World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
63
Citations
21017
World Ranking
2704
National Ranking
1342

Overview

Surya Ganguli is affiliated with Stanford University in the United States and has contributed extensively to the fields of Neuroscience and Computer Science. Their research spans numerous topics related to neural dynamics, brain function, and artificial intelligence, among others.

Their work covers several main topics including:

  • Neural dynamics and brain function
  • Neuroscience and Neuropharmacology Research
  • Neural Networks and Applications
  • Advanced Memory and Neural Computing
  • Memory and Neural Mechanisms
  • Stochastic Gradient Optimization Techniques
  • Domain Adaptation and Few-Shot Learning

Ganguli has published in key research venues, often contributing to:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature
  • Neuron
  • Nature Communications

Frequent coauthors in Ganguli's networks include:

  • Daniel Yamins
  • Daniel Kunin
  • Aran Nayebi
  • Ben Sorscher
  • Lisa M. Giocomo

Highlighted recent papers authored or coauthored by Ganguli include:

  • "Pruning neural networks without any data by iteratively conserving synaptic flow," 2020, arXiv (Cornell University)
  • "Catalyzing next-generation Artificial Intelligence through NeuroAI," 2023, Nature Communications
  • "Fundamental bounds on the fidelity of sensory cortical coding," 2020, Nature
  • "An approximate line attractor in the hypothalamus encodes an aggressive state," 2023, Cell
  • "Coupling of activity, metabolism and behaviour across the Drosophila brain," 2021, Nature

The scientist's research is primarily focused on Artificial Intelligence as a subfield of Computer Science, as well as Cognitive Neuroscience and Cellular and Molecular Neuroscience within the broader discipline of Neuroscience.

Ganguli's contributions promote an understanding of complex neural systems through computational and experimental methods, integrating concepts from both technological and biological perspectives.

Best Publications

  • Deep Unsupervised Learning using Nonequilibrium Thermodynamics

    Jascha Sohl-Dickstein;Eric Weiss;Niru Maheswaranathan;Surya Ganguli

  • Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

    Yann N Dauphin;Razvan Pascanu;Caglar Gulcehre;Kyunghyun Cho

  • Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

    Andrew M. Saxe;James L. McClelland;Surya Ganguli

  • Continual Learning Through Synaptic Intelligence.

    Friedemann Zenke;Ben Poole;Surya Ganguli

  • A deep learning framework for neuroscience

    Blake A Richards;Timothy P Lillicrap;Philippe Beaudoin;Yoshua Bengio;Yoshua Bengio

  • Deep knowledge tracing

    Chris Piech;Jonathan Bassen;Jonathan Huang;Surya Ganguli

  • Holistic Evaluation of Language Models

    Unknown

  • Cortical layer–specific critical dynamics triggering perception

    James H. Marshel;Yoon Seok Kim;Timothy A. Machado;Sean Quirin

  • On the expressive power of deep neural networks

    Maithra Raghu;Ben Poole;Jon M. Kleinberg;Surya Ganguli

  • SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks

    Friedemann Zenke;Surya Ganguli

  • SuperSpike: Supervised learning in multi-layer spiking neural networks

    Friedemann Zenke;Surya Ganguli

  • Exponential expressivity in deep neural networks through transient chaos

    Ben Poole;Subhaneil Lahiri;Maithreyi Raghu;Jascha Sohl-Dickstein

  • On simplicity and complexity in the brave new world of large-scale neuroscience

    Peiran Gao;Surya Ganguli

  • Memory traces in dynamical systems

    Surya Ganguli;Dongsung Huh;Haim Sompolinsky

  • Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

    Alex H. Williams;Tony Hyun Kim;Forea Wang;Saurabh Vyas

  • Pruning neural networks without any data by iteratively conserving synaptic flow

    Hidenori Tanaka;Daniel Kunin;Daniel L. K. Yamins;Surya Ganguli

  • A theory of multineuronal dimensionality, dynamics and measurement

    Gao P;Trautmann E;Yu B;Santhanam G

  • Deep Knowledge Tracing

    Chris Piech;Jonathan Spencer;Jonathan Huang;Surya Ganguli

  • A Multiplexed, Heterogeneous, and Adaptive Code for Navigation in Medial Entorhinal Cortex.

    Kiah Hardcastle;Niru Maheswaranathan;Surya Ganguli;Lisa M. Giocomo

  • Compressed Sensing, Sparsity, and Dimensionality in Neuronal Information Processing and Data Analysis

    Surya Ganguli;Haim Sompolinsky

  • Environmental boundaries as an error correction mechanism for grid cells.

    Kiah Hardcastle;Surya Ganguli;Lisa M. Giocomo

  • Deep Learning Models of the Retinal Response to Natural Scenes

    Lane T. McIntosh;Niru Maheswaranathan;Aran Nayebi;Surya Ganguli

Frequent Co-Authors

Ben Poole
Ben Poole Google (United States)
Jascha Sohl-Dickstein
Jascha Sohl-Dickstein Google (United States)
Stephen I. Ryu
Stephen I. Ryu Stanford University
Lisa M. Giocomo
Lisa M. Giocomo Stanford University
Krishna V. Shenoy
Krishna V. Shenoy Stanford University
Haim Sompolinsky
Haim Sompolinsky Hebrew University of Jerusalem
Yoshua Bengio
Yoshua Bengio University of Montreal
Mark J. Schnitzer
Mark J. Schnitzer Stanford University
Richard H. R. Hahnloser
Richard H. R. Hahnloser University of Zurich

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