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 - Pres.
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 - Pres.
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 - Pres.
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
