Cellular programmes drive the state transitions, identity and function of cells. Breakdown of these programmes can lead to cell death and the development of disease. But the external manipulation of these programmes can allow for the fine control over cell identity, with the potential to reverse cell fate through cell reprogramming. Despite experimental successes, mathematical models for predicting cell transitions and identity remain elusive. This is partly due to the complexity of cellular regulation, which involves processes across multiple time and organisational scales. It also stems from a disconnect between cell biologists’ and theorists’ values and goals.
We urgently need theoretical models to catch up with experimental observations so that we can make this qualitative field more predictive. This one-day symposium will be a call to arms, bringing together researchers from physics, mathematics, machine learning and cell biology. It is hosted by the London Institute for Mathematical Sciences and the cell-coding company Bit.Bio. The event will take place in the Royal Institution’s iconic Lecture Theatre, followed by drinks and discussion. It will also inaugurate the move of the London Institute into the Royal Institution building.
Staying safe during COVID-19
The symposium is in person and will comply with the COVID-19 policies of the government and the Royal Institution. The London Medical Laboratory will offer COVID-19 rapid testing. The small, select group of attendees will have access to the Royal Institution’s large Lecture Theatre, providing ample space to distance.

A one-day, in-person symposium on theoretical models of cell programming and their application at the Royal Institution’s iconic Lecture Theatre.

Mathematics of cell programming

String theory—with its cornerstones of supersymmetry and extra space-time dimensions—has been a muse to pure mathematics. The discipline has provided novel methods of attack for a myriad of mathematical problems: from enumerative geometry to Moonshine, from quantum invariants to mock modular forms. Central to string theory is the study of Calabi-Yau manifolds, which serve as a beacon to such important investigations as compactification, mirror symmetry, moduli space and duality.
In this talk, Yang-Hui reviews how the problem of string phenomenology led physics first to algebraic and differential geometry, then to computational geometry, and now to data science and AI. How did this pencil-and-paper driven field become increasingly suited to computational techniques? Within the playground of the Calabi-Yau landscape, accumulated over four decades by physicists, mathematicians and computer scientists, He shows how the latest techniques in machine-learning can help explore problems of physical and mathematical interest. This talk is a taster of his book The Calabi-Yau Landscape: from Geometry, to Physics, to Machine-Learning.

In this in-real-life only event, Yang Hui talks about how string phenomenology has led from differential geometry to computational geometry and now to machine learning.


Superstrings, Calabi-Yau manifolds and machine learning

The London Institute's Christmas party was a case of swine before pearls. Postdoc Alexander Mozeika provided the swine, in the form of a small pig from his Camden butcher, which was roasted in the fireplace. The pearls came later, courtesy of Institute alumnae Antonia Tingey and Bethia Beadman, supported by office manager Victoria Harrison. Lobbyist Vernon Hunte from the PR firm April Six got in the spirit of things with a dose of his stand-up comedy. The offspring of a Trinidadian and an Italian, Vernon calls himself a "pasta-farian".
Late in the evening, research associate Robert Bywater expressed his approval by gnawing on a trotter. Meanwhile, graphic designer Daniel Eris proclaimed that the world is swamped with mediocrity—apart from the beast and booze, which were both excellent. Beer and wine flowed freely, but the whisky proved elusive. It was kept in a Klein bottle decanter, a three-dimensional object with no interior. A Klein bottle can be constructed at home by gluing together two Möbius strips along their edges. In the party invitation, it was drawn entirely mathematically by Robert Farr.

The London Institute marks the year’s successes at its Yuletide Winterfest, from 4pm on Friday 11 December—if it can get the spirits out.

Yuletide Winterfest

Biological systems are incredibly complex, involving interactions across multiple time and length scales. Gene regulation alone involves many molecular species playing specific roles, structural changes in the epigenome and intercellular forces and signalling, all within the chaotic and noisy cellular environment. Despite this complexity, gene regulation gives rise to multicellular organisms where each cell type is robust to genetic diversity and mutations. The genetic code, logic and computation within the cell is, therefore, something we could learn a great detail from. Understanding these processes would not only pave a way for the design of more efficient therapies and revolutionise personal medicine, but enable the development of biological machines.
To make ground towards these end goals we must develop the field of biology, which has traditionally been based on observation, into a predictive science like physics and mathematics. How do we do this? Do we utilize the explosion of big data and the omics revolution to draw inference on experimental results? Or is a ground-up mathematical approach needed to create models that capture the necessary amount of detail without over complicating or simplifying the situation? Likely, it will need a combination of the two techniques. 
Many of the modelling tools we have at our disposal may not currently be up to scratch though. The toolbox of mathematics and physics was largely developed for systems in equilibrium. Thus, these tools often fail in the messy world of biology. This event aims to bring scientists together to discuss promising and novel techniques for modelling cell biology.

We’re bringing mathematicians and biologists together to discuss novel techniques for modelling cell biology on Wednesday, 16th September.

