.
December 2016 – September 2017
Freelance Web Developer
July 2012 – May 2017
J M Cooper Design: Owner/Creative Director
- Ran small design agency, working for a range of international clients in web design, branding, illustration, publishing and technical artwork.
- Planned complex short and long term projects, leading small teams of freelancers across several time zones.
- Understanding Ancient Coin Images INNS Big Data and Deep Learning 2019
- Meta-learning: Can We Learn How To Learn? 7th Dalehead Philosophy Retreat, 2018
- The AI Safety Problem 6th Dalehead Philosophy Retreat, 2017
- Artificial Intelligence is a Threat To Humanity (debate) St Andrews Computer Science Postgraduate Reading Party
- Preventing Side Effects in Gridworlds AI Safety Research Camp
January 2020 – Present
Doctoral Student, School of Computer Science, University of St Andrews
- PhD in Computer Science, in deep neural network interpretability.
September 2017 – September 2018
MSc Advanced Computer Science (with Distinction), University of St Andrews
- Dean’s List award for academic excellence.
- Modules: Object Oriented Programming, Modelling and Design (Distinction); Artificial Intelligence Principles (Distinction); Artificial Intelligence Practice (Distinction); Interactive Software and Hardware (Distinction); Visual Analytics (Distinction); Data, Ethics & Privacy (Merit); Machine Learning (Distinction).
- Highlights: Built a small autonomous robot and a virtual pond full of evolving fish; created a quantitative framework for assessing privacy risk in data science projects; was nominated for the Proctor’s Award for Teaching Excellence and Student Leader of the Year.
September 2009 – May 2012
BA Fine Art (2:1), Birmingham Institute of Art and Design