Hadi's Homepage - Experience

Summary: I am passionate about fundamental applied research. I have the capacity to quickly grasp new concepts, come up with new ideas, and efficiently implement them. This has enabled me to smoothly change my field of work/research several times and constantly deliver. I have experienced different phases of maturity over the years, ranging from being a team member delving deep into pure research to serving as technical lead and project team lead roles driving innovation in product development. Currently, I am leading applied research in the area of deep learning and computer vision at Shell.

[Adjunct Assistant Professor @ Computer Vision Lab (CV Lab)]

Leading research on Deep Learning and Computer Vision

Shell

[Lead Research Scientist]:

Lead the technical and research track of deep learning/computer vision.
Initiated several R&D collaborations with top universities and research institutions. I keep on (co)supervising Masters, Ph.D. students, and PostDoc researchers from these institutions.
Made fundamental contributions to Shell's affinity to and adoption of deep learning based imaging and computer vision systems. Co-led the largest computer vision project in Shell focused on asset maintenance and integrity recognition, and therein a project team of data scientists/engineers.

[Senior Machine Learning Scientist]

Developed machine learning models for predicting seismicty in order to optimize production plans. Developed statistical models for analyzing seasonality therein.
Developed deep learning based semantic segmentation models to detect coherence energy is seismic inversion tomography systems.

[Research Scientist]

Pioneered the ideation and led the first implementation of wireless IoT (LoRa and NB-IoT) based monitoring and imaging systems in the Oil and Gas industry.
Developed novel methodologies for optimizing seismic acquisition and image reconstruction systems using deterministic non-uniform wavefield subsampling.

[Researcher][PhD student]

Developed novel distributed sparse regression algorithms using dual-subgradient optimization and consensus averaging with theoretical convergence analysis.
Developed dynamic multi-dimensional scaling (dynamic MDS) and dynamic principal component analysis (dynamic PCA) algorithms for mobile configuration tracking.
Developed novel compressive sensing (CS)-based blind multi-source time-difference-of-arrival (TDoA) and received signal strength (RSS) localization (blind parameter estimation) algorithms.
Developed several novel adaptive filters (modified EKF, UKF, particle filters) for motion prediction in partially connected multi-agent cooperative systems.
Developed multi-source localization and tracking algorithms in underwater acoustic sensor networks and subsurface monitoring systems.