Mathematics of biological computation and logic

Until recently, the idea that developmental biology was a one-way process was widely accepted. The advent of cell reprogramming tore this apart, revealing that cells can retain the ability to change identity. Given the complexity of genetic and cellular processes across multiple organizational length scales, the mechanisms driving cell fate are still obscure. Following our recent <a href="https://lims.ac.uk/decoding-cell-programming/">partnership with Bit.Bio</a>, we are building theoretical models and methods of inference to shed a light on the programmes piloting cellular function. We’re also recruiting theorists in <a href="https://lims.ac.uk/careers/postdocs-in-the-theory-of-cell-programming/">cell programming</a> and <a href="https://lims.ac.uk/postdoc-in-machine-learning-and-inference">machine learning</a>.
In this event, we investigate theoretical approaches to describe and predict cell identity, shaped by experimental innovations at Bit.Bio. Applied mathematician and LIMS postdoc Ryan Hannam talks about building models of gene regulation and cell identity grounded in biological fact. Cell coding company Bit.Bio discusses their breakthrough technology, followed by another speaker we are recruiting; if you want to talk, email Ryan at rh@lims.ac.uk. After, there is general discussion on how to accelerate this moonshot mission.
Staying safe at LIMS during COVID-19
The London Institute has taken all necessary actions to ensure it complies with the government’s guidance on managing the risk of COVID-19 at the workplace. We are fortunate to have a building with sufficient space to keep people appropriately separated. If you have questions, please contact Ben Lynch at bl@lims.ac.uk.

Physicists and biologists discuss theoretical models of cell programming and reprogramming, shaped by experimental innovations at Bit Bio.

Reprogramming the cell

How useful is mathematical modelling in biology? Given the complexity of genetic and cellular processes across multiple organizational length scales, biology has eluded a rounded description in terms of a handful of fundamental equations. But there is compelling evidence that this intricacy masks elegant underlying structure: the nominal information content of (coding) DNA, the plasticity of early cell identity, and the adaptive immune system.
In this event, we investigate the state-of-the-art for using our ever-increasing mathematical toolbox to describe and predict biological processes with comparatively simple models. Mark Kotter, a stem cell biologist and founder & CEO of Bit Bio, discusses a unique opportunity to systematically interrogate the OS of human cell programming. Physicist and LIMS Fellow Ton Coolen describes mathematical models of gene regulation and epigenetic programming. Physicist and LIMS postdoc Alexander Mozeika talks about the statistical physics of the adaptive immune response and high-dimensional statistical inference. LIMS director and physicist Thomas Fink describes theoretical approaches to understanding the dynamics of network motifs and larger regulatory networks. This is followed by discussion on whether we have reached a tipping point where the mathematical sciences can help unleash fundamental insights into the operating system of life.

Scientists discuss the potential of mathematical modelling in biology across problems in cell programming, immunology and gene regulation.


Modelling in biology

Collective human behaviour describes emergent behaviour when individuals are influenced by the group to which they belong. The focus is often on behaviour that violates laws and social norms. This can range from the innocuous, such as fashion fads, to more serious instances, such as an anomalous voting or disproportionate responses to stress. For instance, it is now widely believed that Cambridge Analytica influenced both the US and UK democratic processes. In an era of social media storms and political demagoguery, understanding the workings of group dynamics, which can be hard to predict, has become increasingly urgent.
In this event, physicist Gioia Boschi from Kings College London explores opinion dynamics with emergent collective memory; physicist Carmen Cabrera Arnau from University College London discusses the dynamics of road accidents in urban areas; and mathematician Zahra Jafari from University College London talks about migration flows. After the talks, there is a general discussion on the scope for turning collective human behaviour into a quantitative science. Everyone is welcome.

Mathematicians and social scientists discuss quantitative models of group dynamics and emergent behaviour on 30 Jan from 6:30. All welcome.

Modelling collective human behaviour

How we go about solving a problem depends on how far into the future it is. When the problem is around the corner, we tend to react to it. But when it’s a long time away, we seek to transform it, putting to use new opportunities that arise in the interim. In other words, on short timescales we act as if our landscape is fixed, but on long timescales we try to shape our landscape so as to allay the concern. Understanding how to balance these strategies can help us manage distant threats, such as man-made and environmental catastrophes. When multiple people act together to shape the future with the right dynamical rules in place, the path to innovative solutions can be fast-forwarded – even in the absence of explicit cooperation. We call this process collective innovation.
In this dinner hosted by the BCG Henderson Institute, we discuss strategies for acting on multiple timescales, how to respond to distant threats and collective imagination. Participants include Brian Arthur, Thomas Fink, Simon Levin, Dan Levinthal, Mihnea Moldoveanu, Michael Nielsen and Martin Reeves, as well as industry practitioners.

A dinner and discussion about collective imagination, strategies for acting on multiple timescales and how to respond to distant threats.

