BEGIN:VCALENDAR PRODID:-//SiteBuilder 2//University of TV ITS Web Team//EN VERSION:2.0 CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Predictive Modelling » Seminars X-WR-TIMEZONE:Europe/London X-LIC-LOCATION:Europe/London BEGIN:VTIMEZONE TZID:Europe/London LAST-MODIFIED:20201010T011803Z TZURL:http://tzurl.org/zoneinfo/Europe/London X-LIC-LOCATION:Europe/London X-PROLEPTIC-TZNAME:LMT BEGIN:STANDARD TZNAME:GMT TZOFFSETFROM:+000115 TZOFFSETTO:+0000 DTSTART:18471201T000000 END:STANDARD BEGIN:DAYLIGHT TZNAME:BST TZOFFSETFROM:+0000 TZOFFSETTO:+0100 DTSTART:19160521T020000 RDATE:19170408T020000 RDATE:19180324T020000 RDATE:19190330T020000 RDATE:19200328T020000 RDATE:19210403T020000 RDATE:19220326T020000 RDATE:19230422T020000 RDATE:19240413T020000 RDATE:19270410T020000 RDATE:19300413T020000 RDATE:19330409T020000 RDATE:19340422T020000 RDATE:19350414T020000 RDATE:19380410T020000 RDATE:19390416T020000 RDATE:19400225T020000 RDATE:19460414T020000 RDATE:19470316T020000 RDATE:19480314T020000 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END:STANDARD BEGIN:STANDARD TZNAME:GMT TZOFFSETFROM:+0000 TZOFFSETTO:+0000 DTSTART:19960101T000000 END:STANDARD BEGIN:STANDARD TZNAME:GMT TZOFFSETFROM:+0100 TZOFFSETTO:+0000 DTSTART:19961027T020000 RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260426T103551Z DTSTART;VALUE=DATE-TIME:20260427T130000 DTEND;VALUE=DATE-TIME:20260427T140000 SUMMARY:WCPM: Savvaki Savva\, Morgan Advanced Materials TZID:Europe/London UID:20260427-8ac672c49da8d90f019daa0f15040113@warwick.ac.uk CREATED:20260420T152249Z DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: Mod elling in Industry: Case Studies from Ceramics Manufacturing at Morgan A bstract: This seminar presents an industrial perspective on modelling th rough a selection of case studies from ceramics manufacturing at Morgan. I will begin with a brief introduction to Morgan and my role within its modelling activities\, providing context on how modelling fits into a b roader industrial R&D and manufacturing environment. The main focus of t he talk will be two modelling projects\, chosen to illustrate the differ ent roles models can play in industrial decision‑making. Rather than emp hasizing technical detail\, the discussion will highlight how these proj ects were framed\, the constraints under which the modelling was carried out\, and some of the practical challenges encountered\, including data limitations\, uncertainty\, and trade‑offs between model fidelity and u sability. The aim is to give an insight into how modelling research proj ects typically operate in industry\, and how this differs from an academ ic setting. Bio: Savvaki Savva is a Senior Materials Scientist at Morgan Advanced Materials\, with extensive experience in the ceramics and adva nced materials industry. Her work focuses on research and development\, with particular expertise in additive manufacturing\, materials chemistr y\, and process optimisation. Savvaki has built a strong career translat ing fundamental materials science into industrial applications. Since jo ining Morgan Advanced Materials in 2017\, she has progressed from Materi als Scientist to Senior Materials Scientist\, contributing to the develo pment and improvement of high-performance ceramic materials and manufact uring processes. She previously worked at Doncasters Precision Castings\ , where she specialised in process control and materials troubleshooting within ceramic core and shell systems\, driving process improvements in an industrial production environment. Savvaki completed her PhD in Mate rials Chemistry at the University of Birmingham\, where her research foc used on developing novel materials for the removal of strontium from nuc lear waste. Her work explored ion exchange materials\, bridging academic research with real-world nuclear industry challenges\, including collab oration with the National Nuclear Laboratory. With a strong foundation a cross chemistry\, physics\, and materials science\, Savvaki brings a pra ctical\, industry-focused perspective to advanced materials research and innovation. LOCATION:L5\, Science Concourse CATEGORIES:WCPM LAST-MODIFIED:20260420T152249Z ORGANIZER;CN=Jin Kang: END:VEVENT BEGIN:VEVENT DTSTAMP:20260426T103551Z DTSTART;VALUE=DATE-TIME:20260511T130000 