Aiman Jalil

• Project: Perception Team for Indian OEMs.
• Description: Adapting Bosch MPC3 for Indian Road Scenarios.
• Technologies/Frameworks: Python, PyTorch, TensorFlow, OpenCV, Deep Learning, Computer Vision, Data Engineering.
• Responsibilities:
• Training CNN models (Centernet) for Animal Detection to be used as a pre-labeler for MPC3 model improvement.
• Developed CNN model (yolov5) and Inferencing module with Multi-Model approach for Animal Video Tagging for Data Collection.
• Developed the Camera Interface (Oak-D) for IOEM Data Collection.
• Perception Component development for Animal Detection (ADET) in the Bosch Front Video Camera (MPC3evo).
• Data Engineering and Analysis for IOEM Data.
• Collaborating with cross-functional teams to integrate perception components into larger ADAS frameworks.
• Conducting rigorous testing and validation to ensure high accuracy and reliability of perception systems.
• Achievements: Rockstar Award for DL Filter Initiative
• Team Size: 5

• Project: Comprehensive Environment Model (CEM)
• Description: CEM provides multi object tracking info/fused output to Driving Functions for Autonomous Driving
• Module: Environmental Model Framework (EMF)
• Customers: Honda
• Technology/Framework: C++,Python
• Responsibilities:
• Implementation of Scheduling and Error Handling of CEM components
• Writing Automation scripts for various project use cases
• Sprint Planning, Sprint review, Sprint retrospective, Defining Product Backlog , Prioritizing items, Stake Holder interaction
• Bug Fixes, Google test, MISRA fixes(QAC)
• Design, Development with Unit and Simulation(SIL) testing
• Code, Test, Design Inspection and Reviews
• Writing L4 Requirement and Review
• MLC and Functional Safety Activities
• Achievements: Spot Award for Q4 Performance and Building Trust with Counterparts.
• Team Size: 2

• Project: Lateral Dynamics Support (LDS), Road Sign Functions (RSF) and Road Sign Recognition (RSR)
• Description: Level 2 Autonomous Driving System that provides Lane and Road Sign Support based on inputs by Bosch MPC2.5, SVC2.5 and MPC3 cameras
• Customers: Ferrari, Jaguar Land Rover, Maserati, Honda, Great Wall Motors, JAC, BJEV, SAIC, SGMW and Chery
• Technology/Framework: C++, Deep Learning
• Responsibilities:
• Analyzing customer requirements
• Development of RSF features: Speed Limit Assist (SLA), Intelligent Speed Assist (ISA), Electronic Horizon Reconstruction (EHR) and LDS features: Traffic Jam Assist (TJA-ICA), Lane Keep Assist (LKA), Lane Departure Warning (LDW)
• Development of RSR Classifier Engine (Computer Vision) - Classifies Road Signs, using Deep Learning Algorithms, considering worldwide traffic scenes.
• Requirement Engineering: IBM Rational DOORS
• Unit Testing: Google Test/Squish Coco, Simulation(SIL) - ADTF
• Achievements:
• Awarded "One-Time Award" for my contribution towards Chinese OEM projects and RSR Classifier Engine.
• Successfully implemented TJA/ICA R79 EU regulations for Jaguar Land Rover, that helped achieve a 5-Star Euro NCAP safety rating.
• Team Size: 3

.

• Deputation to acquire function development responsibility of Road Sign Functions (RSF) for Bosch, India.
• Directly Interacted with Chinese OEM customers for solutions and requirement negotiations.
• Worked closely with team members to deliver project requirements, develop solutions and meet deadlines.
• Achievements: Received full function development responsibility from Bosch, China