Science of Business IV

Advanced machine learning algorithms provide a powerful set of tools for solving important real-world problems. As machine learning technology improves, these algorithms are becoming responsible for ever more critical decisions. But when they fail in unexpected ways, the consequences can be devastating and potentially lead to cascading failure. 
In this talk, Marc Warner, the CEO and cofounder of AI research company Faculty, talks about how we should manage AI safety both individually and on a collective scale. Clearing a path through the vacuous bullshit that the future of AI tends to accumulate, his conclusions are grounded in Faculty’s scientific research to make AI safe now and in the future. The talk is followed by a general discussion on how to ensure that AI and automated decision-making will be a net positive for businesses and society.

Marc Warner talks about how we should manage the safety of embedded artificial intelligence both individually and on a collective scale. 

Making sure Skynet behaves itself

The collective action problem describes a public good for which the benefits cannot be excluded to those who don’t contribute to it. When the benefits of the good are only realised by the next generation, as is the case with fighting climate change, the problem is compounded by the difficulties of long-term forecasting. But the situation is even more complex, because human innovation, which takes place in an expanding space of technological building blocks, is inherently hard to describe, much less predict.
In this dinner at the London Institute, we discuss innovation, technological change and new ways to combat climate change. Physicist and London Institute director Thomas Fink discusses speeding up innovation as an alternative to our current focus on environmental preservation. Technology expert and complex systems founder Doyne Farmer talks about how empirical regularities over past technological change can foretell the rate of change in the future. Building on these ideas, National Medal of Science winner Simon Levin discusses the collective action problem in climate change and how to overcome it.

A dinner and discussion about speeding up innovation, forecasting technological change and the collective action problem in climate change.

Science of Business III

Tatratea: a Slovakian tea-based liqueur. Ghorme sabzi: an Iranian kidney bean stew. Spaghetti alla puttanesca: Italian pasta with anchovies, olives and capers. These are some of the delicacies, each particular to their country of origin, contributed by everyone who attended the London Institute’s Christmas Party. Thomas Fink kept things real by grilling Texan cheeseburgers in the fireplace, followed by Antonia Tingey toasting marshmallows over a wood fire. 
After the feasting, a Meccano cracker construction competition ensued, which was won by Ton Coolen. Festivities continued into the small hours with drinks and conversation in equal measure.

The Institute’s Christmas Party continued into the small hours as members served their local delicacies and held a Meccano competition.

Christmas party goes crackers

Companies are composed of many individual employees that are collectively more than the sum of their parts. This super-additive aspect of companies can be thought of as a kind of organizational intelligence. Business leaders strive to build firms which are not only intelligent but can learn—and forget—new things as their goals and environments change. How do companies learn collectively and transform learning into action? How do they learn and act on multiple timescales simultaneously?
In this dinner hosted by the BCG Henderson Institute, we discuss different aspects of intelligent organizations. Martin Reeves, Global Director at Boston Consulting Group and Director of the BCG Henderson Institute, discusses commitment and flexibility in strategy for companies and natural systems. Simon Levin, Professor in Ecology and Evolutionary Biology at Princeton, talks about how "multi-clock" speed organizations act on multiple timescales. Mihnea Moldoveanu, Vice Dean of the University of Toronto School of Management, discusses learning and forgetting in the age of artificial intelligence.

A dinner and discussion about commitment and flexibility, acting on multiple timescales and learning and forgetting in the age of AI.

Science of Business II

Fires at the London Institute are a regular tradition. They form a focal point for conversation and a backdrop for blackboard calculations. Visitors are delighted and surprised to find a smouldering fire in London, but fires are perfectly permissible. Our fires are made from a range of fuels: hard and soft wood and coal and smokeless coal. (This is in contrast to the American tradition, where resinous soft woods are proscribed because fireplaces are rarely swept). The energy output of these fuels is largely proportional to their densities, but they differ in how much flame they emit and how long they last. In general, soft wood is to hard wood is to coal is to smokeless coal, where the amount of flame decreases along the progression but longevity increases.
The fireplace itself is in the seminar room and dates from the 18th-century. At the top of the marble surround is a classical lamp, in the manner of Robert Adam, which forms the Institute’s seal. In addition to fires for warmth and companionship throughout the year, the fireplace is occasionally used for barbeques—an even rarer central London sight.

Thomas Fink barbeques a Texan lunch in the popular seminar room fireplace as the London Institute celebrates American Independence Day.

Independence  Day BBQ

An ecosystem is a community of species in a single habitat. Interdependencies within the ecosystem mean the fate of one species can have surprising effects on the ecosystem as a whole. In a similar way, interconnected firms make up an economic ecosystem, and many of the challenges facing it are analogous to those confronting the natural ecosystem. Examples include resilience in the face of unexpected events, the agility to handle sudden environmental change, and the risk of cascading failure leading to ecosystem collapse.
In this dinner at the London Institute, we discuss the application of biological principles to problems in business and the environment. National Academy of Sciences biologist Simon Levin talks about evolutionary strategies for tackling intractable challenges in climate change. Former Government Chief Scientific Adviser Sir John Beddington discusses lessons from ecology on mitigating risk in complex ecosystems. Shifting to current events, New York Times columnist and Pulitzer Prize winner Thomas Friedman discusses reinventing the political process using evolutionary principles.

