Syed Haseeb Raza

Supervisor: M.Sc Malte Oeljeklaus Project: InVerSiv - (Intelligent transport infrastructure for secure networked driving in the megacity) The project focuses on the perception of the environment using state-of-the-art Computer vision and Deep learning techniques. My role is to implement different methods to aid a car to perceive its environment using multiple sensors including cameras and radars. I am working with Nvdia Tx2 board and developing the software in Python.

I was part of an R&D project at the Computer Science department of TU Kaiserslautern. The project titled “DyMASH” dealt with programming and development of hybrid UAV’s that are capable of interacting with the environment. Aims: - Programming on Raspberry pi in C++ to control the Mikrokopter drone autonomously - Development of serial communication protocol to send commands to the flight controller of the drone. - Design of a linear controller - Integration of all system components in ROS.

Department: RF Optimization, Duration: 1.5 months, Project: Understand the RF optimization process and tools in detail. Tools learnt: MAPINFO, TEMS, KPI analysis (using online tools).

Description: Explored machine learning techniques to classify and understand signals acquired from the brain using Open BCI toolkit, in order to identify and classify signals from a person's brain. Following were the results: 1. Development of Hangman game in Java using Binary Classification of motor imagery signals. 2. 4 way classification of brain signals to control a robotic car. (BRAIN CONTROLLED ROBOT). Tools used: MATLAB (for signal processing and machine learning), Open BCI, Arduino, Open-Vibe.

Mobile Robots, Modeling and control of Robotic manipulators, 3D Computer vision, Cyber Physical Systems, networked mobile robot systems, Computational intelligence, Learning in Robotics, Deep learning for computer vision.

Probability, Computer Vision Fundamentals, Introduction to Artificial Intelligence, Digital Image Processing, Mobile Robotics, Digital Control Systems, Advanced Programming.