Abduallah Mohamed

Motion, Behavior and Deep Learning Research Scientist, PhD

Applied Research Scientist @Meta Reality Labs LinkedIn, Github, Scholar, Twitter, Resume

Abduallah Mohamed, BSc EE, MSc CE, PhD ECE abduallah.adel.omar (at) gmail.com

I was part of Mobile Automation and Sensing Systems lab @(UT Austin) lead by my advisor Prof: Christian Claudel and my advisor Prof: Ahmed Tewfik while being co-advised by Prof: Mohamed Elhoseiny @(KAUST/ Stanford).

** I'm currently co-supervising PhD students working on motion related problems, please reach out if you seek collaboration **

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About

I specialize in crafting practical and effective deep models tailored for real-world usability, with a primary focus on solving intricate challenges related to motion problems

Deep/Machine Learning Expertise:

Proven track record in developing real-time deep learning models for tasks such as sensor data fusion and motion/trajectory analysis using various sensors.
Emphasis on creating solutions with real-time functionality, low memory footprint on edge devices, and adherence to power requirements.
Applied experience in different domains such as AR/VR/XR, self-driving vehicles and robotics.
Understanding of edge devices, embedded systems and HW/SW integration.
Heavy expertise in developing 0->1 POC (Proof of concept).

Spatio-temporal and Motion Analysis:

Specialization in real-time deep models for multiple-agent motion, action, and trajectory forecasting/understanding, considering uncertainty in predictions.
Research focuses on devising novel metrics for evaluating the performance of such models.
Understanding of control theory and motion dynamics.

Outdoor and Indoor Localization:

Industrial experience in non-visual localization employing classical and data-driven approaches.
Pioneered the development of multi-level data fusion systems, ensuring robust localization solutions.

Sensor Expertise:

Proficient with IMUs, magnetometers, and ultrasonic technologies for developing heading and tracking systems.
Integrative approach using both physics and data-driven solutions.
Familiarity with GNSS and similar positioning systems.

Scholarly Achievements:

Author of 1000+ citations, with publications in renowned venues such as CVPR, ECCV, and AC.
Active involvement as a reviewer for top-tier conferences.
Co-supervision of Ph.D. students engaged in multidisciplinary research.

People:

Ability to tech lead multiple projects across multiple orgs and different teams functionalities.
Technical alignment between HW/SW teams to reach consistent project executions.

Programming Proficiency:

Skilled in Python, deep learning libraries, C++, Matlab, and software engineering.

Services

AC/PC: ACML 2022/23, SMARTTECH 2022

Reviewer: CVPR, NeurIPS, ICML, IEEE ITS, IEEE TCSVT, Transportation Research Part C.

Collaborators

Tian Lei, Kun Qian, Amr Abdulazim, Ehab AlBadawy, Huancheng Chen, Zhangyang(Atlas) Wang, Deyao Zhu