Explainable AI Seminars @ Imperial

CLArg Group, Department of Computing, Imperial College London


XAI has witnessed unprecedented growth in both academia and industry in recent years (alongside AI itself), given its crucial role in supporting human-AI partnerships whereby (potentially opaque) data-driven AI methods can be intelligibly and safely deployed by humans in a variety of settings, such as finance, healthcare and law. XAI is positioned at the intersection of AI, human-computer interaction, the social sciences (and in particular psychology) and applications.

Overall, XAI is increasingly part of all AI policies on ethics, trustworthiness and safety of AI. This seminar series focuses on all aspects of XAI, ranging from methods to applications.

Coming up

Prof Mihaela van der Schaar: Title TBC

Monday 20th February, 16:00 GMT

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Next Seminar

Prof Mihaela van der Schaar: Title TBC

Monday 20th February, 16:00 GMT, Hybrid - Huxley Building, Lecture Theatre LT 145, Imperial College London (see here for directions) and on Microsoft Teams: Link


Abstract

TBC

Short Bio

Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge and a Fellow at The Alan Turing Institute in London. In addition to leading the van der Schaar Lab, Mihaela is founder and director of the Cambridge Centre for AI in Medicine (CCAIM). Mihaela was elected IEEE Fellow in 2009. She has received numerous awards, including the Oon Prize on Preventative Medicine from the University of Cambridge (2018), a National Science Foundation CAREER Award (2004), 3 IBM Faculty Awards, the IBM Exploratory Stream Analytics Innovation Award, the Philips Make a Difference Award and several best paper awards, including the IEEE Darlington Award. Mihaela is personally credited as inventor on 35 USA patents (the majority of which are listed here), many of which are still frequently cited and adopted in standards. She has made over 45 contributions to international standards for which she received 3 ISO Awards. In 2019, a Nesta report determined that Mihaela was the most-cited female AI researcher in the U.K.

Past Seminars (since 2019)

Speaker Title Date Attendance
Pietro Totis Reasoning on Arguments and Beliefs with Probabilistic Logic Programs December 8, 2022 Over 25
Eleonora Giunchiglia Deep Learning with Hard Logical Constraints November 23, 2022 Over 25
Emiliano Lorini Non-Classical Logics for Explanations in AI Systems November 9, 2022 Over 25
Cor Steging Responsible AI: Towards a Hybrid Method for Evaluating Data-Driven Decision-making October 26, 2022 Over 20
Gopal Gupta Automating Commonsense Reasoning October 14, 2022 Over 20
Benjamin Grosof Towards Stronger Hybrid AI: Combining Extended Logic Programs with Natural Language and Machine Learning October 5, 2022 Over 30
Lun AI Effects of machine-learned logic theories on human comprehension in machine-human teaching July 13, 2022 Over 10
Dylan Slack Exposing Shortcomings and Improving the Reliability of ML Models June 22, 2022 Over 15
Joao Leite Logic-based Explanations for Neural Networks June 9, 2022 Over 15
Oana Camburu Neural Networks with Natural Language Explanations May 26, 2022 Over 15
Nino Scherrer Learning Neural Causal Models with Active Interventions April 27, 2022 Over 10
Hamed Ayoobi Explain What You See: Argumentation-Based Learning for 3D Object Recognition April 6, 2022 Over 10
Mattia Setzu Breaking the Local/Global explanation dichotomy: GLocalX and the Local to Global explanation paradigm March 17, 2022 Over 10
Eoin Kenny Explaining Black Box Classifiers via Post-Hoc Explanation-by-Example: Factual, Semi-Factual, and Counterfactual Explanations March 2, 2022 Over 20
Riccardo Crupi Counterfactual Explanations as Interventions in Latent Space February 14, 2022 Over 20
Martin Jullum Prediction explanation with Shapley values February 3, 2022 Over 15
Ioannis Votsis The Study of Reasoning in Philosophy, Psychology and AI: In Search of Synergies January 19, 2022 Over 15
Michael Yeomans Conversational Receptiveness: Improving Engagement with Opposing Views December 13, 2021 Over 10
Piyawat Lertvittayakumjorn Explanation-Based Human Debugging of NLP Models December 1, 2021 Over 15
Leila Amgoud Explaining Black-Box Classifiers: Properties and Functions November 24, 2021 Over 40
Guilherme Paulino-Passos Monotonicity, Noise-Tolerance, and Explanations in Case-Based Reasoning with Abstract Argumentation November 10, 2021 Over 10
- explAIn Workshop: Exploring the links between Explainable AI, Causality and Persuasion July 8, 2021 Over 30
Fabrizio Silvestri Counterfactual Explanations of (some) Machine Learning Models June 9, 2021 Over 15
Marek Sergot Actual cause and chancy causation in 'stit' logics June 2, 2021 Over 15
Menna El-Assady Visual Analytics Perspectives on Interactive and Explainable Machine Learning May 5, 2021 Over 25
Tony Hunter Overview of Computational Persuasion and relationships with Explainable AI April 14, 2021 Over 20
Timotheus Kampik Principle-based and Explainable Reasoning: From Humans to Machines March 17, 2021 Over 10
Umang Bhatt Practical Approaches to Explainable Machine Learning February 24, 2021 Over 30
Riccardo Guidotti Exploiting Auto-Encoders for Explaining Black Box Classifiers January 27, 2021 Over 40
Kacper Sokol Modular Machine Learning Interpretability: A Case Study of Surrogate Explainers December 9, 2020 Over 15
Hana Chockler Why do things go wrong (or right)? November 25, 2020 Over 40
Emanuele Albini Relation-based conterfactual explanations for Bayesian classifiers November 4, 2020 Over 40
Jannes Klass Explainable AI in the Wild: Lessons learned from applying explainable AI to real world use cases March 4, 2020 Over 15
Brent Mittelstadt Governance of AI through explanations: From approximations to counterfactuals February 12, 2020 Over 20
Claudia Schulz Explaining (how to improve) Diagnostic Reasoning January 15, 2020 Over 30
Erisa Karafili Helping Forensics Analysts to Understand and Attribute Cyber-Attacks December 4, 2019 Over 15
Pasquale Minervini Explainable, Data-Efficient, Verifiable Representation Learning in Knowledge Graphs November 27, 2019 Over 15
Adam White Measurable Counterfactual Explanations for Any Classifier November 13, 2019 Over 15
Loizos Michael Acceptable Explanations through Machine Coaching November 7, 2019 Over 15
Dave Braines Conversational Explanations – Explainable AI through human-machine conversation October 14, 2019 Over 25
Zohreh Shams Explanation in Ontology Reasoning October 1, 2019 Over 25
Filip Radlinski User-Centric Recommendation July 4, 2019 Over 25
Sanjay Modgil Dialectical Formalizations of Non-monotonic Reasoning: Rationality under Resource Bounds June 20, 2019 Over 20
Daniele Magazzeni Model-Based Reasoning for Explainable AI Planning as a Service May 30, 2019 Over 25
Christos Bechlivanidis Concrete and Abstract Explanations May 20, 2019 Over 20
Simone Stumpf Making Human-Centred Machine Intelligence Intelligible April 15, 2019 Over 20
Ken Satoh ContractFrames: Bridging the gap between Natural Language and Logics in Contract Law March 25, 2019 Over 20
Number of talks:

Contact Information

Email: xai-CO@groups.imperial.ac.uk

Organisers

Nico Potyka       Fabrizio Russo