I am a Professor of Artificial Intelligence and the Director of the Visual Artificial Intelligence Laboratory, a thriving research unit comprising around 35-40 people, including permanent staff, paid researcher and members at large. I am also in the Board of Oxford Brookes' Institute of Ethical AI and of the Healthy Ageing and Care (HAC) network.
Teaching and supervision
Although I am not currently involved in the teaching, I do have an extensive teaching experience at university level in three different countries, first as a Teaching Assistant (TA) in Padua and Milan, Italy, later as a TA at the University of California at Los Angeles, USA, and eventually as the Module Leader for a number of Undergraduate and Postgraduate courses at Oxford Brookes University, UK. At Brookes I have supervised several Master's students' dissertations and third year’s final projects. I was also Subject Coordinator for the PG "Computer Vision" programme.
Taught courses at PostGraduate level: P00990 “Research and Scholarship Methods" (2013-14), P00405 “Mathematical Methods for Computer Vision" (2013-17), P00406 “Machine Learning" (2013-18), P00408 “Advanced Computer Vision" (2015-17), P08821 / DALT7021 “Advanced Machine Learning” (2018-2021), SOFT7010 “Data Science and Machine Learning” (2019-2021), all as the Module leader, plus P00702 “Cyber security and the web” and P00407 “Principles of Computer Vision” as co-teacher.
At UnderGraduate level: U08781 / COMP6025 “Machine Vision" (2008-2021), U08280 “Advanced Artificial Intelligence" (2009-2013), U08884 “Image Technology" (2009-2015) as the Module Leader, plus U08027 “Current research”, U08702 “Multimedia IT skills” and U08055 “Professional issues and computer risks” as co-teacher.
I am currently supervising 4 MSc students, 5 PhD students and 8 postdocs and research fellows. The full list of people under my supervision is provided below.
Aytac Kanaci, funded by the ECM School (Sep 2021 - now); Naeemullah Khan, funded by H2020 Epistemic AI (Aug 2021 - now); Ajmal Shahbaz, funded by the Huawei Research Agreement (Jan 2021-2023); Bogdan-Ionut Cirstea, funded by the Leverhulme Trust (Feb 2020-now); Reza Javanmard Alitappeh, funded by ECM School fellowship (Apr 2019 – Nov 2019); Inna Skarha-Bandurova, Vivek Singh, Dinesh Jackson Samuel, funded by the SARAS EU project (Aug 2019 – Dec 2021), Mohamed Ibrahim Mohamed (Dec 2019 - June 2021), also funded by the SARAS Horizon 2020 project; Suman Saha (Dec 2017-Jul 2018), now postdoc at ETH Zurich; Ruomei Yan (Sep 2017-Dec 2017), now with ARM Semiconductors; Ahmed Samet (Mar 2016 - onward), Project title: “New robust foundations of statistical machine learning”; Wenjuan Gong (Feb 2013 - Jan 2014), funded by EPSRC First Grant, Project title: “Tensorial modeling of dynamical systems for gait and activity recognition" (now Lecturer at China University of Petroleum, Qingdao, Shandong, China).
Vivek Singh (Nov 2021 - now), funded by an Innovate UK KTP partnership with Supponor; Neha Bhargava (Apr 2019-21), funded by the KTP with Createc Technologies; Ruomei Yan (Sept 2015 - Nov 2017), funded by Meta Vision KTP, Project title: “Sensing a good weld: new applications in computer vision" (formerly a Lecturer at Shanghai Chan-Mai University, the 3rd best Chinese university).
