Daniel Soudry

Welcome to my home page !

I am an associate professor and Schmidt Career Advancement Chair in AI, working in the Deparment of Electrical & Copmuter Engineering at the Technion, in the area of machine learning. I am especially interested in all aspects of neural networks and deep learning: see Research for my current research, and Background for a more general background.

I am looking for highly motivated and excellent MSc/PhD students and Post-Docs with similar research interests to join our team! (More Info)

Short Bio

I did my post-doc (as a Gruss Lipper fellow) working with Prof. Liam Paninski in the Department of Statistics and the Center for Theoretical Neuroscience at Columbia University.

I did my Ph.D. (2008-2013, direct track) in the Network Biology Research Laboratory in the Department of Electrical & Computer Engineering at the Technion, Israel Institute of Technology, under the guidance of Prof. Ron Meir.

In 2008 I graduated summa cum laude with a B.Sc. in Electrical Engineering and a B.Sc. in Physics, after studying in the Technion since 2004.

My Complete CV

Recorded Talks

Talks for the general audience:

Talks that require a machine learning background:

In the Press

  • I was selected to The Marker’s “40 under 40” list.
  • A short public relation movie on the collaboration with Intel.

News

--- May 1st 2024 ---

The paper “How Uniform Random Weights Induce Non-uniform Bias - Typical Interpolating Neural Networks Generalize with Narrow Teachers” has been accepted at ICML 2024, as a Spotlight presentation!

--- January 24th 2024 ---

The paper “Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators” has been accepted at ICLR 2024.

--- January 24th 2024 ---

The paper “The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting - An Analytical Model” has been accepted at ICLR 2024.

--- December 28th 2023 ---

Welcome Itamar, Gil and Gon!

--- September 21st 2023 ---

The paper “How do Minimum-Norm Shallow Denoisers Look in Function Space?” has been accepted at NeurIPS 2023.

--- September 21st 2023 ---

The paper “DropCompute - simple and more robust distributed synchronous training via compute variance reduction” has been accepted at NeurIPS 2023.

--- September 21st 2023 ---

The paper “Explore to Generalize in Zero-Shot RL” has been accepted at NeurIPS 2023.

--- April 25th 2023 ---

The paper “Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond” has been accepted at ICML 2023.

--- April 25th 2023 ---

The paper “Continual Learning in Linear Classification on Separable Data” has been accepted at ICML 2023.

... see all News