A dinner and discussion about applying principles from evolution and ecology to seemingly intractable problems in business and politics.

Science of Business I

A blockchain is a way to store a list of records that grows in time in a way that is difficult to falsify. The main idea is that each new record, along with its parent record’s codeword, is translated into a new codeword. Because it is infeasible to decipher a codeword, a record can’t be changed without changing all of the records that have descended from it. In cryptocurrencies based on blockchain, transactions are validated through a process called mining, which is incentivized with rewards to reduce transaction costs. Cryptocurrencies are the best-known applications of blockchain, but are there other uses for commerce and private data that could be just as transformative?
In this event, cryptographer and hedge fund manager Robert Sams talks about cryptocurrency stabilization; Simone Bronzini, co-founder of the blockchain company Chainside, discusses a threat model of blockchain applications; and physicist Andrea Baronchelli from London City University talks about modelling the cryptocurrency market. After the talks there is a general discussion on using blockchain technology for the public good.

Scientists and businessmen discuss the use of blockchain technologies across cryptocurrencies, commerce and the analysis of private data.

The future of blockchain

In one of the most damaging cyberattacks ever, the 2017 Wannacry ransomware spread across 150 countries. By encrypting sensitive data and demanding payment in Bitcoin, it held thousands of businesses hostage. Until it was brought down by a hidden kill switch, the identity of the hostage takers was protected by the blockchain technology behind the Bitcoin cryptocurrency. More crippling ransomware attacks are sure to follow. But how does ransomware work, and how can we protect against it? What is the blockchain technology behind the cryptocurrencies funding it, and how can it transform business? 
In this symposia organized by Elli Streit and Ben Lynch from the LIMS Ventures board, leaders in intelligence, defence, business and academia help answer these questions. Ben Addis from the Serious Organised Crime Agency opens with an introduction to ransomware. Charly Shugg and Jeff Birnbach from Sylint give a strategic vision for cybersecurity. Simone Bronzini, co-founder of Chainside, introduces blockchain and cryptocurrency. Last, Nicolas Courtois from UCL talks about stealth and anonymity in blockchains.

Leaders in intelligence, defence, business and academia discuss the technology behind ransomware and the cryptocurrencies that fund it.

Ransomware  and blockchain

Artificial neural networks were inspired by simple models of computation in the brain. Despite rapid progress in understanding them theoretically, artificial neural networks did not live up to their early promise in terms of practical results. Only recently have they begun to show potential for performing seemingly intelligent tasks. On the other hand, biological neural networks are capable of extraordinary computational feats, but how they achieve it remains a mystery. Do artificial networks really offer insight into brain function, or are they a distinct framework for computation in their own right?
In this event, Thomas Parr from University College London talks about active inference and computational neuropsychology. Grace Lindsay, also from UCL, discusses using convolutional neural networks to study biological visual attention. Alexander Mozeika from King’s College London talks about the statistical physics of feedforward Boolean networks. After the talks there is a general discussion on whether and how artificial neural networks can help us understand the workings of their biological counterparts.

Physicists and neuroscientists and discuss how artificial neural networks can shed light on the working of their biological counterparts.

Neuroscience and  artificial intelligence

Scientists discuss different types of modified gravity and prospects for a consistent theory in our Late Night at London Institute series.

Modified gravity and cosmology

One of the most puzzling things about physics is that the mathematics that describes the universe is surprisingly beautiful. This language of the universe advances in a way that is both deeper and more elegant then would seem humanly reasonable, despite being borne of human consciousness. As Roger Penrose explains it, “We have a closed circle of consistency here: the laws of physics produce complex systems, and these complex systems lead to consciousness, which then produces mathematics, which can then encode in a succinct and inspiring way the very underlying laws of physics that gave rise to it.” Because the subjects are so intertwined, a guiding principle of the London Institute is to keep them both under one roof.
In this talk Charles Epstein talks about the fruitful but factious relationship between physics and mathematics from the 17th century until now. He discusses the difficulties met when physicists and mathematicians collaborate, the role of intuition in each subject, and how they interpret the concept of “proof”. He speculates on how the two fields will influence each other into the future.

Charles Epstein talks about the longstanding fractious but fruitful relationship between pure mathematics and mathematical physics.