DTEND;VALUE=DATE-TIME:20260511T140000 SUMMARY:WCPM: Samuel Cooper\, Imperial TZID:Europe/London UID:20260511-8ac672c49da8d90f019daa126b06011b@warwick.ac.uk CREATED:20260422T124603Z DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: Sma ll Features\, Big Impact: Designing at the Microscale with Generative AI Abstract: The microscale features of porous battery electrodes strongly influence how fast they charge and how long they last. These features a re governed by manufacturing parameters such as temperature and pressure \, yet the relationship between processing and the resulting microstruct ure remains extremely difficult to predict using physics-based simulatio ns. In this talk\, I will demonstrate how generative AI tools\, develope d by my team at Imperial College London\, have unlocked powerful new cap abilities for microstructural characterisation and design\, such as the generation of 3D data from a single 2D image. I will also share our work on a new workflow for the characterisation and simulation of graded ele ctrodes\, which are common in commercial cells. Finally\, I will present my teams most recent work on vision and language foundation models\, in particular exploring who they conceptualise scientific concepts and how they can be used in agentic workflows. Bio: Dr Sam Cooper leads the TLD R group at Imperial College London who focus on the application of AI to materials science. Recently publications have focused on the use of gen erative AI to create 3D microstructural data from a 2D image [1]\, condi tionalized models to map processing parameters to the microstructure of battery electrodes [2]\, and the representation of scientific concepts i nside LLMs [3]. Dr Cooper was recently awarded a £2M EPSRC Open Plus Fel low in AI for Materials Science with Deep Reproducibility. In 2024 he sp un-out a company\, www.polaron.ai\, to bring IP developed at Imperial to manufacturers around the world. Polaron were the winners of the inaugur al Manchester prize and recently raised an $8M seed round. In 2017\, Dr Cooper created the online course “Mathematics for Machine Learning” on C oursera which has since been taken by over 700\,000 learners. [1] https: //www.nature.com/articles/s42256-021-00322-1 [2] https://www.cell.com/ma tter/fulltext/S2590-2385(24)00446-6 [3] https://pubs.rsc.org/en/content/ articlelanding/2025/dd/d5dd00374a LOCATION:L5\, Science Concourse CATEGORIES:WCPM LAST-MODIFIED:20260422T124603Z ORGANIZER;CN=Jin Kang: END:VEVENT BEGIN:VEVENT DTSTAMP:20260426T103551Z DTSTART;VALUE=DATE-TIME:20260615T130000 DTEND;VALUE=DATE-TIME:20260615T140000 SUMMARY:WCPM\, Sam Livingstone\, UCL TZID:Europe/London UID:20260615-8ac672c49da8d90f019daa204e20016d@warwick.ac.uk CREATED:20260420T090217Z DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: TBC Abstract: TBC Bio: Sam is an associate professor at University College London (UCL). In his research he uses tools from probability and mathema tical analysis to study algorithms in Statistics and Machine Learning. T he field is often called CSML. He can also do some more methodological w ork in probabilistic modelling\, particularly for health applications (s ee his research page for more).https://samueljlivingstone.wixsite.com/we bpage He currently serves as associate editor for the journal Biometrika . Until Oct 2024 he held an EPSRC New Investigator Award entitled 'Robus t and scalable Markov chain Monte Carlo for heterogeneous models'. In 20 21he became the first UK recipient of the Blackwell--Rosenbluth award fr om the International Society for Bayesian Analysis. He joined the depart ment of Statistical Science in January 2018\, after a postdoc at the Uni versity of Bristol\, under Christophe Andrieu\, as part of the i-like pr oject\, and before that a PhD at UCL\, supervised by Mark Girolami and A lex Beskos. He believes in Stigler's law of eponymy\, and that the conce pt of multiple discovery/simultaneous invention is more closely aligned with the reality of scientific research than the heroic theory of invent ion that is dominant in popular culture. That being said\, I still have a romantic view of academic life and strive for originality in his work. You can understand some of his thoughts on research from this podcast e