Ph.D. students (as Director of Studies, unless otherwise indicated)
Michael Sapienza (Oct 2011 - Oct 2014), Thesis title: “Recognising and localising human actions" (now with Samsung Research, formerly postdoc at Oxford University, Department of Engineering Science); Vinhav Vineet (January 2014 - October 2014), second supervisor, thesis title: “Recognition, Reorganisation, Reconstruction and Reinteraction for Scene Understanding" (now postdoc at Stanford University); Min Han Lee (September 2014 - August 2015), Topic: “Action recognition from unconstrained videos"; Suman Saha (September 2014 - present), Topic: “Uncertainty in Computer Vision", Winner of best MSc dissertation at University of Bedfordshire and best reading group competition at the 2015 International Summer School of Computer Vision (ICVSS 2015), now postdoc at ETH Zurich; Gurkirt Singh (September 2015 - present), Topic: “Real-time Action Recognition for Human-Robot Interaction", now postdoc at ETH Zurich; Wojtek Buczynski (Oct 2018 - now), based in Cambridge University, second supervisor (DoS Prof Barbara J. Sahakian); Salman Khan (Feb 2020 - now), funded by the research agreement with Huawei Technologies; Devashish Bharti (April 2020-now), topic: “Federated learning for model adaptation”; Izzedin Teeti (from Jan 2021), topic: “Intelligent Transport Systems”; Shireen Kudukkil Manchingal (from Sep 2021), funded by the Epistemic AI Horizon 2020 project.
Rocco de Rosa (January 2014 - July 2014), EU Erasmus Training Programme (now Data Science Manager at Rank Group, formerly a postdoc at University of Rome “La Sapienza"); Serdar Buyukkanli (June 2014 - September 2014), funded by EU Erasmus Training Programme; Brenda Romino (February 2016 - August 2016), funded by University of Naples; Manuele Di Maio (March 2017 - September 2017), funded by Erasmus+; Andrea Morelli (January 2017 - May 2017), funded by Erasmus+; Shashwat Shukla, Oxford Brookes - IIT Bombay exchange programme; Santanu Rathod (May-Jul 2018), Brookes - IIT programme; Valentina Fontana (Mar-Sep 2018), Erasmus+ trainee from Naples’ Federico II; Giacomo De Rossi (Sep-Nov 2018), Univ of Verona; Silvio Olivastri (Mar-Jun 2018; Mar 2019), AI Labs, Bologna; Dr Filippo Vella (Jan 2019), researcher at CNR Palermo, Italy; Prof Ahmad Osman (Aug 2019), Professor at Fraunhofer Institute, Saarbrucken, Germany; Biplab Banerjee (Feb 2020), Assistant Professor at IIT Bombay, India.
Brad Lishman (2012), Stephane Bourgeois (2014), Jonathan Pound (2014), Paula Rocafull (2015), Ben Guy (2016), Kurt DeGiorgio (2016), Misbah Munir (2016-17), Stavros Gasparis (2017), Krishna Parshotam (2017), Stephen Akkrigg (2018), Francis Kaping’A (2018), Parijat Patel (2019), Anudeep Chikkam (2019-2020), Hui Li (2020), Adam Gibson (2020), Mark Edward (2020), Tereza Maláčová (2021), Ruben Guerrero (2021), Wei Guo (2021), Karthik Ambati (2021).
I was external examiner for PhD candidates Andrea Argentini, University of Trento, in 2012 (title of the thesis: “Ranking Aggregation Based on Belief Function Theory”); Pawel Kowalski, University of Bristol, 2021; Farnoosh Heidarivincheh, University of Bristol (“Action completion recognition and detection”), 2020; Zhenghua Xu, Oxford University, 2017; Timber Kerkvliet, VU University Amsterdam, 2017; and for the habilitation of John Klein (Lille University, France), 2017. I was member of the PhD panel for Marco Podda and Daniele Castellana (University of Pisa, Italy), 2021. I have been internal for Ph.D. candidates Chris Russell (title: “Higher-order inference for vision problems”) and Paul Sturgess (April 2016). I have been invited to act as external at KTH Sweden and University of Belfast in the autumn of 2018.
|Devashish Bharti||Federated machine learning||Active|
|Salman Khan||Deep Scene Graph Models for Complex Activity Detection||Active|
|Shireen Kudukkil Manchingal||Epistemic Artificial Intelligence||Active|
|Mr Izzedin Teeti||Predictive Algorithms for Advanced Autonomous Vehicle Perception||Active|
I am a recognised leader in the field of uncertainty theory and belief functions, as conference chair, four-term member of the Board of Directors of the Belief Functions and Applications Society (BFAS), former Executive Editor of SIPTA (the Society for Imprecise Probabilities) and editor of journals such as IJAR and IEEE TFS. My reputation there comes from the formulation of a geometric approach to uncertainty in which various measures are analysed by geometric means. This work has led to two monographs, two edited volumes and various tutorials and invited talks at top universities and venues. More in general, I am widely contributing to the mathematical foundations theory of random sets (generalised laws of probability, generalised statistical inference and random variables), with the aim to make it a viable alternative to probabilistic reasoning.