Pure mathematics meets  mathematical physics

How do you describe the behaviour of hair? Leonardo da Vinci thought it flowed like water, but modeling realistic hair in computer animated films is challenging. Hair fibers are elastic filaments with random intrinsic curvature, like cotton and fiberglass. A bundle of fibers is subject to the combined effects of bending elasticity, gravity and orientational disorder. Despite the ubiquity of fiber bundles in the natural and man-made world, a mathematical description of how a bundle behaves has remained elusive.
In this talk Robin Ball develops a mathematical model of the behaviour of a bundle of fibers and applies this formalism to the iconic problem of the ponytail. The elasticity, gravity, and disorder are recast as a differential equation for the envelope of the ponytail bundle, in which the compressibility enters through an equation of state. From this, it is possible to identify the balance of forces in various regions of the ponytail, extract a remarkably simple equation of state from laboratory measurements of real ponytails, and relate the pressure to the random curvatures of individual fibers.

Robin Ball talks about a theoretical model of fibers in which their elasticity and curliness produce the characteristic shape of a ponytail.

Ponytail physics

Technology changes through an evolutionary process in the sense that it satisfies Darwin and Wallace’s key properties: descent with modification and selection. However, the process through which change takes place in technology is very different from that in biology. For example, biology mutates in all directions, but in technology variation is more directed. There are also differences is the available data and our knowledge of it. In biology we have an accurate phylogeny, and the fossil record indicates how this changed through time. For technology we have historical observations of when inventions appeared, but know much less about the forces that influenced them. There are several taxonomies provided by patent processes but they are far from concordant.
There are nonetheless some statistical laws about technological performance, such as Wright’s law and a variety of Moore’s laws for different technology sectors. In this talk Doyne Farmer summarizes the state of the art of our understanding of technological evolution and sketches some of the problems that need to be solved to create a better theory.

Doyne Farmer talks about what technology is and how it evolves and our improving ability to forecast technological change into the future.

Evolution of  technology

A multifractal is a generalization of a fractal in which there is not a single scaling exponent but a continuous spectrum of exponents which depends on the length scale. Multifractals were originally conceived to describe turbulence in fluids, but have since developed into one of the main tools of econophysics. A collection of related studies, econophysics employs statistical physics to investigate the distribution of financial returns, macroscopic models of financial markets, agent-based models of the economy and the network structure of financial institutions.
In this talk Tiziana Di Matteo describes the use of multifractals to study financial data. Two main elements define the complexity of financial time series: multifractality, which is associated with the behavior of each variable and how it scales in time; and the structure of dependencies between time series, associated with the collective behavior of the whole set of variables. So far, these two manifestations of complexity have been investigated separately. Here, by considering both simultaneously, a theory emerges describing how they relate.

Tiziana Di Matteo talks about the interdependence of multifractal financial time series and a new way to understand and forecast them.

Multifractal finance

The Grand Tour of Science is a comprehensive account of modern science in seven two-hour lectures for the public. The lectures are in two parts, with drinks and discussion before, in between and after.
This lecture covers: 
• Shannon’s information theory 
• Bayesian versus maximum likelihood statistics 
• The problems of ‘big data’ 
• True patterns versus overfitting 
• Modern information-driven medicine

Mark Girolami talks about how information, inference and data analysis drives the digital revolution in part 7 of our Grand Tour of Science.

The science of information

The Grand Tour of Science is a comprehensive account of modern science in seven two-hour lectures for the public. The lectures are in two parts, with drinks and discussion before, in between and after.
This lecture covers: 
• The standard model: particles and interactions 
• The Higgs and its mysteries 
• Problems and puzzles 
• Unification and supersymmetry 
• Superstrings and M-theory

Neil Lambert talks about subatomic particles and the elusive search for a theory of everything in part 6 of our Grand Tour of Science.

High energy  physics

The Grand Tour of Science is a comprehensive account of modern science in seven two-hour lectures for the public. The lectures are in two parts, with drinks and discussion before, in between and after.
This lecture covers: 
• What is life? 
• The beginnings of molecular biology 
• Crystals, symmetry and X-ray crystallography 
• Discovery of the structure of DNA 
• Towards synthetic biology

Brian Sutton talks about the path to understanding life, molecular biology and synthetic biology in part 5 of our Grand Tour of Science.

DNA and the human genome

The Grand Tour of Science is a comprehensive account of modern science in seven two-hour lectures for the public. The lectures are in two parts, with drinks and discussion before, in between and after.
This lecture covers: 
• Conundrums of the atom and black-body radiation 
• Wave mechanics and matrix mechanics 
• Heisenberg’s uncertainty principle 
• Discovery of antimatter 
• Quantum information and materials science

Chris Pickard talks about how Nature’s mysterious non-determinism is captured by quantum mechanics in part 4 of our Grand Tour of Science.

