What are the next ITC topics?

The International Titisee Conferences are organized two years in advance. Here you will find topics, chairs, dates, and if already available, lists of confirmed speakers for the upcoming International Titisee Conferences. 

Chaired by Frank Jülicher (Dresden, Germany) and Marcos Gonzalez-Gaitan (Geneva, Switzerland)

A fundamental question in biology is to understand the principles and mechanisms that underlie the spatial organization of cells and living organisms and the dynamic processes by which such spatial organization is generated and maintained. Cells have to organize many cellular functions and complex chemistry in space. They are organized in organelles and further distinct compart­ments and exhibit a distinct spatial organization. On larger scales, cells form tissues with specific shapes and sizes by morphogenesis during development. All these spatial structures and morphologies arise in the context of dynamic processes and are part of the spatiotemporal organization of life.

This meeting will bring physicists, chemists, and biologists together to discuss the emergence of spatiotemporal organization and the role of information, energy, self-organization, phase transitions, active processes, and material properties in the organization of living matter.

Invited speakers

  • Aumeier, Charlotte (Geneva, Switzerland)
  • Baum, Buzz (London, United Kingdom)
  • Bellaiche, Yohanns (Paris, France)
  • Bitbol, Anne-Florence (Lausanne, Switzerland)
  • Brugués, Jan (Dresden, Germany)
  • Derivery, Emmanuel (Cambridge, United Kingdom)
  • Dogterom, Marileen (Delft, The Netherlands)
  • Fakhri, Nikta (Cambridge, MA, USA)
  • Grill, Stephan (Dresden, Germany)
  • Howard, Jonathon (New Haven, CT, USA)
  • Hyman, Anthony (Dresden, Germany)
  • Januschke, Jens (Dundee, United Kingdom)
  • Kicheva, Anna (Klosterneuburg, Austria)
  • Krishnamurthy, Vijaykumar (Bangalore, India)
  • Kruse, Karsten (Geneva, Switzerland)
  • Mani, Madhav (Evanston, IL, USA)
  • Mietke, Alexander (Cambridge, MA, USA)
  • Milinkovitch, Michel C. (Geneva, Switzerland)
  • Nelson, David R. (Cambridge, MA, USA)
  • Pelkmans, Lucas (Zürich, Switzerland)
  • Popovic, Marko (Dresden, Germany)
  • Prost, Jacques (Paris, France)
  • Rao, Madan (Bangalore, India)
  • Ronceray, Pierre (Marseille, France)
  • Rulands, Steffen (Dresden, Germany)
  • Saunders, Timothy (Coventry, United Kingdom)
  • Scheele, Colinda (Leuven, Belgium)
  • Viasnoff, Virgile (Singapore, Singapore)
  • Wyart, Matthieu (Lausanne, Switzerland)

Chaired by Leonid Mirny (Cambridge, MA, USA) and Job Dekker (Worcester, MA, USA)

Cells organize their genomes in three-dimensional space to facilitate and regulate a wide array of chromosomal functions ranging from gene regulation and DNA replication to chromosome condensation and segregation during cell division. During the last decade we have witnessed a revolution in our ability to measure the structural organization of chromosomes at increasing resolution and detailed views of the folded state of chromosomes can now be obtained even from single cells. These insights are now leading to new questions about the mechanisms and dynamics of chromosome folding, and the ways chromosome conformation relates to chromosome function.

Addressing these current questions requires highly interdisciplinary approaches at the interface of biology and physics. This includes development and application of experimental systems for structure–function analysis on the one hand, and physical modelling on the other to test and study the mechanisms of folding, the relation to gene regulation and other processes, and the molecular machines involved in these processes.

This inter-disciplinary meeting aims to bring together scientists who study chromosome folding and apply a wide range of approaches including cell biological studies, imaging-based measurements, genomics assays, computational analyses, polymer physics, and dynamic simulations of chromosome folding mechanisms.

Invited speakers

  • Bienko, Magda (Solna, Sweden)
  • Coulon, Antoine (Paris, France)
  • Dekker, Cees (Delft, The Netherlands)
  • Earnshaw, William C. (Edinburgh, United Kingdom)
  • Everaers, Ralf (Lyon, France)
  • Farabella, Irene (Barcelona, Spain)
  • Gerlich, Daniel (Vienna, Austria)
  • Giorgetti, Luca (Basel, Switzerland)
  • Gregor, Thomas (Paris, France)
  • Grosberg, Alexander Y. (New York, NY, USA)
  • Häring, Christian (Würzburg, Germany)
  • Heard, Edith (Heidelberg, Germany)
  • Hirano, Tatsuya (Wako, Saitama, Japan)
  • Jost, Daniel (Lyon, France)
  • Kaplan, Noam (Haifa, Israel)
  • Karpen, Garry (Berkeley, CA, USA)
  • Kleckner, Nancy (Cambridge, MA, USA)
  • Marlow, Heather (Chicago, IL, USA)
  • McCord, Rachel Patton (Knoxville, TN, USA)
  • Nora, Elphége-Pierre (San Francisco, CA, USA)
  • Peters, Jan-Michael (Vienna, Austria)
  • Rando, Oliver (Worchester, MA, USA)
  • Rosa, Angelo (Trieste, Italy)
  • Rowland, Benjamin D. (Amsterdam, The Netherlands)
  • Solovei, Irina (Martinsried, Germany)
  • Spitz, Francois (Chicago, IL, USA)
  • Staight, Aaron (Stanford, CA, USA)
  • Tachibana, Kikuë (Martinsried, Germany)
  • Zickler, Denise (Gif sur Yvette, France)
  • Zidovska, Alexandra (New York, NY, USA)

Chaired by
Michael Häusser (London, United Kingdom), Matthew Botvinick (London, United Kingdom) and Caswell Barry (London, United Kingdom)

The last decade has seen phenomenal advances in the field of machine learning (e.g. deep learning, RL) and its application in AI. While these changes have already had considerable impact on most areas of science, they hold a special resonance for neuroscience. Not only does AI share a common lineage with neuroscience but there is the exciting prospect that machine learning and the brain may employ similar computations to process information. For these reasons machine learning provides a means to emulate neural functions and the circuits supporting them, providing insights and hypotheses to drive our understanding of perception, behaviour, and cognition. Equally, AI tools provide a means to discover, segment, and track distinct neural and behavioural states – yielding more efficient experiments and accelerating the pace of discovery. At the same time, this understanding of the brain’s incredible efficiency and flexibility feeds back into the design of more effective AI approaches, architectures and models.

This link between neuroscience and AI highlights the critical need for a dialogue between individuals whose research spans these two fields – who can pose and test hypotheses about the brain but are also able to apply the lessons learnt to generate further advances in machine learning. This conference, featuring the leaders in the field, will provide an ideal relaxed and informal setting for this dialogue to flourish.

Chaired by Benjamin L. Ebert (Boston, MA, USA) and Peter Campbell (Hinxton, Cambridge, UK)

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