Within artificial intelligence at large my work is directed at providing new robust foundations for statistical learning theory via uncertainty theory, and developing novel tools based on the theory of random sets, e.g. the generalisation of the logistic regression and max-entropy classification frameworks. In the past I also worked on manifold learning for dynamical models and the generalisation of bilinear classifiers to the tensorial case (EPSRC First Grant). Since 2016 my interests and the activities in my group have been expanding towards surgical robotics (via the H2020 SARAS project of which I am Scientific Officer, and the recent EPSRC MAESTRO Jr project with Imperial College), AI for healthcare (via joint papers and bids with Prof Helen Dawes and Prof Derick Wade), cognitive artificial intelligence (see my Leverhulme machine theory of mind grant with Cambridge Neuroscience) and autonomous driving (via a collaboration with Federico II University, Naples and OBR - Autonomous). Very recently I have been strongly promoting the injection of second-order uncertainty into the very foundations of artificial intelligence, in particular through my recent H2020 FET ‘Epistemic AI’, neurosymbolic learning (in collaboration with Oxford University and Samsung AI) and continual learning, in particular in the semi-supervised setting, in collaboration with ContinualAI.
The Visual Artificial Intelligence Laboratory, which I funded in 2012 under the name first of Artificial Intelligence and then of AI and Vision group, is now a vibrant and fast growing team projected to comprise 35 people in 2022, including 6 members of staff (F. Cuzzolin, A. Rast, M. Rolf, T. Olde-Scheper, A. Bradley and I. Skarga-Bandurova), 1 KTP associate, 8 postdocs and research fellows, 6 PhD students, 1 administrator, 3 MSc students and 12 external collaborators. The Lab is one of the largest in the University, and one of the top research groups in the world in deep learning for action detection, collaborating with top universities such as Oxford, Cambridge and Imperial and companies such as Samsung and Huawei. The Lab is now pioneering frontier topics such as future action prediction, the modelling of complex activities via deep neural architectures, machine theory of mind, continual semi-supervised learning, neurosymbolic AI, the theory of self-supervised learning and epistemic artificial intelligence.
More information is available on our internal website.
To date I am the author of some 130 peer-reviewed publications, published or under review. In particular I am sole author of two monographs, editor of two LNCS volumes, and author of 35 journal papers or book chapters. Lambert Academic (LAP) has published a heavily revised version my Ph.D. thesis “Visions of a generalized probability theory" as a monograph in September 2014. I was the sole Editor of the volume “Belief functions: theory and applications" - BELIEF 2014 Proceedings, and co-Editor for the “Belief functions: theory and applications" BELIEF 2018 LNCS volume. My 866-page monograph “The geometry of uncertainty – The geometry of imprecise probabilities", collecting my original ten-year work on this topic, was published by Springer Nature in January 2021.
To date I attracted direct external funding for a total of circa £5,400,000, of which around £4M since 2018, part of grants for a total value of around 10M, including the recent €3M H2020 Future Emerging Technologies (FET-Open) project Epistemic AI which I am coordinating. In addition, I am overall Scientific Officer for the €4.3M Horizon 2020 project SARAS (Smart Autonomous Robotic Assistant Surgeon), and I am Lead Team member and advisor for the recent £1,257,000 Research England Development (RED) funded Oxford Brookes Artificial Intelligence & Data Analysis Incubator (AIDA). I was also awarded over the years by the university internally-funded studentships for the equivalent of £416,000.
Currently the Visual AI Lab (VAIL) is running on a budget of around £3.2M, with nine live projects funded by Horizon 2020 (2), the Leverhulme Trust, Innovate UK (2), Huawei Technologies, UKIERI, and the School of Engineering, Computing and Mathematics.