Quantum  theory

One new thing often leads to another. Such correlated novelties are a familiar part of daily life. They are also thought to be fundamental to the evolution of biological systems, human society and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called “expanding the adjacent possible”. However, correlated novelties and how they change over time have yet to be quantified empirically or modeled mathematically. Nowadays, thanks to the availability of extensive longitudinal records of human activity online, it has become possible to test whether everyday novelties crop up by chance alone, or whether one truly does pave the way for another.
In this talk Vittorio Loreto proposes a simple mathematical framework that mimics the process of exploring a physical, biological or conceptual space that enlarges whenever a novelty occurs. He tests the predictions on four data sets of human activity. He also highlights future directions: the interplay between individual and collective effects and the different mechanisms supposedly leading to innovation.

Vittorio Loreto talks about the dynamics of correlated novelties in the evolution of biological systems, human society and technology.

Dynamics of  correlated novelties

The Grand Tour of Science is a comprehensive account of modern science in seven two-hour lectures for the public. The lectures are in two parts, with drinks and discussion before, in between and after.
This lecture covers: 
• Non-integer dimensions and scale invariance 
• Riemannian geometry 
• Groups and crystals 
• Aperiodicity and Gödel incompleteness 
• Turing machines and non-computability

Andrew Green talks about the theory of relativity, cosmology and the structure of the universe in part 3 of our Grand Tour of Science.

Relativity and  the universe

Thomas Fink talks about radical new mathematical developments that set the stage for modern physics in part 2 of our Grand Tour of Science.

Revolutions  in mathematics

The Grand Tour of Science is a comprehensive account of modern science in seven two-hour lectures for the public. The lectures are in two parts, with drinks and discussion before, in between and after.
This lecture covers: 
• The hypothesis-prediction-experiment loop 
• Tycho Brahe and the role of data 
• The scientific revolution of the 17th century 
• Physics from Gallileo to Maxwell 
• The character of physical laws

Robert Farr talks about the emergence of science from astronomy and the rise of classical physics in part 1 of our Grand Tour of Science.

Classical quantitative science

BBC science presenter Steve Mould bought a 50m long chain as a prop and stored it in a jar. To his surprise, he found that if he dangled the end of the chain over the rim of the jar, the entire chain would spontaneously flow down to a pile on the floor. More surprisingly, it leapt up in a sustained arc above the jar. Mould made a video of his chain which went viral on YouTube. But despite millions of views and much speculation in illustrious physics departments around the world, no one could explain why the chain rises above the jar.
In this talk, John Biggins explains how he and Mark Warner solved the mystery of the leaping chain. To do so, he first revisits and repairs textbook notions about how chains are picked up from surfaces. He shows that a chain fountain spontaneously forms in the shape of an upside-down catenary, that is, the inversion of the shape of a hanging chain. This is the optimal shape for an arch of perfect compression and has been used by architects and engineers from Hooke and Wren to Gaudi. But the chain fountain is a new structure: an arch of perfect tension stabilized by motion.

John Biggins talks about how he solved the mystery of the chain fountain, in which a chain spontaneously leaps up as it flows out of a jar.

Unraveling the  chain fountain

Is physics creative? Many people think of it as the opposite: all left brain and no right brain. But when it comes to scientific discoveries, mathematical prowess is only one side of the coin. Fundamental advances rely on finding links, usually mathematical in form, between seemingly disconnected fields—an intrinsically creative act.
In this talk, Thomas Fink gives a personal account of how physicists discovery theories by building systems of the world. He presents three tales from his own experience: about discovering tie knots, tiling the plane and learning to dance. In the first, he explains how systems can be found almost everywhere, if we look closely enough: mathematical structure lurks behind the ordinary as well as the remarkable. In the second, he illustrates how in the world of systems, miracles can happen: our intuition is all but useless when it comes to how the universe works, and there are extraordinary surprises to be had. In the third, he describes the dangers of trying to systematize human aspects of life that resist mathematical insight: not everything has a system, and that’s OK.

Thomas Fink talks about physicists’ inner drive to systematize the world around them and the role of imagination in building theories.

Calculation and creativity

Chris Pickard talks about materials under conditions so extreme they cannot be studied in the laboratory in our Science and Society series.

From stars and exoplanets to materials that matter

Can mathematics help us understand the market? Consider this real-life conundrum. The El Farol bar in Sante Fe organizes Irish music once a week. It’s a popular event but sometimes leads to overcrowding, which is unpleasant. So in order to decide whether or not to go, each individual tries to forecast the decisions of others, and then do the opposite of the majority: go when most plan to stay home, and vice versa. Deductive reasoning is ruled out, because it would be picked up by others and invalidate itself. In practice, each individual bases his decision on a number of personal ad hoc rules, based on the past performance of himself and others.
In this talk, Anthonius Coolen explains how the minority game—a simple mathematical model of the El Farol bar problem—has increased our understanding of the cooperation and fluctuations observed in financial markets. The minority game exhibits intriguing collective phenomena that would not emerge in game-theoretic market models. Despite its apparent simplicity, it has stumped physicists around the world, and only recently have its several surprises been unlocked.

Anthonius Coolen talks about a game of motorways, bars and financial markets solved by the statistical mechanics of disordered systems.

