Overview
You can find the programme for the conference here.
The Maxwell Society presents its 71st annual conference which this year is on the theme of information. The conference will feature five talks on topics ranging from black holes to quantum computing and machine learning, and you can also expect networking opportunities, socials, and of course tea and coffee on both days! The first day will end with a murder mystery and a complimentary afternoon tea (tea, cakes, scones, fancies etc) andthe second day will finish with a pub-based social.
Keep reading to find out more information about our speakers!
____________________________________________________________
Prof Chris Timpson (University of Oxford)
Title: Is the concept of information physically fundamental?
Is it time to move on from materialism in quantum, towards an immaterial front? Could the study of quantum information reveal new things about quantum mechanics? Or could it resolve ghosts of times past? Can you “know” anything at all?
Prof. Chris Timpson joins us from the University of Oxford to talk about this and give us an introduction to the most fundamental aspects of the philosophy of Quantum Information Theory.
Check him out at: https://www.bnc.ox.ac.uk/about-brasenose/academic-staff/395-dr-christopher-timpson-dean
Dr Ben Criger (Cambridge Quantum Ltd)
What is the next frontier in computation? How can you make a difference as a physicist or a mathematician?
Joining us is Cambridge Quantum Computing's Ben Criger, at the meeting point of Physics, Mathematics and Computer Science, to discuss the new age of information transmission. We bring to you how Quantum Information is revolutionising the world, through evolved, more advanced, and highly efficient underlying quantum mechanical systems.
Check him out at: https://online-learning.tudelft.nl/instructors/ben-criger/
Prof Ian Ford (University College London)
Title: Maxwell’s Demon and the management of ignorance in stochastic thermodynamics
What if information could be turned into energy?
Bringing to you, Prof. Ian Ford of the Dept. of Physics & Astronomy at UCL, to talk about Maxwell’s infamous demon.
A 115-year-old demon, so powerful that it ALMOST broke entropy….. yes! A system where entropy begins to decrease…. And a possible solution to this is in the form of information entropy.
Check him out at: https://www.ucl.ac.uk/physics-astronomy/people/professor-ian-ford
Check out the article that this talk will be based on: https://www.tandfonline.com/doi/full/10.1080/00107514.2015.1121604
Bilyana Tomova (University of Cambridge)
Can a black hole erase information from the universe?
Find out with us, as we share the room with the University of Cambridge’s Bilyana Tomova, a PhD student at the Applied Mathematics department. She will discuss the Black Hole Information Paradox, first discovered by the person that revolutionised astronomy, Stephen W. Hawking! Have we found a glitch in the matrix? A point where the notorious quantum wave function is violated? Or…
Check her out at: https://www.maths.cam.ac.uk/person/bt363
Emma Dann (University of Cambridge & Wellcome Sanger Institute)
Title: Best practices and open challenges in single-cell genomics data analysis
Ever wondered how a single cell can hold a complete set of information? Can editing of information take place through genomics?
Emma Dann, a PhD student at the Wellcome Sanger Institute and the University of Cambridge joins us as we discuss analysis ideas in Single-Cell genomics. She has a longstanding interest in understanding global principles of gene regulation and protein interactions, with application to immunology. Her programme is focused on cell-atlasing and cellular genetics.
Abstract: Single-cell RNA sequencing (scRNA-seq) and other single-cell genomics technologies have become the norm to investigate cell-to-cell heterogeneity. Collective research efforts have generated “cell atlases” that represent reference maps of the great diversity of cell states in tissues. The growth in scale of single-cell datasets has gone hand-in-hand with the development of computational methods to analyse this data in an efficient and statistically sound manner.
In this talk, I will discuss best practices and open challenges in single-cell genomics data analysis. I will give an overview of commonly used unsupervised learning techniques used for pre-processing, identification and characterization of cell types and inference of differentiation trajectories. I will then discuss open challenges in the field, including multi-condition comparative analyses and strategies to integrate data from different single-cell molecular measurements and imaging technologies.
Check her out at: https://emdann.github.io
____________________________________________________________
IMPORTANT INFO:
Once you’ve booked your tickets, please fill out the dietary requirement form below for us to be able to provide you with the best quality service during the event.
https://forms.office.com/Pages/ResponsePage.aspx?id=FM9wg_MWFky4PHJAcWVDVmGUy5DtIt9PmB_eEZy2vM1UMFFYTERSMVRVQVBKN1ZJS1E0ODI0MTVVUC4u
Please note: We require a negative LF-test taken within 24 hours of the event. Tickets are non-refundable.