- Second place overall in IMechE Formula Student – AI 2021
- W&B Best Library Award – CLVision Workshop @ CVPR 2021
- for the paper: “Avalanche: an End-to-End Library for Continual Learning”
- First place overall in IMechE Formula Student – AI 2020
- Overall UK winner in both Dynamic Driving Task and Autonomous Vehicle Simulation Development
- Third place in IMechE Formula Student - AI 2019 (as part of OBR - Autonomous)
- 2017 CVPR Charades challenge, 2nd place (with G. Singh)
- 2016 CVPR ActivityNet action detection challenge, 2nd place (with G. Singh)
- Next 10 Award - Oxford Brookes University - Faculty of TDE (2012)
- Research accelerator programme, awarded to the top emerging researchers in the Faculty of Technology, Design and Environment
- Outstanding Reviewer Award - British Machine Vision Conference (BMVC 2012)
- Short-listed for the Best Paper Award - British Machine Vision Conference (BMVC 2012)
- For the paper: “Learning discriminative space-time actions from weakly labelled videos"
- Best Poster Prize - INRIA Visual Recognition and Machine Learning Summer School (VRML 2012)
- For the poster: “Learning discriminative space-time actions from weakly labelled videos" (with student Michael Sapienza)
- Best Poster Award - International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA’11)
- For the poster: “Geometric conditional belief functions in the belief space"
- Short-listed for the Best Paper Award - ECSQARU 2011
- For the paper “On consistent approximations of belief functions in the mass space"
- Best Paper Award - Pacific Rim International Conference on Artificial Intelligence (PRICAI’08)
- For the paper: “Alternative formulations of the theory of evidence based on basic plausibility & commonality assignments”
- Marie Curie fellowship (2006), in conjunction with INRIA Rhone-Alpes, France
In addition, my former PhD student Suman Saha won the reading group prize at ICVSS 2015, the International Computer Vision Summer School. My MSc student Misbah Munir won in February 2017 the OBSEA (the Oxford Brookes Social Entrepreneur Awards) Try It Award to fund a proof of concept of her work. Anoher PhD student of mine, Gurkirt Singh, won a Best Reviewer Award at ICCV 2019, the top computer vision conference.
- Autonomous Driving and Intelligent Transport
- Health Innovation and Technology Trials (HITT)
- Visual Artificial Intelligence Laboratory (VAIL)
- MAESTRO Jr - Multi-sensing AI Environment for Surgical Task & Role Optimisation
- Artificial intelligence for autonomous driving
- Deep learning for complex activity detection in videos
- Epistemic Artificial Intelligence
- Knowledge Transfer Partnership with Createc
- Knowledge Transfer Partnership with Supponor
- Smart Autonomous Robotic Assistant Surgeon (SARAS)
- Some novel paradigms for analyzing human actions in complex videos
- Theory of mind at the interface of neuroscience and AI
Projects as Principal Investigator, or Lead Academic if project is led by another Institution
- Multi-sensing AI Environment for Surgical Task & Role Optimisation (led by Imperial) (01/09/2021 - 31/05/2023), funded by: Engineering & Physical Sciences Research Council (EPSRC), funding amount received by Brookes: £137,541
- Epistemic AI (01/03/2021 - 28/02/2025), funded by: European Commission, funding amount received by Brookes: £966,236
- Theory of mind at the interface of neuroscience and AI (10/02/2020 - 31/12/2023), funded by: Leverhulme Trust, funding amount received by Brookes: £136,743
- Deep Learning for Complex Activity Recognition (01/12/2019 - 30/11/2022), funded by: Huawei Technologies (UK) Co. Ltd, funding amount received by Brookes: £278,824
