Danish Rahman (he/him)

Danish Rahman (he/him)

System Engineer | Mechanical Engineer | Autonomous Vehicles | Rehabilitation Robotics

Portfolio

Perturbation-based training for motivating gait training paradigms in elderly people

The aim of this research project is to develop gait training paradigms through the application of different types of perturbations while subjects are moving with an assistive walker. By analyzing variations in mobility and stability with changing perturbation regimes, it is envisioned that a mobile task-oriented training system can be created to reduce the rates of high-risk falls for elderly subjects. This project is an extension of the Tethered Pelvic Assist Device (TPAD), and is being conducted with the Columbia University Robotics and Rehabilitation Laboratory, in a multidisciplinary team of researchers ranging from robotics and medical backgrounds. The outcomes and results of this research project were published in Nature’s Scientific Reports here.

Rheinmetall Barzan Advanced Technologies - Unmanned Ground Vehicle (UGV) R&D

I designed, prototyped and tested multiple subsystems, for a fleet of electrified semi-autonomous UGVs. Throughout my time on the project, I was involved in various aspects of the system. Initially, I was responsible for the integration and optimization of sensors such as LiDARs, EO/IR cameras and RADARs, along with troubleshooting of drivetrain and electrical subcomponents. This culminated in the development of a quasi-static UGV performance simulator on Simulink and an intensive characterization campaign to test vehicle performance in harsh climates and terrain. Simultaneously, I worked on verifying the hardware-agnosticity of the vehicle’s Command and Control (C2) software, by developing a new proof-of-concept vehicle and integrating it with the C2. Upon completion, this led me to the more architectural and design-oriented role of System Engineer, where I was responsible for the definition of system requirements and architecture for the vehicles’ relevant subsystems. This included vehicle and sensor performance requirements along with autonomous features such as waypoint navigation, target tracking and multi-UGV cluster mission planning and estimation.

Texas A&M University - Design and development of a hybrid cooling system for the thermal management of CPV solar cells

Designed, fabricated and tested a prototype hybrid cooling system for solar cells, using varying air-water flow rates under adiabatic conditions. Testing was conducted to analyze the impact of two-phase flow regimes on the cooling efficiency in CPV cells. Through fluctuating air and water flow rates entering the test section from cross-flow and cell impingement interfaces, flow regimes were identified through visualization via a high-speed camera. From further image-based analysis, the flow-rate ratio was tuned to observe the progression of critical flow regimes for optimal cooling efficiency.