algorithms

PCCFD - Predictive Complex Computational Fluid Dynamics

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B9 L2 H1

The PCCFD workshop will focus on cutting-edge research in the field of algorithmic development for CFD and multi-scale complex flow simulations.

Efficient Machine Learning across Hardware, Software, and Algorithms

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B2 L5 R5209

Deep neural networks (DNNs) are revolutionizing computing, necessitating an integrated approach across the computing stack to optimize efficiency. In this talk, I will explore the frontier of DNN optimization, spanning algorithms, software, and hardware. We'll start with hardware-aware neural architecture search, demonstrating how tailoring DNN architectures to specific hardware can drastically enhance performance.

Machine learning models gather momentum

1 min read ·
New methods for training machine learning models are quicker and more accurate than current approaches, previously considered state-of-the-art.

Ferrofluid surface simulations go more than skin deep

1 min read ·
Computer models efficiently and accurately simulate the magnetic responses of ferrofluids by considering only the fluid’s surface.

Harnessing the particle-tracking power of the algorithm

1 min read ·
A simple camera system paired with a sophisticated image-processing algorithm can achieve faster and more accurate reconstructions of particle flow.

Ruogu Ding

Ruogu Ding obtained his Master's Degree in Computer Science under the supervision of Professor Panagiotis Kalnis at InfoCloud Research Group (CLOUD) in King Abdullah University of Science and Technology (KAUST). Prior to that, Ruogu received his Bachelor's degree in Computer Science from Peking University in July 2009. He worked as a research assistant on large-scale sequence assembly algorithms 2009-2010 at Peking University. Ruogu is currently serving as a Technology Partner at MiningLamp, a fast-growing startup aiming to provide enterprises with big data solutions. He worked on Algorithm

Peter Richtarik

Professor, Computer Science
Professor Richtárik specializes in big data optimization and machine learning. He is known for his work on randomized coordinate descent algorithms, stochastic gradient descent and federated learning.

Konstantin Mishchenko

Ph.D. Student, Computer Science
Konstantin Mishchenko is a Ph.D. candidate at Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Peter Richtarik in his research group. Education and Early Career Konstantin Mishchenko obtained his bachelor degree in Computer Science and Physics from Moscow Institute of Physics and Technology in 2016. After that in 2017, he received his master degree in Machine Learning MASH from Université Paris Dauphine in Paris, France. Konstantin had many internships during his studies. The most recent was with Amazon in

Elnur Gasanov

Elnur Gasanov is a master student at Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Peter Richtárik in his research group. Education and Early Career Elnur Gasanov obtained his bachelor degree in Applied Mathematics and Physics from Moscow Institute of Physics and Technology (MIPT) in Moscow, Russia in 2018. Research Interest His research interests are in optimization and machine learning. Education Profile ​B.Sc., Applied Mathematics and Physics, Moscow Institute of Physics and Technology (State

Amin Allam

Amin Allam obtained his Ph.D. in Computer Science at the King Abdullah University of Science and Technology (KAUST) under the supervision of Prof. Panagiotis Kalnis in 2017. Amin is a lecturer in the Computer Science department, Faculty of Computers and Information, Cairo University, Egypt. He got his bachelor's degree in Computers and Information in 2003 from Cairo University. Then, he got a Master's degree titled "An Arabic-Disambiguating Engine Based on Statistical Approaches" in Computer Science from the same university in 2008. Research Interest Amin's research interests include

Ali Charara

Ali Charara obtained both, his MS Degree and PhD Degree from Computer Science at KAUST in 2011 and 2018 respectively. His master thesis supervisor was Alyn Rockwood and his PhD thesis supervisor was David Keyes. Ali's research interests were in High Performance Computing with a focus on parallel computing and algorithms using multicore and manycore Computer Graphics Units. Education Profile MS Degree, Computer Science, KAUST (2011) PhD Degree, Computer Science, KAUST (2018)

Ahmed El-Roby

Ahmed El-Roby obtained his M.S. degree in Computer Science under the supervision of Professor Panagiotis Kalnis at InfoCloud Research Group (CLOUD) in King Abdullah University of Science and Technology (KAUST). He got his Ph.D. in Computer Science from the David R. Cheriton School of Computer Science at the University of Waterloo. Currently, Ahmed is working as an Assistant Professor at the School of Computer Science at Carleton University in Ottawa, Ontario. Research Interests Ahmed's research interests included Data Integration, Automatic Linking, User Feedback, Artificial Intelligence, and