- SARAS (led by Universita Degli Studi Di Verona) (01/01/2018 - 31/12/2021), funded by: European Commission, funding amount received by Brookes: £455,865
Giunchiglia E, Khan S, Stoian M, Cuzzolin F, Lukasiewicz T, 'ROAD-R: the Autonomous Driving Dataset for Learning with Requirements'
Machine Learning [in press] (2023)
ISSN: 0885-6125 eISSN: 1573-0565Abstract Open Access on RADAR
Langley C, Cirstea B, Cuzzolin F, Sahakian BJ, 'Editorial: Theory of Mind in Humans and in Machines'
Frontiers in Artificial Intelligence 5 (2022)
eISSN: 2624-8212Abstract Published here Open Access on RADAR
Langley C, Cirstea B, Cuzzolin F, Sahakian BJ, 'Theory of Mind and Preference Learning at the Interface of Cognitive Science, Neuroscience, and AI: A Review'
Frontiers in Artificial Intelligence 5 (2022)
eISSN: 2624-8212Abstract Published here Open Access on RADAR
Singh G, Akrigg S, Di Maio M, Fontana V, Javanmard Alitappeh R, Saha S, Jeddisaravi K, Yousefi F, Culley J, Nicholson T, Omokeowa J, Khan S, Grazioso S, Bradley A, Di Gironimo G, Cuzzolin F, 'ROAD: The ROad event Awareness Dataset for Autonomous Driving'
IEEE Transactions on Pattern Analysis and Machine Intelligence [online first] (2022)
ISSN: 0162-8828 eISSN: 1939-3539Abstract Published here Open Access on RADAR
Samuel DJ, Cuzzolin F, 'Unsupervised Anomaly Detection for a Smart Autonomous Robotic Assistant Surgeon (SARAS) Using a Deep Residual Autoencoder'
IEEE Robotics and Automation Letters 6 (4) (2021) pp.7256-7261
eISSN: 2377-3766Abstract Published here
Ullah FUM, Obaidat MS, Muhammad K, Ullah A, Baik SW, Cuzzolin F, Rodrigues JJPC, Albuquerque VHC, 'An intelligent system for complex violence pattern analysis and detection'
International Journal of Intelligent Systems Online first (2021)
ISSN: 0884-8173 eISSN: 1098-111XAbstract Published here
Khan S, Muhammad K, Hussain T, Ser JD, Cuzzolin F, Bhattacharyya S, Akhtar Z, de Albuquerque VHC, 'DeepSmoke: Deep learning model for smoke detection and segmentation in outdoor environments'
Expert Systems with Applications 182 (2021)
ISSN: 0957-4174Abstract Published here
Buczynski W, Cuzzolin F, Sahakian B, 'A review of machine learning experiments in equity investment decision-making: why most published research findings do not live up to their promise in real life'
International Journal of Data Science and Analytics 11 (2021) pp.221-242
ISSN: 2364-415X eISSN: 2364-4168Abstract Published here
Cuzzolin F, Morelli A, Cîrstea B, Sahakian BJ, 'Knowing me, knowing you: theory of mind in AI'
Psychological Medicine 50 (7) (2020) pp.1057-1061
ISSN: 0033-2917 eISSN: 1469-8978Abstract Published here Open Access on RADAR
Leporini A et al, 'Technical and Functional Validation of a Teleoperated Multirobots Platform for Minimally Invasive Surgery'
IEEE Transactions on Medical Robotics and Bionics 2 (2) (2020) pp.148-156
ISSN: 2576-3202 eISSN: 2576-3202Abstract Published here Open Access on RADAR
Liu Z, Liu Y, Dezert J, Cuzzolin F, 'Evidence combination based on credal belief redistribution for pattern classification'
IEEE Transactions on Fuzzy Systems 28 (4) (2019) pp.618-631
ISSN: 1063-6706Abstract Published here Open Access on RADAR
Gong W, Cuzzolin F, 'A belief-theoretical approach to example-based pose estimation'
IEEE Transactions on Fuzzy Systems PP (99) (2017) pp.1-14
ISSN: 1063-6706Abstract Published here Open Access on RADAR
De Rosa R, Gori I, Cuzzolin F, Cesa-Bianchi N, 'Active Incremental Recognition of Human Activities in a Streaming Context'
Pattern Recognition Letters 99 (2017) pp.48-56
ISSN: 0167-8655Abstract Published here Open Access on RADAR
