People - Faculty
S. P. Arun
Research Areas: visual perception, image processing, neuroscience
My research interests are in the intersection of statistical physics, combinatorics and probability.
Research Area: Computer Vision, Deep-learning, Video Analytics, Multimedia
Research areas that are being pursued actively in the laboratory are broadly described under two categories: (A) Systems Biology, (B) Structural Bioinformatics, both combined towards addressing fundamental aspects of disease processes, obtaining global perspectives of perturbations in disease and application of that knowledge to tackle specific problems in disease diagnosis, drug discovery and immunology. A range of mathematical models, at multiple levels and scales are utilized for these.
Research Interests: How does our brain enable us to pay attention selectively to some things, and to ignore others? What happens in the brain when we make important decisions? Our research focuses on understanding the neural basis of cognitive phenomena such as selective attention and decision making. To address these questions we follow a quantitative approach that combines neuroscience experiments, model-based analyses (e.g., linear/nonlinear dynamical systems, control theory, machine learning) as well as large-scale computer simulations. We directly measure or perturb brain activity with a variety of techniques, including functional neuroimaging (fMRI), diffusion imaging (dMRI), high-density electro-encephalography (EEG), and transcranial electrical and magnetic stimulation (tES/tMS). The overarching goal is to develop a unified framework that describes how cognitive phenomena emerge from neural computations by a systematic analysis of brain and behavior.
Research Interests: Finite Element Analysis, High Performance Computing, Computational Fluid Dynamics, Bio-medical Applications
Research Area: Numerical Analysis for Partial Differential Equations.
S. K. Nandy
Prof. S. K. Nandy's current research addresses important issues in micro-architectural and compiler optimizations for power and performance in Chip Multiprocessors (CMPs) and Runtime Reconfigurable System on Chips (MP-SoCs). All his research target massively parallel architectures/platforms for accelerating computations for Next Generation Sequence Alignment, Numerical Linear Algebra, Real-time Face Recognition, Cognition Engines, and Molecular Dynamics.
Debnath Pal’s group works at the interface of biology and chemistry, mixing it with interesting and innovative ideas from physics, maths and computer science. His research application areas span the domains of genomics, transcriptomics, proteomics, metabolomics, structural biology and drug discovery. His group develops new methods and algorithms to address unanswered problems. He is interested in building next generation life science applications on accelerator platforms. He also runs a wet laboratory to test some of his computational work.
Research interests: Physics and Computational Science of Turbulence, Electrical-wave Turbulence in Cardiac Tissue, and Cold-atom Systems.
My research interest is in studying constrained and related stochastic dynamical systems with computational mathematical tools. Current work includes applications to problems of data assimilation and rough path behaviour.
Space dynamical systems (such as satellite orbit estimation) and biochemical reactions are examples of fields of application.
Govindan Rangarajan (Convener)
Research Interests: Time series analysis; Applications in neuroscience; Nonlinear dynamics and chaos
Recent studies have identified a small subpopulation of cells within several cancers termed as cancer stem cells (CSCs). These CSCs play critical roles in tumor initiation, progression, and maintenance. Furthermore, CSCs remain unaffected by currently used chemotherapeutic drugs, thereby leading to chemotherapy failure and cancer recurrence. The research focus of my laboratory is to understand the unique molecular mechanisms operating within CSCs, and find novels ways for targeting them. Work done in my laboratory has identified AMP activated protein kinase (AMPK) as a key signaling molecule in the regulation of breast cancer stem-like properties, survival and drug resistance. Current interests are in understanding the molecular mechanisms downstream of AMPK activation that contribute to cancer progression.
I received a B.Tech in Electrical Engineering from IIT Kanpur and a PhD in Biomedical Engineering from the Johns Hopkins School of Medicine. My postdoctoral training was in the department of Neurobiology at Harvard Medical School with Dr. John Maunsell. I joined the Center for Neuroscience, IISc, in June 2011. From 2012 onwards, I have also been an associate faculty in the Electrical Engineering Department at IISc.
Our lab studies the neural basis of selective attention, with a focus on a brain rhythm called “gamma” (30-80 Hz), which is modulated by attentional load and is thought to be linked to high-level cognitive processes. Attentional mechanisms have been studied at several different recording scales – from single neurons in monkeys to diffuse population measures such as electro-encephalography (EEG) in humans. However, the relationship between signals recorded from such different scales is poorly understood. The long-term goal of this research is to elucidate the mechanisms of attention by linking the neural recordings obtained from these vastly different scales. This involves recordings from both humans and non-human primates using a variety of techniques while they are engaged in certain cognitive tasks, development of advanced signal processing techniques to build the “links” across recording scales, and mathematical modelling of brain signals, including gamma oscillations, using dynamical system approach as well as detailed biophysical models. Establishment of this cross-species, cross-scale link between brain signals has far reaching applications, such as in Brain-computer Interfacing (BCI) and clinical diagnosis of brain disorders.
Research Interests: Mechanisms of attention and gamma oscillations; Modeling and Signal Processing, Brain-Computer Interfacing.
Prof. Srinivasan's research interests include evolution of protein and its implication on structure, functions and interactions.
Research Areas: Computational methods in medical imaging, medical image processing (reconstruction/analysis), physiological signal processing, photoacoustic tomography, and diffuse optical tomography.