Ali Haidar Email & Phone Number

Beirut, Beirut Governorate, Lebanon

• Developed and implemented a real-time camera calibration system with the Spinnaker FLIR API, enabling precise 3D reconstruction. This system facilitated accurate alignment of multiple camera views, significantly.
• Optimized a C++ multi-threaded pipeline for detecting and tracking foreign object debris (FOD) on airport runways using the YOLO framework and Kalman filters.
• Automated the deployment process for AI models by developing bash scripts in Linux to build inference engines, ensuring seamless integration of AI models into production environments. Through this experience, I gained.
• Gained extensive expertise in image preprocessing and utilized OpenCV to refine images for analysis, ensuring high-quality input for downstream AI models, thereby improving overall system accuracy and performance.

Beirut Governorate, Lebanon

• Developed a CSP entitled “Electronic Waste Mismanagement in Beirut Southern Suburbs” under the supervision of AUB CCECS, in partnership with Ecoserv NGO, and in collaboration with five fellow USAID scholars to promote.
• Delivered awareness workshops about e-waste environmental and health hazards and performed field inspections to collect data for surveying and assessment.
• Developed a prototype of an AI-powered recycling system for e-waste classification, utilizing the YOLO framework for object detection and integrating sensors and actuators with Arduino and Raspberry Pi.

Beirut, Beirut Governorate, Lebanon

• Developed electrical designs for MV/LV power supply and distribution networks, ensuring compliance with global standards and project specifications.
• Designed earthing systems for enhanced safety and system reliability.
• Collaborated with multidisciplinary engineering teams to optimize designs and align with client requirements.
• Ensured project deliverables met both technical and regulatory standards while maintaining efficiency and cost-effectiveness.

Beirut Governorate, Lebanon

• Conducted measurements on vector network analyzer to record biosensors’ response to change in nicotine concentrations.
• Measured dielectric variations with respect to changes in nicotine concentration over broad frequency spectrum using a dielectric probe, providing novel data.
• Optimized input data by performing featuring engineering and utilizing feature forward selection wrapper method.
• Developed a Gaussian Process Regression (GPR) model to predict nicotine concentrations from radio-frequency signals, particularly scattering parameter data, achieving 95% accuracy on a dataset of 100 real saliva samples.

Rouen, Normandy, France

• Performed image segmentation tasks on multi-institutional pre-operative MRI scans from the Brain Tumor Segmentation (BraTS 2020) Challenge dataset to segment heterogeneous brain tumors, particularly gliomas.
• Acquired a comprehensive understanding of the BraTS20 dataset including its multimodal format (T1, T1ce, T2, FLAIR) and its segmentation labels of the brain tumor.
• Explored and tested diverse preprocessing techniques applicable to 3-dimensional images, such as Numpy array conversion, scaling, cropping, transforming, data augmentation, and data splitting techniques.
• Investigated the composition and building blocks of the U-net architecture, prominently used for segmentation tasks.
• Researched and experimented with various loss functions employed for segmentation tasks, such as dice loss, binary cross-entropy, focal loss, and batch dice loss.
• Implemented region-based training by modifying the segmented mask to encompass overlapping regions (namely whole tumor, tumor core, and enhancing tumor) instead of the default segmented labels.

• Represented USAID scholars within the LEAD committee, successfully advocating for scholar-led initiatives and improvements.
• Organized events and workshops that increased student participation by 80%, fostering stronger community bonds and enhancing professional development opportunities.

Bachelor Of Engineering - Be, Electrical And Computer Engineering, High Distinction Cgpa: 3.96/4.00

- Graduated with High Distinction, constantly being placed on the Dean’s Honor List. - Received the Dean’s Award for Creative Achievement.

Track, Control And Robotics, 4/4

Completed core modules including Control Systems, System Design and Analysis, System Identification, Instrumentation, and Machine.

High School Diploma, General Sciences, 18.11/20.00