Cuzzolin F, Sapienza M, Esser P, Saha S, Franssen M, Collett J, Dawes H, 'Metric learning for Parkinsonian identification from IMU gait measurements'
Gait & Posture 54 (May 2017) (2017) pp.127-132
ISSN: 0966-6362 eISSN: 1879-2219Abstract Published here Open Access on RADAR
Cuzzolin F, 'Belief functions: Theory and applications (BELIEF 2014)'
International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems 72 (2016) pp.1-3
ISSN: 0888-613XPublished here Open Access on RADAR
Sapienza M, Cuzzolin F, Torr PHS, 'Learning discriminative space-time action parts from weakly labelled videos'
International Journal of Computer Vision 110 (1) (2014) pp.30-47
ISSN: 0920-5691Abstract Published here
Cuzzolin F, Sapienza M, 'Learning Pullback HMM Distances'
IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (7) (2014) pp.1483-1489
ISSN: 0162-8828Abstract Published here
Cuzzolin F, 'Lp consonant approximations of belief functions'
IEEE Transactions on Fuzzy Systems 22 (2) (2014) pp.420-436
ISSN: 1063-6706Abstract Published here Open Access on RADAR
Cuzzolin F, 'On the fiber bundle structure of the space of belief functions'
Annals of Combinatorics 18 (2) (2014) pp.245-263
ISSN: 0218-0006 eISSN: 0219-3094Abstract Published here Open Access on RADAR
Antonucci A, De Rosa R, Giusti A, Cuzzolin F, 'Robust classification of multivariate time series by imprecise hidden Markov models'
International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems 56 (Part B) (2014) pp.249-263
ISSN: 0888-613XAbstract Published here
Cuzzolin F, Mateus D, Horaud R, 'Robust temporally coherent laplacian protrusion segmentation of 3D articulated bodies'
International Journal of Computer Vision 112 (1) (2014) pp.43-70
ISSN: 0920-5691Abstract Published here
Cuzzolin F, 'On the relative belief transform'
International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems 53 (5) (2012) pp.786-804
ISSN: 0888-613XAbstract Published here Open Access on RADAR
Ozonoff A, Cuzzolin F, Snow P, 'Special issue on information fusion applications to human health and safety'
Information Fusion 13 (2) (2012) pp.102-104
ISSN: 1566-2535Abstract Published here Open Access on RADAR
Cuzzolin F, 'Credal semantics of Bayesian approximations in terms of probability intervals'
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 40 (2) (2010) pp.421-432
ISSN: 1083-4419Abstract Published here
Cuzzolin F, 'Geometry of relative plausibility and relative belief of singletons'
Annals of Mathematics and Artificial Intelligence 59 (1) (2010) pp.47-79
ISSN: 1012-2443Abstract Published here Open Access on RADAR
Cuzzolin F, 'The geometry of consonant belief functions: simplicial complexes of necessity measures'
Fuzzy Sets and Systems 161 (10) (2010) pp.1459-1479
ISSN: 0165-0114Abstract Published here Open Access on RADAR
Cuzzolin F, 'Three alternative combinatorial formulations of the theory of evidence'
Intelligent Data Analysis 14 (4) (2010) pp.439-464
ISSN: 1088-467XAbstract Published here Open Access on RADAR
Cuzzolin F, 'A geometric approach to the theory of evidence'
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 38 (4) (2008) pp.522-534
ISSN: 1094-6977Abstract Published here Open Access on RADAR
Memberships of professional bodies
I am a Reviewer for ERC - the European Research Council since 2017, Reviewer for the Italian Ministry of Scientific Research, and I am a Member of the Associate College of reviewers for EPSRC (2017-now). I am REF2021 external assessor for UoA 11 the University of Wolverhampton (as of August 2018). I have also reviewed grant applications for the Leverhulme Trust and the Vienna Research Group, Austria.