pisode: Betancourting Disaster Round 13: Transitioning Between Statistic al Theory and Practice | Patreon. LOCATION: URL: ATTACH: CATEGORIES:WCPM LAST-MODIFIED:20260420T090217Z ORGANIZER;CN=Jin Kang: END:VEVENT BEGIN:VEVENT DTSTAMP:20260426T103551Z DTSTART;VALUE=DATE-TIME:20260629T130000 DTEND;VALUE=DATE-TIME:20260629T140000 SUMMARY:WCPM\, Loïc Lannelongue\, Cambridge TZID:Europe/London UID:20260629-8ac672c49da8d90f019daa254b71025d@warwick.ac.uk CREATED:20260422T085417Z DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: The (environmental) sustainability challenge of modern computing & AI Abstr act: From genetic studies and astrophysics simulations to AI\, scientifi c computing has enabled amazing discoveries—and there's no doubt it will continue to do so. At the same time\, the resource usage (energy\, wate r) and environmental impacts of digital (research) infrastructures are b ecoming impossible to ignore given the urgency of the climate crisis. So what can we all do about it? And as scientists\, should we even be thin king about this? We'll break down how computing activities impact the en vironment\, debate our collective responsibility to tackle it\, and disc uss the latest efforts of the Cambridge Sustainable Computing Lab to emp ower researchers to understand and mitigate their environmental impacts. Through the lens of the GREENER principles for environmentally sustaina ble science\, we'll explore the challenges the research community needs to overcome to create real change in this space. It will also be a chanc e to highlight how the Green DiSC certification framework can support sc ientists and institutions in making their research more sustainable. Bio : Dr Loïc Lannelongue is an Assistant Research Professor in Computer Sci ence at the University of Cambridge\, where he also serves as Bye-Fellow and Director of Studies in Computer Science (Part II) at Jesus College Cambridge. His work sits at the intersection of computing\, sustainabili ty\, and responsible innovation. Dr Lannelongue specialises in environme ntally sustainable computing\, with a particular focus on understanding and reducing the environmental impact of modern computational practices\ , including artificial intelligence. His research takes a multi-faceted approach\, combining technical development\, behavioural insights\, and policy engagement to drive more sustainable scientific workflows. His ac ademic interests include developing tools to monitor and reduce the carb on footprint of scientific computing\, contributing to sustainability fr ameworks and policy\, and exploring the ethical implications of modern s cience and AI. In parallel\, he works in radiogenomics\, applying machin e learning to integrate genomics and medical imaging data to improve und erstanding of cardiovascular disease. Through his research and teaching\ , Dr Lannelongue is committed to advancing a more sustainable and respon sible future for computational science. Webpage: https://www.jesus.cam.a c.uk/people/loic-lannelongue LOCATION: CATEGORIES:WCPM LAST-MODIFIED:20260422T085417Z ORGANIZER;CN=Jin Kang: END:VEVENT BEGIN:VEVENT DTSTAMP:20260426T103551Z DTSTART;VALUE=DATE-TIME:20260608T130000 DTEND;VALUE=DATE-TIME:20260608T140000 SUMMARY:WCPM\, Kevin Huang\, TV TZID:Europe/London UID:20260608-8ac672c59d8bfea7019daa1cd0024e12@warwick.ac.uk CREATED:20260420T085828Z DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: TBC Abstract: TBC Bio: Kevin is a postdoctoral research fellow funded by th e Engineering and Physical Sciences Research Council (EPSRC) through the ProbAI Hub. They are currently based at the University of TV\, wor king with Gareth Roberts\, and collaborate with Boris Hanin at Princeton University. They completed a PhD in machine learning at the Gatsby Comp utational Neuroscience Unit\, University College London\, under the supe rvision of Peter Orbanz and Morgane Austern. During this time\, they wer e also a visiting researcher with the LIPS group at Princeton Computer S cience\, hosted by Ryan P. Adams. Prior to this\, they completed both th eir undergraduate and master’s degrees in mathematics at the University of Cambridge. Their research lies at the intersection of machine learnin g theory\, probability\, and statistics. They