This page contains an overview of my publications, teaching, awards and fellowships, ways in which I am contributing to the field and a selection of invited talks and workshops I have led.
My Google Scholar contains the most up to date list of publications.
Note: I now publish under my legal name, Joseph Aylett-Bullock. Before April 2021 I published under Joseph Bullock.
Note: Given the sensitivity of my current work, my academic publications are now less regular; however, I still engage in research and development which I will publish when possible
Area Chair, AI for Social Impact, AAAI (2022)
Reviewer, ACM GoodIT (2022)
Guest Editor, Remote Sensing (2020-2021)
Area Chair, AI for Social Impact, AAAI (2021)
Programme Chair, ACM COMPASS (2020)
Reviewer, International Conference on Machine Learning (2020)
Reviewer, AI for Humanitarian Assistance and Disaster Response Workshop, NeurIPS (2020))
Senior Programme Chair, AI for Social Impact, AAAI (2020)
Organiser and Track Chair, AI for Social Good Workshop, NeurIPS (2019)
Organiser, Data Science Forum, Institute for Data Science, Durham University (2019-present)
Convener, Annual Young Experimentalists and Theorists Institute (2019)
Lead Convener, 12th Annual Young Theorists Forum (2019)
Convener, 11th Annual Young Theorists Forum (2018)
Co-founder, Machine Learning Journal Club, Durham University (2018)
Reviewer, Computers and Geosciences, Elsevier
Teaching Assistant:
Statistics and Machine Learning, part of the Masters in Scientific Computing and Data Analytics (MSc) programme, Durham University (2019-2021)
Complex Analysis, Department of Mathematics, Durham University (2017)
RAMP Early Career Investigator Award: The Royal Society (2021)
Departmental Award for Excellence: Durham University (2020)
Most Notable Article: Remote Sensing, MDPI (2020)
Top Reviewer: International Conference on Machine Learning (ICML) (2019)
Best Student Paper: SPIE Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging (2019)
Best Presentation: Josephine Butler Research Forum, Durham University (2018)
Durham Award: For exceptional contribution to University and College life, community outreach, and developing key skills for increased employability (2017)
EPSRC IAA: Funding bid with Durham University for 1.5 postdocs for 6 months to support epidemic modelling work (co-supervised) (2021-2022)
UN Global Pulse Research Fellowship: Fellowship supporting my work with UN Global Pulse (2018-2019)
Intel Research Award: Financial and computational support relating to the publication of papers in medical imaging (2018)
NVIDIA Hardware Grant: Awarded access to NVIDIA computational resources (2018)
UKRI-STFC Ph.D Scholarship: Full funding for doctoral programme (2017-2021)
Member, UNESCO Working Group on Ethical Principals and Policy Recommendations (2022-present)
Member, Broadband Commission Epidemic Preparedness Working Group (2020-present)
Invited to join ML for COVID Working Group, Schmidt Futures (2020)
Co-Chair, The United Nations AI-Geo Working Group (2019-2020)
National representative, The Youth Assembly (2019)
Epidemic Modelling in Refugee and IDP Settlements, United Nations World Data Forum (2021)
Machine Learning for Crisis Response, World Bank Monitoring and Evaluation Seminar Series (2021)
AI for Policy and Operational Impact, World Bank RMES Results Peer Learning Series (2021)
Epidemic Modelling in Refugee and IDP Settlements, WHO Epidemic Modelling Cell (2021)
Machine Learning for Crisis Response, Guest Lecture, Public Health Data Science, MIT (2021)
Mathematical Modelling for Crisis Response, United Nations Innovation Network (2021)
Radio Monitoring for Public Health Social Listening, WHO Infodemic Management Training (2021)
Radio Monitoring for Public Health Social Listening, WHO Infodemic Management Conference (2021)
From Biomedical Image Segmentation to Flood Mapping at UNOSAT, Geneva Health Forum (2020)
JUNE: an Open-Source Individual-Based Epidemiology Simulation, Institute for Data Science Seminar Series, Durham University (2020)
Using Neural Networks for Scattering Amplitude Approximation, Innovative Computing Group, Durham University (2020)
Machine Learning for Geospatial Analysis, InsurTech Alliance Expo (2020)
Humanitarian Applications of AI for Remote Sensing, Institute for Risk and Reslience, Durham University (2020)
Mapping Risks and Biases in AI Systems, Innovative Computing Group, Durham University (2020)
Mapping Risks in Generated Text, Institute for Data Science Launch Event, Durham University (2019)
AI for Humanitarian Relief, Digital Aid Workshop, Alan Turing Institute (2019)
Data Science for Humanitarian Relief, Office of the United Nations High Commissioner for Human Rights (2019)
A complex systems approach to AI and converging technologies, ITU AI for Good Global Summit (2019)
AI for Social Good, Second Annual Conference of the Durham University STFC Centre for Doctoral Training in Data Intensive Science (2019)
Humanitarian uses of AI, Durham University Advanced Research Computing Launch Event (2019)
Segmenting X-Ray Images with Neural Networks, Live Demonstration, Showcase event, United Kingdom House of Commons (2019)
Applied Ethics in Data Analytics, Guest Lecture, Data Analytics and Metrics for the Nonprofit Sector, Columbia University School of Professional Studies (2019)
Segmenting X-Ray Images with Neural Networks, Live Demonstration, Computer- Aided Diagnosis Workshop, SPIE Medical Imaging (2019)
Satellite Image Analysis for Humanitarian Relief, InsureTech Alliance Meeting (2019)
Satellite Image Analysis for Humanitarian Relief, Center for Data Science, New York University (2018)
Introduction to Machine Learning, 4-day workshop, IBEX Innovations Ltd. (2018)
X-Ray Image Segmentation, First Annual Conference of the Durham University STFC Centre for Doctoral Training in Data Intensive Science (2018)
Hey Google: Show me a llama: An Introduction to Machine Learning, Josephine Butler Research Forum, Durham University (2018)
An Introduction to Machine Learning, Broaderlands Lecture Series, Durham University (2018)