Membership of Editorial Boards and Societies
- Steering Committee member of the new Oxford Brookes Institute for Ethical Artificial Intelligence (Feb 2020-now)
- Oxford Clinical Allied Technology and Trials Services Unit (OxCATTS) Steering Group member (2019-now)
- Executive Committee member of the Huawei Technologies Canada – Simon Fraser University joint Visual Computing Research Lab (2018 - 2020)
- Associate Editor of the International Journal of Approximate Reasoning (2018 - now)
- Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems (impact factor 11.683) (Jan 2020 – now)
- Research Topic Editor for Frontiers in Artificial Intelligence: ‘Theory of Mind in Humans and in Machines’ (Oct 2020-now), with Barbara J. Sahakian and Bogdan-Ionut Cirstea
- Associate Editor of the IEEE Transactions on Fuzzy Systems (2013 - 2017)
- Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics C (Jan 2011 - March 2013)
- Guest Editor of Information Fusion (2009 - 2012)
- Four-term member of the Board of Directors of the Belief Functions and Applications Society (BFAS)
- Executive Editor of the Society for Imprecise Probabilities – Theory and Applications (SIPTA), 2017-2019
Organisation of Conferences and Workshops
I was the General Chair and Program Chair of the 3rd International Conference on the Theory of Belief Functions (BELIEF 2014), held in St. Hugh's college, Oxford, UK, September 26-28 2014.
I was in the Steering Committee (Program Chairs) of the joint SMPS-BELIEF 2018 international conference.
I was Co-organizer of WPMSIIP 2011 - 4th Int. Workshop on Principles and Methods of Statistical Inference with Interval Probability.
I was also the Lead Organiser of the following recent events:
- The MIDL 2020 SARAS endoscopic vision challenge for surgeon action detection (SARAS-ESAD 2020), July 9 2020
- The IJCAI 2021 Workshop on Continual semi-supervised learning (CSSL @ IJCAI 2021), August 19-20 2021
- The MICCAI 2021 Multi-domain Endoscopic Surgeon Action Detection (MESAD) challenge, September 27 2021
- The ICCV 2021 workshop: The ROAD challenge: event detection for situation awareness in autonomous driving, October 16, 2021
I will be Program Chair of the upcoming first International Conference on Continual Learning (ICCL 2022)
Membership of Technical Program Committees
I have served in the Technical Program Committee of some 150 international conferences, including the top venues in Artificial Intelligence, Machine Learning, Computer Vision and Uncertainty Theory.
- IJCAI (the International Joint Conference on Artificial Intelligence), 2016-2021;
- ECAI (the European Conference on Artificial Intelligence), 2018;
- NeurIPS (Neural Information and Processing Systems), 2018-2021 (the top machine learning venue);
- ICML (the International Conference on Machine Learning), 2018-2020;
- AAAI 2020-21 (the Association for the Advancement of Artificial Intelligence series of conferences);
- UAI (Uncertainty in Artificial Intelligence), 2014-2019 as Senior Program Committee member (Area Chair);
- BMVC (the British Machine Vision Conference) 2009-2020, as Area Chair 2016-19;
- ECCV (the European Conference on Computer Vision) 2020, as Area Chair;
- ICCV (the International Conference on Computer Vision), in 2021 as Area Chair;
- IEEE CVPR (Computer Vision and Pattern Recognition), 2016-now;
- SMC (the IEEE International Conference on Systems, Man, and Cybernetics) 2013-2020, Main Track.
Others major venues include FUSION - the International Conference on Information Fusion, IPMU - the Information Processing and Management of Uncertainty series of conferences; ACCV - The Asian Conference of Computer Vision; VISAPP (2006-2019) - International Conference on Computer Vision Theory and Applications; FLAIRS (2008-2018) - the Florida AI Research Society International Conferences; ISIPTA - the International Symposium on Imprecise Probabilities and Their Applications; ECSQARU - the European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty; BELIEF (2010-2022) - The International Conference on the Theory of Belief Functions; AVSS 2013-2014 - the IEEE International Conference on Advanced Video and Signal-Based Surveillance; IUKM 2010-2022 - the International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making.
