As the end of the year approaches, we wanted to recap an exciting year of engagement and take a moment to thank everyone who attended Inspiration Exchange in 2022. Our audience, their engagement, and contributions have made this series a truly enriching experience for all of us.
In addition, we are grateful to have had the opportunity to host such a diverse group of speakers, who shared their knowledge and insights with us on a wide range of topics.
You can find recordings of all our sessions here. There, you can also find the option to sign up for our future sessions.
Our 2022 sessions
ML to transform organ transplantation (7th Jan) – We began the year with an applications-focused session for ML in organ transplantation, discussing recent work OrganITE, OrganSync, and iTransplant. We were joined by 3 clinicians working in organ transplantation Dr Alexander Gimson, Dr Vasilis Kosmoliaptsis (University of Cambridge), and Dr Brent Ershoff (UCLA).
Next frontiers in interpretability (7th Feb) – In this session we discussed the unique requirements for interpretability in healthcare, highlighting the multi-faceted nature of the problem and the different types of interpretability needed.
Discovery using machine learning (4th Mar) – Machine learning is capable of more than building predictive models – in this session, we explored how ML can be used to discover governing equations from data.
Causal deep learning (Part 1 – 14th Apr, Part 2 – 27th May) – These were our first Inspiration Exchange sessions with a newly introduced format! Across two sessions, we discussed the emergent field of causal deep learning and the impact principles of causality could have in machine learning. In Part 1, we were joined by Dr Silvia Chiappa (DeepMind), Dr Kim Branson (GSK), and Dr Lindsay Edwards (Relation Therapeutics), and in Part 2, we welcomed Dr Amit Sharma (Microsoft Research), Dr Cheng Zhang (Microsoft Research), and Dr Jim Weatherall (AstraZeneca) for lively “round-table” discussions.
Neural differential equations (4th Oct) – Neural differential equations are a fascinating new class of machine learning models. In this session, we provided an introduction to neural DEs and discussed their impact in healthcare and beyond with Dr Emma Slade (GSK) and Dr Javier Hernández (Microsoft Research).
Frontiers in ML interpretability (25th Oct) – We were thrilled to be joined by Dr Been Kim (Google Brain) and Dr Jianying Hu (IBM) as we revisited the critical topic of interpretability in healthcare, presenting recent advances in concept-based explanations and an example of how interpretability can be used to evaluate models.
AutoPrognosis 2.0 (22nd Nov) – In this session, we introduced AutoPrognosis 2.0, our lab’s latest open-source software package that allows users to build diagnostic and prognostic models using automated machine learning. We discussed the role and impact of such approaches in medicine with Dr Aditya Nori (Microsoft Health Futures) and clinical collaborators Prof. Eoin McKinney (University of Cambridge) and Dr Thomas Callender (UCL), the latter presenting an early application of AutoPrognosis 2.0 to lung cancer.
Data-centric AI (13th Dec) – Our final session of the year explored data-centric AI with Prof Isabelle Guyon (Google Brain), who recently gave a fascinating Keynote at NeurIPS 2022 on the data-centric era. In this session, we discussed a framework for data-centric ML as well as specific methods for understanding training and test data.
Our next session will be held on 1 February 2023. The focus of the session will be Synthetic Data, a new and exciting area of machine learning with real-world impact.
More details to follow in the New Year!
We are very much looking forward to welcoming you to our Inspiration Exchange in 2023!