The Minority Game

A fractal has the property that any part of it, when magnified, resembles the whole. Examples include the snowflake-like Koch curve and the Mandelbrot set. Remarkably, biology employs fractal designs to achieve high efficiency: spongy bone for anisotropic stiffness; ramified networks for gas exchange; and self-similar shells for pressure resistance. But in the man-made world, the reverse is true: fractal designs are rarely used for mechanical efficiency. Transmission towers and the branching columns of Gaudi’s cathedral Sagrada Familia hint at fractal design principles; but the small number of hierarchical levels and the lack of quantitative understanding suggest these are heuristic.
In this talk, Rob Farr explains how new classes of structures based on fractal designs can offer extraordinary gains in mechanical efficiency. Remarkably, they exhibit new strength-to-mass scaling behaviour, where the advantage achieved at one generation is passed on to the next. This bold shift in design philosophy offers a broad range of applications not only in the built environment but also in aerospace and space.

Rob Farr talks about the physics of architecture and how self-similar mechanical structures can make seemingly impossible designs a reality.

Fractal structures and architecture

In a hostile and compromised cyber environment, nations require communication networks that are secure. The London Institute and the Air Force Office of Scientific Research challenge research communities on both sides of the Atlantic to advance the mathematics that will underpin fundamental advances in cyberspace network security. 
In this two-day symposia organized by John Harer and Samson Abramsky and funded by the AFOSR, we hear from 10 speakers and discuss the challenge. ○ Peter Chin: Large-scale structures for graph computation. ○ George Cybenko: Two short stories about mathematics in computer security. ○ Dan Ghica: System level semantics. ○ John Harer: Persistent homology and networks. ○ Pasquale Malacaria: Contributions to the science of confidentiality. ○ Andrzej Murawski: Anonymity and game semantics. ○ Linda Ness: Network measurements: representation and analysis. ○ Dusko Pavlovic: Semantical methods for security games. ○ Antonio Scala: On the need for maps of cyberspace. ○ Nikos Tzevelekos: Programs, security and games. ○ Patrick Wolfe: Point process modeling for directed interaction networks.

A two-day workshop funded by the Air Force Office of Scientific Research on computational topology, game semantics and network security.

Cyberspace network security

In the run-up to the 2008 financial crisis, an increasingly elaborate set of financial instruments emerged, intended to optimize returns to individual institutions with seemingly minimal risk. Little attention was given to their possible effects on the stability of the system as a whole, and the tools available to detect latent stress were qualitative and unsophisticated.
In this symposium for physicists, bankers and policy advisors, we explore the interplay between complexity and stability in deliberately simplified models of financial and trade networks. We draw on analogies with the dynamics of ecological food webs, the spread of infectious diseases and combinatorial models of production. Luciano Pietronero, Fellow of the London Institute and Director of the Institute for Complex Systems, talks about the building blocks of economic complexity and the forecasting of financial crises. Lord May of Oxford, former Government Chief Scientific Adviser and recently President of the Royal Society, discusses his work on systemic risk in banking ecosystems, reported in this week’s cover article in Nature.

A lunchtime symposium of physicists and financiers on banking ecosystems, financial risk and the building blocks of economic complexity.

Ecology, physics and finance

Yang-Hui He is Professor of Mathematics at City University of London, Chang-Jiang Chair Professor at NanKai University and Lecturer at Merton College, Oxford. He studied at Princeton, Cambridge and MIT and works at the interface of geometry, string theory and machine-learning.

Lee Hazelwood is a principal scientist at bit.bio and visiting researcher at the London Institute. His research interest is to understand the biological and physical basis of cellular identity using quantitative methods.

Raffaella Mulas is a postdoc between the Alan Turing Institute of London and the University of Southampton, where she works in the group of Ben MacArthur. She recently obtained her PhD at the MPI MiS, with a thesis on the spectra of graphs and hypergraphs.

Kaiser Karim is a Scientist at bit bio specialising in making and analysing cells in the central nervous system from human iPSCs, especially glutamatergic neurons. He did his PhD at the University of Cambridge in Mark Kotter’s lab, investigating the mechanisms of NGN2-driven cell reprogramming.

Reimer Kühn received a PhD in Theoretical Physics from Kiel University in 1987. He held post-doctoral and lecturer positions at the University of Heidelberg, and visiting professorships at Leuven, Bordeaux and Gottingen. He has been a member of the Mathematics Department at King's since 2003.
Reimer Kühn has broad scientific interests in the field of Statistical Mechanics of Complex and Disordered Systems.

Ryan Hannam is a postdoc at the London Institute & received his PhD from King's College London. His research interests centre on the emergence of multicellular life from genetic interactions. He uses tools from the statistical physics of complex systems and neural networks.

Ton Coolen is a Fellow of the London Institute and Professor of Applied Mathematics at King’s College London. He develops new mathematical methods for the study of heterogeneous many-variable systems and non-equilibrium processes in physics, biology and computer science.