Organisation of Tutorials, Special Issues and Special Sessions
- “Belief functions: A gentle introduction”, invited tutorial, Seoul National University, June 1 2018
- “Belief functions for the working scientist”, International Joint Conference on Artificial Intelligence (IJCAI-16), New York, July 2016
- “Belief functions for the working scientist”, Uncertainty in Artificial Intelligence (UAI) 2015, Amsterdam
- Special Issue “Selected papers from BELIEF 2014”, International Journal of Approximate Reasoning, 2015-16
- Special Issue “Information Fusion Applications to Human Health and Safety”, Information Fusion, Elsevier, Volume 13, Issue 2, 2012; Co-editors: Paul Snow and Al Ozonoff (Harvard University)
- Special Session: “Belief functions, Symbolic and Quantitative Approaches to Reasoning with Uncertainty” (ECSQARU 2015); Co-chair: Dr David Mercier
- Special Issue on “Effective Feature Fusion in Deep Neural Networks”, IEEE Transactions on Neural Networks and Learning Systems (upcoming); Co-editors: Yanwei Pang (Tianjin University), Fahad Shahbaz Khan (Inception Institute of Artificial Intelligence, UAE), Xin Lu (Adobe)
I was invited to give seminars at a host of national and international institutions, including Oxford University’s Department of Engineering (Feb 13 2018), Harvard University’s Department of Statistics (July 14 2016), Cambridge University’s Department of Engineering (March 2016), Microsoft Research Europe (2006), GeorgiaTech (2006), Pompeu Fabra University (2006), EPFL-IDIAP (2006), MIT (1999). In 2015 I was invited by the Oxford Martin School to join a select group of Oxford Academics to meet with former World Chess Champion Garry Kasparov and discuss some of the future challenges of AI. I was invited again in March 2017.
In recent years I was invited speaker or keynote speaker at a number of events:
- the CSA 2016 international conference (Algiers, Dec 2016);
- the 2017 BMW Knowledge Day (February 2017);
- the 4th Summer School on Belief Functions (Xian, China, July 2017);
- the Roadmap to Autonomous Surgery Workshop, Verona, Italy, Oct 31 2017;
- the Oxford Prospects Programme (St Cross and Regent’s colleges, Oxford, Jan 31/Jul 31 2018);
- the Ambassadors’ Roundtable on AI of the Anglo-Israel Association (Royal Society, London, Feb 27 2018);
- the Bayesian, Fiducial and Frequentist Workshop (BFF4), Harvard, May 2017;
- the Fifth Bayesian, Fiducial and Frequentist Workshop (BFF5), Ann Arbor, USA, May 6-9 2018;
- the 2nd Biennial Summer School on Surgical Robotics (COSUR 2018), Verona, Italy, July 10 2018
- the ICRA 2019 workshop “Next Generation Robotic Surgery: Seamless integration of Machine Learning, Knowledge Representation and Robotics within the operating rooms”, Montreal, Canada, May 2019
- the Hamlyn Symposium Workshop “Towards robotic autonomy in surgery”, London, June 23 2019
- the Cambridge Science Festival - Artificial Intelligence, the Human Brain and Neuroethics, March 2020 (cancelled because of Covid)
- DeepView: Global Multi-Target Visual Surveillance Based on Real-Time Large-Scale Analysis, A workshop of the IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS 2021), Nov 16 2021
Media and public engagement
- Article: Walk this way, “International Innovation", a Research Media magazine, January 2014
- UAI 2015 tutorial "Belief functions for the working scientist"
- “Towards machines that can read your mind”, Professorial Lecture, Jan 24 2018
- Harvard Statistics colloquia invited talk: Belief functions: past, present and future, July 14 2016
- Risk Group LLC: invited podcast on “Advances in Artificial Intelligence: Gesture and Action Recognition”
- “The 3,600 mile experiment: Parkinson's disease on the ocean” – MedicalXpress, June 25 2018
- “Row for Parkinson’s” – The West Australian, 7 July 2018
- “British Crew Rowing the Distance to Improve Understanding of Parkinson’s Disease”, Parkinson’s News Today, June 27 2018
- Venturefest Oxford: https://venturefestoxford.com/experts/the-crucial-role-of-theory-of-mind-tom-capabilities-in-developing-a-next-generation-human-centric-artificial-intelligence/
- SARAS Challenge – Best of MIDL 2020, Computer Vision News, August 2020
- CLVision Poster: "Avalanche: an End-to-End Library for Continual Learning"