Research Intern with Dr. Andrea Matic
May 2024 - Present
- Improving the robustness of 3D person detection in indoor environments to withstand adverse conditions such as occlusion and poor lighting.
- Running Camera based methods (BEVDet, BEVDet4D, BEVDepth), LiDAR based methods (CenterPoint, PointPillars), and Camera-LiDAR methods (BEVFusion) on Audi and JackRabbot datasets using mmdetection3d toolbox.
Research Intern with Professor Gerhard Rigoll 's Lab
March 2024 - Present
- Working on 3D object detection and tracking through multi-modal sensor fusion (camera and 4D radar) using nuScenes and View of Delft (VOD) datasets.
- Implementing BevDet pipeline with VOD dataset and enhancing the radar encoder architecture.
- Improved the model performance by 14 mAp.
Research Intern with Professor Federico Tombari's Lab
October 2023 - February 2024
- Worked with the computer vision team at the CAMP Chair on multimodal learning for autonomous driving utilizing data from different modalities (text, 2D image, and lidar point cloud).
- Transformed Lidar 3D point clouds to depth images.
- Finetuned the ImageBind model using text, camera images, and depth images using nuScenes dataset.
Participant in Google's Computer Science Research Mentorship Program
September 2021 - Decemer 2021
- Mentored by Dr. Leo Cheng, a Google research scientist, regarding research pathways in machine learning and data science.
- Attended a series of individual and pod meetings as well as workshops about research in computer science.
Research Intern with Professor Shady Elbassuoni
May 2021 - May 2022
- Conducted literature review regarding using deep learning models to optimize the buildings’ operating costs.
- Worked on preprocessing the gathered data, analyzing Beirut weather data, and coming up with useful insights.