Work experience

• Data Scientist

  WHOOP

  2021.09-Current

  (5 years)

  (4 years 6 months) Operating at the intersection of signal processing and machine learning, I design and productionize algorithms that translate noisy physiological data into precise health metrics. Core Technical Ownership: Cuff-less Blood Pressure (R&D to Production): - Served as an algorithm designer for WHOOP’s novel blood pressure monitoring feature. - Owned the full technical lifecycle from initial R&D concepts to V4 production deployment. - Designed the deep learning model architecture and the end-to-end inference pipeline, solving critical challenges in extracting signal from PPG noise. Strength Trainer (Motion Intelligence): - Acting as the Data Science owner for the Strength Trainer feature. - Architected deterministic and ML-based algorithms to detect, classify, and score complex weightlifting movements using low-SNR IMU data. - Developed sanitization techniques to ensure accuracy across diverse user behaviors and hardware environments. System Architecture & Modernization: - Worked on modernization of the core Cardio Strain Score algorithm, migrating it to a scalable, high-performance API. - Designed optimization algorithms deployed in C++ (Edge) for real-time processing and Python for cloud-based inference. - Expanded the device's detection capabilities by developing machine learning models for automated workout detection and device wear location classification Tech Stack: Python, TensorFlow, PyTorch, C++ (Embedded/Edge), SQL, Signal Processing (DSP), Sensor Fusion.
• Algorithm Engineer

  PUSH (acquired by WHOOP)

  2019.10-2021.09

  (2 years)

  I worked on building and optimizing signal processing algorithms to detect and analyze weightlifting using IMU signals. During this time, I have: • Added real-time support for tens of exercises. • Created a generic real-time detection algorithm for barbell exercises. • Created an algorithm to estimate the barbell path during weightlifting. • Design algorithms for several weightlifting strength and endurance tests. • Add arm and bar kinematics to the sensor motion to calculate repetitions' velocities and other metrics VBT metrics
• Graduate Research Assistant

  University of Waterloo

  2017.05-2019.04

  (2 years)

  My research focused on analyzing human motion from Inertial Measurement Units. During this time, I have: • Built an inverse dynamics model of the human motion captured using inertial measurement units. • Built a biomechanical-based on-site ergonomics assessment tool with a graphic user interface. • Worked with my team to analyze the motion of bricklayers using the model I have developed. • Used machine learning algorithms to identify physical fatigue and safe working postures.
• Research and Teaching Assistant

  German Jordanian University

  2015.10-2017.04

  (2 years)

  (1 year 7 months) During my time at German-Jordanian University, I worked in teaching and research. I conducted laboratory sessions, review and tutorial sessions, graded exams, and advised students on their term projects. I assisted in many courses, including Dynamics, Engineering drawing and CAD, Thermodynamics, Fluid Mechanics, Digital Sytems, and Advanced Machine CAD courses. I was also responsible for prototypes fabrication and testing of several research projects, including Passive fluid micro-mixers, Lab-on-a-chip for colorimetric detection of nitrate in water, and Coating silicon wafers with silicon nano-particles using inkjet printing.
• Service Engineer Intern

  Abdullah Hashim Co. Ltd

  2013.05-2013.08

  (4 months)

Educational experience

• University of Waterloo

  System Design Engineering

  2017.01-2019.01

  (2 years)
• University of Jordan

  Mechanical Engineering

  2010.10-2015.01

  (4 years)

Certificates