study the emergence of uni versal structures in large-scale stochastic systems\, drawing on tools f rom random matrix theory\, high-dimensional statistics\, symmetry-based inference\, and stochastic optimisation. Alongside this theoretical work \, they increasingly engage with applied challenges\, particularly aroun d scaling laws in neural networks\, AI for scientific discovery\, and th e robustness and safety of machine learning models. For the 2025–2026 ac ademic year\, he is co-organising the ProbAI online seminar series and w ill lead the ProbAI Theory of Scaling Laws Workshop at TV in summer 2026. LOCATION: URL: ATTACH: CATEGORIES:WCPM LAST-MODIFIED:20260420T085828Z ORGANIZER;CN=Jin Kang: END:VEVENT BEGIN:VEVENT DTSTAMP:20260426T103551Z DTSTART;VALUE=DATE-TIME:20260601T130000 DTEND;VALUE=DATE-TIME:20260601T140000 SUMMARY:WCPM\, Thomasina Ball\, TV TZID:Europe/London UID:20260601-8ac672c69da8d8e7019daa186609062e@warwick.ac.uk CREATED:20260420T085338Z DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: TBC Abstract: TBC Bio: Research Interests: Thomasina's research interests l ie in mathematical modelling of fluid dynamical phenomena from observati ons of laboratory experiments and the natural world around us. In partic ular she is interested in the areas of: non-Newtonian rheologies\, yield stress fluids\, gravity-driven flow\, geophysical flows\, instabilities that arise from rheology contrasts\, fluid-structure interactions. Most relevant recent publications: Ball\, T. V. & Balmforth\, N. J. (2025) N on-axisymmetric patterns in floating viscoplastic films. J. Fluid Mech. 1007. Ribinskas\, E.\, Ball\, T. V.\, Penney\, C. E.\, & Neufeld\, J. A. (2024) Scraping of a viscoplastic fluid to model mountain building. J. Fluid Mech. See her Publications page for a full list with preprints: ht tps://warwick.ac.uk/fac/sci/maths/people/staff/tball/ LOCATION:L5\, Science Concourse URL: ATTACH: CATEGORIES:WCPM LAST-MODIFIED:20260420T085338Z ORGANIZER;CN=Jin Kang: END:VEVENT BEGIN:VEVENT DTSTAMP:20260426T103551Z DTSTART;VALUE=DATE-TIME:20260518T130000 DTEND;VALUE=DATE-TIME:20260518T140000 SUMMARY:WCPM\, Paddy Royall\, TV TZID:Europe/London UID:20260518-8ac672c79d8bfbdd019daa14f5bc2c52@warwick.ac.uk CREATED:20260420T084953Z DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: TBC Abstract: TBC Bio: TBC LOCATION:L5\, Science Concourse URL: ATTACH: CATEGORIES:WCPM LAST-MODIFIED:20260420T084953Z ORGANIZER;CN=Jin Kang: END:VEVENT BEGIN:VEVENT DTSTAMP:20260426T103551Z DTSTART;VALUE=DATE-TIME:20260622T130000 DTEND;VALUE=DATE-TIME:20260622T140000 SUMMARY:WCPM\, Ludovic Berthier\, ESPCI TZID:Europe/London UID:20260622-8ac672c79d8bfbdd019daa22fb6c2c96@warwick.ac.uk CREATED:20260420T090512Z DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: TBC Abstract: TBC Bio: Ludovic Berthier is a Directeur de Recherche at the CNRS\, based at the Laboratoire Gulliver at ESPCI Paris. He is an intern ationally recognised leader in statistical physics\, specialising in the theory and simulation of complex\, disordered systems. His research spa ns a wide range of topics at the intersection of physics and materials s cience\, including non-equilibrium statistical mechanics\, soft matter a nd complex fluids\, and the physics of supercooled liquids and glasses. He has made particularly influential contributions to understanding the glass transition\, amorphous solids\, and jamming phenomena\, as well as emerging areas such as active and biological matter. Ludovic’s work com bines theoretical insight with advanced computational methods to uncover universal behaviours in high-dimensional and disordered systems. He has authored numerous high-impact publications in leading journals such as Nature Materials\, Physical Review Letters\, Physical Review X\, and PNA S\, and has contributed to major review articles shaping the field\, inc luding on yielding in amorphous solids and machine learning approaches t o glassy systems. Through his research\, he continues to push the bounda ries of how we understand and design complex materials\, both in and out of equilibrium. Find out more here: https://ludovicberthier.github.io/ LOCATION: URL: ATTACH: CATEGORIES:WCPM LAST-MODIFIED:20260420T090512Z ORGANIZER;CN=Jin Kang: END:VEVENT END:VCALENDAR