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Lectures
CALIBRE Symposium 2026
ORGANIZERS
CALIBRE, ICTS-TIFR
DATE & TIME
26 October 2026 to 27 October 2026
VENUE
International Centre for Theoretical Sciences (ICTS-TIFR), Bengaluru

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The Centre for Artificial Learning and Intelligence for Basic Research and Education (CALIBRE)  is organising a two-day symposium bringing together researchers from academia and industry to foster interdisciplinary collaborations across biology, mathematics, physics, and computer science. The symposium will feature talks from postdoctoral fellows, faculty members, and industry experts working at the interface of artificial intelligence, computation, and the natural sciences.


The symposium will provide a platform to discuss recent advances, emerging opportunities, and challenges in applying AI/ML approaches to fundamental scientific problems. Through a diverse programme of talks and discussions, the event aims to foster interdisciplinary exchange, encourage new collaborations, and explore how AI can accelerate discovery across the physical, mathematical, and life sciences.

Many Worlds Seminar

As part of the symposium, the Many Worlds Seminar will feature Dr. Sushrut Thorat, who will speak on “Neural Networks as Scientific Instruments.” The talk will explore how neural networks can be used as controllable experimental systems to investigate mechanistic questions about cognition and the brain. Through examples from visual learning and representational drift, the talk will illustrate how computational models can help turn qualitative ideas about biological processes into testable scientific predictions.

The goal is to have

  • Research talks by postdoctoral fellows, faculty members, and industry experts
  • Opportunities for collaboration across disciplines and between academia and industry
  • Future directions and Interdisciplinary perspectives on AI and Biology


The symposium will be of interest to postdoctoral fellows, faculty members, graduate students, researchers, and industry professionals interested in artificial intelligence, machine learning, and their applications to fundamental scientific research.

CONTACT US
calibre  ictsresin
PROGRAM LINK
https://www.icts.res.in/lectures/cs-2026
  • Other links
CALIBRE Symposium 2026 (Tentative Schedule)
Monday, 26 October 2026
Time Speaker Title Resources
09:15 to 09:30 Professor Rajesh Gopakumar (Centre-Director, ICTS-TIFR) Introduction
09:30 to 10:15 Akshit Goyal (ICTS-TIFR) TBA
10:15 to 11:00 Rituparno Mondal (Raman Research Institute) TBA
11:30 to 12:15 Bruno Barton (NCBS-TIFR) Emergence in magnets, zebrafish and fruit flies.

How do a large number of interacting parts, such as magnetic spins or biological cells, come together to be understood with a small number of macroscopic degrees of freedom? I discuss my past research, in the field of magnetic skyrmions in condensed matter, and how it links to my research as part of CALIBRE on spiking networks with Sarthak Chandra and drosophila dorsal closure with Madan Rao. 
 
12:15 to 13:00 Paras Chopra (Lossfunk, Bengaluru) How to Build a Theory of Consciousness

We are all intimately familiar with consciousness, yet the science of it is at a rudimentary level. Physics had its Newton and Einstein, but we're still at the dark arts stage for consciousness. In this talk, we'll approach the question of what it takes to "solve" the mystery of consciousness from a philosophy of science point of view, traversing metaphysics and our empirical reality. Then we will talk about how we're approaching this project at our lab and finally lay down a few (wild) hypotheses for what we believe consciousness could be about.
14:00 to 14:45 Osheen Sharma (NCBS-TIFR) TBA
14:45 to 15:30 Akshay S H (ICTS-TIFR) Explosive Synchronization in Networks of Type-I Neurons.

Synchronization occurs across a wide variety of physical and Biological systems. The transition to synchronization in these systems can be smooth and continuous, or abrupt and discontinuous, with hysteresis in the order parameter. This abrupt synchronization transition, termed Explosive Synchronization (ES), has been studied extensively in the Kuramoto oscillatory networks. In the context of neuroscience, ES has been hypothesized as the mechanism behind some brain dynamics. But the studies involving neuronal models are sparse and have model-specific conditions under which ES is observed. In this talk, we will look at ES in networks of a weakly heterogeneous and weakly coupled class of neurons. Leveraging the recently demonstrated mapping between the Kuramoto and QIF models, we will realize different scenarios known to show ES in the oscillatory networks. 
16:00 to 17:00 Sushrut Thorat (Lossfunk) Neural Networks as Scientific Instruments

Can neural networks help explain cognition, rather than merely mimic it? I will show how they can serve as controllable experimental systems for testing mechanistic theories of the brain. Using two examples — how early visual experience may produce human-like shape bias, and how learning drives representational drift — I’ll illustrate how neural networks can turn qualitative ideas into testable predictions for biology.

 

This is based on a couple of papers:
Tuesday, 27 October 2026
Time Speaker Title Resources
09:30 to 10:15 Udpinder S. Bhalla (NCBS-TIFR) TBA
10:15 to 11:00 Maanasa Natrajan (ICTS-TIFR) TBA
12:15 to 13:00 Shreyank Goel (ICTS-TIFR) TBA
14:00 to 14:45 S. Roshan Kumar (NCBS-TIFR) Learning to Learn: What the zebrafish larva can teach AI

Artificial Intelligence emerged from ideas rooted in neuroscience. However, over time, the field has diverged from its roots, with recent breakthroughs in AI having little connection to neuroscience. In this talk, I will introduce our efforts to reconnect AI development with insights from neuroscience, as part of a growing movement seeking to address key limitations of current AI: poor performance in tasks involving interaction with the physical world, high energy expenditure, reliance on large amounts of data, and centralised architectures. I will discuss how motor development in zebrafish can provide a blueprint for new approaches to AI training, with the aim of improving AI performance in a domain where it has traditionally struggled, robotics. By tracking the emergence of motor skills in zebrafish larvae, we hope to identify general principles that can be used to develop new architectures and training regimes suited to controlling physical systems.
14:45 to 15:30 Shrisuti Sriraman (NCBS-TIFR) Spatial transcriptomic study of invasion markers in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most prevalent malignancies in India and is associated with high rates of recurrence and poor clinical outcomes. Pattern of invasion (POI), a histopathological descriptor of the tumor-stromal interface, is a robust predictor of invasion risk and recurrence in OSCC. Despite the strong correlation between POI and clinical outcomes, the molecular basis of aggressive invasion remains incompletely characterised.
Using NanoString GeoMx spatial profiling on an in-house cohort of 19 OSCC patients, we compared tumour and stromal regions of high-risk and low-risk POI. Differential expression revealed upregulation of extracellular matrix remodelling, partial-EMT, and hypoxia programs alongside an immunosuppressive microenvironment in high-risk POI tumor regions. Further, transcription factor activity analysis revealed coordinated TGF-β,AP-1,NF-κB signalling coupled with suppressed antigen presentation and epithelial differentiation programs. These findings resulted in a comprehensive invasion signature gene expression list.
Stratification of HNSCC patients from the TCGA cohort using our invasion signature demonstrated significant differences in progression-free survival. Cross-validation of these signatures against independent HNSCC single-cell and spatial datasets corroborated the spatial organisation of these programs at the tumor invasive front. Somatic mutation profiling further suggested enrichment of TP53, CDKN2A, HRAS, and CASP8 alterations in high risk POI tumors.
Since next generation sequencing remains impractical for wide clinical use, we are extending this work by applying deep learning-based spatial gene expression imputation directly from whole slide images. These findings position our invasion signature as a predictive biomarker for risk stratification and translate our findings into a scalable, cost-effective clinical tool suited to the Indian healthcare context, where OSCC disproportionately burdens patients with limited access to advanced molecular diagnostics.