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END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260517T153506Z
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:20260517T153506Z
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:20260517T153506Z
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:20260517T153506Z
DTSTART;VALUE=DATE-TIME:20260608T130000
DTEND;VALUE=DATE-TIME:20260608T140000
SUMMARY:WCPM\, Kevin Huang\, Warwick
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 Warwick\, 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 Warwick in summer
  2026.
LOCATION:
URL:
ATTACH:
CATEGORIES:WCPM
LAST-MODIFIED:20260420T085828Z
ORGANIZER;CN=Jin Kang:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T153507Z
DTSTART;VALUE=DATE-TIME:20260601T130000
DTEND;VALUE=DATE-TIME:20260601T140000
SUMMARY:WCPM\, Thomasina Ball\, Warwick
TZID:Europe/London
UID:20260601-8ac672c69da8d8e7019daa186609062e@warwick.ac.uk
CREATED:20260505T112726Z
DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: Mod
 elling mountain building: Wrinkles and creases in thin layers of viscopl
 astic fluid Abstract: Wrinkles or creases in the surface of a material a
 re indicative of compression. For example\, on Earth\, mountain ranges f
 ormed due to the plate tectonics exhibit regular spaced folds on the sur
 face. In this talk I will discuss some of the theoretical and experiment
 al approaches we have taken to describe the process of mountain building
  by modelling it as a viscoplastic fluid (a material with solid and flui
 d-like properties). Bio: Research Interests: Thomasina's research intere
 sts lie in mathematical modelling of fluid dynamical phenomena from obse
 rvations of laboratory experiments and the natural world around us. In p
 articular she is interested in the areas of: non-Newtonian rheologies\, 
 yield stress fluids\, gravity-driven flow\, geophysical flows\, instabil
 ities that arise from rheology contrasts\, fluid-structure interactions.
  Most relevant recent publications: Ball\, T. V. & Balmforth\, N. J. (20
 25) Non-axisymmetric patterns in floating viscoplastic films. J. Fluid M
 ech. 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 preprint
 s: https://warwick.ac.uk/fac/sci/maths/people/staff/tball/
LOCATION:L5\, Science Concourse
CATEGORIES:WCPM
LAST-MODIFIED:20260505T112726Z
ORGANIZER;CN=Jin Kang:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T153507Z
DTSTART;VALUE=DATE-TIME:20260518T130000
DTEND;VALUE=DATE-TIME:20260518T140000
SUMMARY:WCPM\, Paddy Royall\, Warwick
TZID:Europe/London
UID:20260518-8ac672c79d8bfbdd019daa14f5bc2c52@warwick.ac.uk
CREATED:20260514T125923Z
DESCRIPTION:Networking Lunch: Outside L5\, from 12:30pm - 1pm. Title: Pre
 dicting Nucleation: is it the end of the road for the second-largest dis
 crepancy in physics? Abstract (with images): Crystallisation is among th
 e most familiar physical phenomena of everyday life. One would quite rea
 sonably imagine that it has been long understood. And yet there are many
  basic unanswered questions. Here we will tackle two. Firstly\, we enqui
 re how quickly materials crystallise. Secondly we will consider which cr
 ystal lattice structure they form. Prediction of nucleation rates in fam
 iliar materials such as water remains very challenging. In such general 
 problems\, model systems play a crucial role\, as a benchmark of theory 
 and computer simulation. Alas\, the most studied material\, colloidal ha
 rd spheres\, exhibits a wild disagreement between experiment and numeric
 al prediction of 20 orders of magnitude\, which has been dubbed “the sec
 ond-largest discrepancy in physics” [1]. Since the experimental work rel
 evant to this discrepancy was carried out in the last millennium\, we ex
 pect that developments\, such as particle-resolved studies may shed ligh
 t on this phenomenon. Such experiments are amenable to analysis with hig
 her—order structural measures. This allows us to directly investigate wh
 ether Sir Charles Frank’s conjecture that “five-fold symmetry is abhorre
 nt to crystallisation”. It is [2]. We then investigate whether fivefold 
 symmetry might explain the hard sphere nucleation discrepancy. It doesn’
 t [1]. But with careful matching of state point between experiments and 
 simulation\, we do find agreement for the energy barriers to form pre-cr
 itical nuclei [3]. The second problem\, of which crystal lattice (polymo
 rph) a system chooses has important real-world consequences. For example
 \, following clinical trials and release onto the market of the anti-AID
 S drug Ritonavir\, an unknown polymorph formed\, which was not effective
 \, leading to withdrawal of the drug from the market. We have deduced th
 e mechanism of polymorph selection in simple model systems [4\,5]. We th
 en show how our method can be used to understand polymorph selection in 
 more complex systems with many competing polymorphs [6\,7] and 3d active
  colloids [8\,9]. [1] Royall CP et al\, Rev. Mod. Phys. 96 045003 (2024)
 . [2] Taffs J. and Royall CP\, Nature Commun. 7 13225 (2016). [3] Kürten
  L\, Castagnède A\, Smallenburg F\, Royall CP\, Science Advances 12\, ea
 ec8906 . [4] Gispen W\, Coli GM.\,van Damme R\, Royall CP and Dijkstra M
 \, ACS Nano 17 8807–8814 (2023). [5] Royall CP\, J. Chem. Phys. 164 0249
 07 (2026). [6] Skipper K\, Moore FJ and Royall CP\, J. Chem. Phys. 161 1
 44308 (2024). [7] Wu X\, Skipper K\, Yang Y\, Moore FJ\, Meldrum FC\, an
 d Royall CP\, Soft Matter 21 2787-2802 (2025). [8] Sakaï N\, Skipper K\,
  Moore FJ\, Russo J and Royall CP\, Soft Matter\, 21 5204-5213 (2025). [
 9] Chao X\, Skipper K\, Royall CP\, Henkes S\, Liverpool TB\, Phys. Rev.
  Lett. 134 018302 (2025). Bio:Professor Paddy Royall is a leading resear
 cher in soft condensed matter physics and a CNRS Director of Research at
  ESPCI Paris\, and is currently a Leverhulme Visiting Professor at the U
 niversity of Warwick. His work focuses on understanding the microscopic 
 origins of complex material behaviour\, particularly in areas such as th
 e glass transition\, crystallisation\, and amorphous materials\, combini
 ng advanced experiments with computational approaches.
LOCATION:L5\, Science Concourse
CATEGORIES:WCPM
LAST-MODIFIED:20260514T125923Z
ORGANIZER;CN=Jin Kang:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260517T153507Z
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