Mar. 2020 - Sep. 2020
Spent spectacular 6 months in the lovely Munich City. I was
fortunate enough to work on my Bachelor Project/Thesis in the
area of
Distributed Deep Reinforcement Learning. The
project was held in the chair of Robotics, Artificial
Intelligence, and Embedded Systems. This
project is associated with the
Human Brain Project
Organization
and
Neurorobotics Platform
Team.
During my stay in Munich, I was lucky to join multiple events
and hackathons including
HackRoboy with
amazing
Roboy Team and spending
time at this amazing building
UnternehmerTUM GmbH. Visiting
Max Planck Institute of
Quantum Optics
and discovering the amazing
research
they are doing in Quantum Machine Learning, Quantum Computing
and Tensor Networks. Adding to that, spending wonderful time at
the Chair for Computer Aided
Medical Procedures & Augmented Reality (
CAMP) at their
Virtual Reality Labs with my friend Omar. 😎
My favorite place there was Olympiapark! ❤️
Jul. 2020
One of the best things that happened to me in 2020 when I
received the acceptance email to attend DeepMind EEML Summer
School! Starting in 1st of July, during
my university exams and OpenMined fellowship, I was full of
excitement and enthusiasm to attend the school and I had a great
time learning from the best
researchers in the world of Deep Learning and Reinforcement
Learning from various companies and universities including
DeepMind, Facebook AI (FAIR), Google
Research, McGill University, Warsaw University, and University
College London. This 10 days was full of fun, learning,
discovering new fields and getting pieces
of advices and mentorship! Thank you EEML!! ❤️
Mar. 2020 - Now
We're an open, distributed research group working on
significantly improving learning systems and applying them
to the toughest problems humanity faces. We
do this by advancing theory and also building exceptional
open source tools. Manifold Computing is a fairly unique
research lab, formed from the thesis that
the biggest scientific problems we face as a civilization
will require progress on numerous fronts. One of these is
improving the theory and applicability
of modern learning systems, which despite significant
progress, do not scale well to multimodal, heirarchical and
data starved problems. Manifold Computing
is built on numerous collaborations, with folks from well
known research institutions like Harvard, UCL, TUM, Georgia
Tech, industry organizations like
Google, OpenAI, and Facebook.
you're interested in building the Infrastructure of
Intelligence, reach out!
My current work there focus on Research on Creating,
Managing, and Understanding Large,Sparse, Multitask Neural
Networks 🕸 & Working on new algorithms for
Neural Architecture Search with Differential Privacy 🕵🏻♂️
Jan. 2020 - Now
OpenMined is an open-source community whose goal is to make the
world more privacy-preserving by lowering the barrier-to-entry
to private AI technologies.
Working on various open-source projects ranging between python
development, multi-language libraries, federated learning,
infrastructure management. Adding to
that, being a Research Engineer working with Research scientists
on multimodal and multitask learning, neural architecture search
with differential privacy, and
federated reinforcement learning. Moreover, I recently got
accepted into 👉🏻
OpenMined-UCSF
Project for Data-Centric Federated Learning as Senior
Fellow
and I am Leading the Infrastructure team for multiple cloud
deployment of our
PyGrid
Platform as Peer-to-peer
Platform for Decentralized Data Science.
Oct. 2019 - Now
We are a multi-disciplinary team of scientists and engineers who
like doing research for fun. Our only objective is to publish
good machine learning research
that is useful and interesting. Our collaborators include
researchers from research institutions such as Google Brain,
University of Oxford, and Vector
Institute for Artificial Intelligence. Currently, Collaborating
with OATML Oxford Research Group on autonomous driving and
Bayesian deep learning, Building
OATomobile: A research framework for autonomous driving for
doing novel research, Experimenting with CARLA simulator for
novel research in reinforcement
learning and autonomous driving with Uncertainty-Aware Policy
Distillation. Building a Highly modular codebase for
reinforcement learning models training,
testing and visualization. Researching curriculum learning,
hierarchical reinforcement learning, selfdriving cars, and
neural network optimization.
Apr. 2020 - Oct. 2020
Creating artistic robots that can draw incredible portrait
paintings with neural style transfer Developing automated
pipeline for image modification &
enhancement methods using GANs and computer vision techniques
Helping with creating simulated environments for the robotic arm
and training RL algorithms
Building a distributed pipeline system for integrating the
software and hardware parts of the robots
Jun. 2019 - Oct. 2019
AI Engineer (Voice Emotion Recognition) was Responsible for Viva
Robot’s Visual and Emotional Perception, Implemented speech
emotion recognition system using
the State of the Art methods for viva robot
Mar. 2019 - Sep. 2019
Worked on Neurorobotics for the next Generation of Intelligent
Robots, Worked with the team of the neurorobotics platform on
building new environments and
simulations for distributed reinforcement learning agents
🇨🇦
Currently living in Canada with bears 🐻 and moose 🦌
🇩🇪
Spent time at the Technical University of Munich (TUM) and exploring the beauty of Germany
🇸🇦
Spent time with family in Riyadh and performed Umrah in my favorite cities Mecca and Medina 🤍
🇪🇬
During University and undergraduate studies
🇪🇬
My hometown and where I grew up with my family and friends.