Dr Thomas Fink is the director of the London Institute for Mathematical Sciences. He studied at Caltech, Cambridge and Ecole Normale and is Charge de Recherche in the French CNRS. He works in statistical physics, biological modelling, combinatorics and the mathematics of innovation.

Alexander Mozeika has an MSc in neural networks and a PhD in applied mathematics from KCL. He is a LIMS and KCL postdoc working on high-dimensional statistics and modelling the adaptive immune response. His research is in information theory, statistics and statistical physics.

Dr Mark Kotter is a stem cell biologist and neurosurgeon at Cambridge and the founder and CEO of Bit.Bio. The cell coding company’s mission is the efficient and consistent reprogramming of human cells to standardise biomedical research, enable drug discovery and develop next-generation cell therapies.

Dr Robert Farr is an Associate Fellow at the London Institute and a Senior Scientist at Jacobs Douwe Egberts. He read physics at Cambridge University, winning the Clerk Maxwell University Prize for physics, then sat the Part III Tripos before doing his Ph.D. at the Cavendish Laboratory. For 12 years he was a Senior Research Scientist at Unilever and at the same time held a visiting appointment at Nottingham University. Dr Farr applies geometric ideas to classical physics and materials science, especially to multi-scale and fractal systems. He has contributed to a range of other fields, including discrete geometry, spectral graph theory, combinatorial innovation and repairable systems.

Dr Thomas Fink is Director of the London Institute and Charge de Recherche in the CNRS. He studied physics at Caltech and Cambridge University, winning the Fisher Prize for physics and Green Prize for research. He did a postdoc at Ecole Normale Superieure and was a Junior Fellow at Caius College, Cambridge, where he worked at the Cavendish Laboratory. Dr Fink uses statistical physics and discrete mathematics to form basic science insights into complex physical, biological and socioeconomic systems. Outside of physics, he is interested in models of simplicity, collective creativity, graphic design and mobile technology startups. His books The 85 Ways and The Man's Book have sold 1/3m copies.

John Biggins is a physicist and lecturer in engineering at Cambridge University and a Fellow of Corpus Christi College. He studied at Cambridge and did his PhD between Cambridge and Caltech before winning an 1851 Research Fellowship, which he spent at Harvard. On returning to Cambridge he was a research fellow at Trinity Hall and an early career lecturer at the Cavendish Laboratory. 

Dr Biggin’s research centers on the theory of mechanical instabilities, such as buckling, wrinkling and folding, and an exciting new category of artificial muscle known as liquid-crystal elastomers. He has also published in a range of other fields, including plasmonics, embryology and the mechanics of chains.


Dr Marc Warner is the CEO of the AI research company Faculty, which he co-founded in the belief that the benefits of AI should extend to everyone. He has since overseen Faculty’s growth to become one of Europe’s leading AI companies. He has led data science projects for clients ranging from EasyJet and Siemens to the UK Government and the NHS. Before Faculty, Dr Warner was a Marie Curie Fellow in physics at Harvard University, specialising in quantum sensing. Outside Faculty, he advises the UK Government on digital data and artificial intelligence through the Digital Economic Advisory Council. He has a PhD in quantum computing and a degree in physics from Imperial College London.

Robert Farr is an Associate Fellow at the London Institute and Senior Scientist at Jacobs Douwe Egberts. He studied physics at Cambridge, since when he has worked at Unilever and Nottingham University. Dr Farr applies geometric ideas to materials science and classical physics.

Prof. Andrew Green holds the Chair of Condensed Matter Physics at University College, London. His interests include the properties of natural and manufactured materials, harnessing quantum mechanics for information processing, and the overlap of the latter with machine learning.

Prof. Chris Pickard is Sir Alan Cottrell Professor of Materials Science at Cambridge University. He did his PhD at Cambridge, since when he has worked at the universities of Kiel, Paris and London. Prof Pickard explores the universe at the atomic scale through quantum mechanics. 

Prof. Brian Sutton is Professor of Molecular Biophysics at Kings College, London. He did his D.Phil in molecular biophysics at Oxford University, since when he has worked at Oxford and Kings. His interests include structure-based drug design and the evolution of anti-body structure.

Prof. Neil Lambert is Professor in Theoretical Physics at Kings College, London. He did a PhD in String Theory and Branes at Cambridge University. Since then he has worked at the ENS in Paris and Rutgers University. His interests include supersymmetry, string theory and M-theory. 

Prof. Mark Girolami is Sir Kirby Laing Professor of Civil Engineering at Cambridge University. He is a founding executive director and current strategic director at the Alan Turing Institute. Prof Girolami's research combines the statistical, mathematical, physical and engineering sciences.

A software engineer with many years of experience in full-stack development and also AR game development. Born in Ukraine, and raised in Italy, he studied Applied Computer Science at the University of Urbino.