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Welcome to our lab, where Professor Occhipinti and her team develop multi-modal AI approaches across different sectors, from cancer biology to metabolic engineering
Welcome to our lab, where Professor Occhipinti and her team develop multi-modal AI approaches across different sectors, from cancer biology to metabolic engineering
I am a Professor at Teesside University. I hold a PhD in Computer Science from the University of Cambridge, awarded in 2016.
I work at the intersection between Computer Science and Biology to develop machine learning and deep learning methodologies for cancer prediction. My current research topics include deep learning applications for multi-modal data integration, mathematical and computational modelling of cancer, machine learning, survival analysis and statistical methods.
I have recently received several awards for my contributions in the field of machine learning, big data and cancer research, including an award from the University of Cambridge for my contribution to breast cancer research.
My research is also supported by multiple BBSRC and EPSRC grants, past and ongoing, that I have led, on the application of AI to diverse challenges in the biological sciences.
I also have experience in AI applications for biotechnology. I am currently involved in multiple Innovate UK projects with industrial partners to apply AI techniques for gaining valuable operational insights from different data sources.
External Roles:
External Professional Expert at the National Institute for Health and Care Excellence (NICE)
Co-lead of the "AI for Women's Health" Interest Group, The Alan Turing Institute
BBSRC Pool of Experts Committee Member, reviewing Responsive Mode and sLoLa grants
External Grant Reviewer for Cancer Research UK, SBRI Healthcare, and The Academy of Medical Sciences;
Lead of the Young Researchers Group as part of the Net4Brain European COST Action
Co-Lead of WP2 on Metabolic Modelling Community and EDI representative as part of the Horizon Europe Project XTREAM. Press release link
Working with the AIBIO-UK (BBSRC) Network as part of the "AI-Ready Data WG"
Guest Editor of the Collection on AI for Multimodal Biomedical Imaging, Communications Engineering
We develop AI methods for integrating multiple data types and gain biological insights
We develop AI methods for integrating multiple data types and gain biological insights
News and Events
News and Events
I was interviewed as part of the press release (When) Will AI Improve Women’s Health?, Algorithm Watch
Our "AI for Women's Health" event was a great success! Thank you to everyone who joined. You can read more here
The AI for Women's Health group led by myself, Bianca Schor, Kristin Caolo, and Emma Karoune has been recognised as 2025 AI Visionaries by the Health Innovation Kent Surrey Sussex (KSS) and the Department for Health and Social Care (DHSC). This award celebrates our contributions to women's health and gender equity through artificial intelligence!
I received EPSRC funding through the NortHFutures Hub to host an intern as part of the Black Internship Program!
PhD Meeting. It was great to meet all PhD students in SCEDT on the 9th of December for our Christmas Celebration!
The next AI for Women's Health meeting will be on the 4th of December at 12pm. Don't miss it! Registration Link Here
I am acting as a Guest Editor of the Collections on AI for Multimodal Biomedical Imaging, Communications Engineering.
Invited speaker at the "G2W: Genomics to Whole Cell Workshop" in Sheffield 23rd-25th October, as part of the AIBIO-UK network. More information here and here
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