Work Experience

  • Working in a Real-time Networking Group focused on TSN (Time Sensitive Networking) /AVB (Audio Video Bridging) technology.
  • Develop embedded software for the NXP i. MX RT1180 crossover MCU with TSN Switch. The work is available on GitHub.
  • Applications include Industrial and Automotive

Technical Skills:

Programming Language: C
Embedded board:  i.MXRT1180
Operating System: FreeRTOS, Linux
Source control & collaboration: JIRA, BitBucket

Project: The AI-driven payload for miniaturized spacecraft using edge computing technology

  • Worked in the space systems research group at SnT,  University of Luxembourg
  • Developed AI algorithms on the embedded boards for detecting thermal anomalies on space electronics hardware. 
  • Performed system modeling of the space payload (PCB board)
  • The work involved assembly and testing of the payload at the CubeSat lab.
  • On 12th June, this “AI4Space” project was launched on the SpaceX Falcon 9 rocket. This research has the potential to increase the lifetime of satellites in orbit by detecting faults in space hardware.

Technical Skills:
Programming languages: Python
Embedded board: FPGA (Xilinx Ultrascale+ MPSoC), Raspberry Pi Zero
Operating System: Embedded Linux, Raspberry Pi OS
Software: Ttool
Source control & collaboration: Gitlab

  • Worked in PDK( Process Design kit) team as a Physical Verification engineer.
  • Developed design rule decks including DRC (Design Rule check), LVS (Layout vs Schematic), and QRC (Parasitic resistance, capacitance, and inductance extraction)  for the PDK.
  • Worked on high-performance Analog technologies and Bipolar technologies.
  • Co-operated with hardware teams in the USA and India.

Technical Skills:
Programming languages: PVL (Physical Verification Language), SKILL
Operating System: Linux
Software: Cadence Virtuoso, Cadence Assura Physical Verification, Cadence Quantus Extraction Solution
Source control & collaboration: DesignSync Cadence

Project: QC Methodology to check the consistency between pre and post-layout simulation of all the PDK components.

  • Worked with the PDK (Process Design Kit )team
  • Implemented Automation Software to enhance quality check (QC) flow and reduce the cost of fabrication.
  •  Designed the test methodology to check consistency between the different process design kits and detect the faults in the hardware components   

Technical Skills:
Programming languages: Perl, SKILL
Operating System: Linux
Software: Cadence Virtuoso
Source control & collaboration: DesignSync Cadence

  • Trained in Embedded systems with projects such as password-protected lighting systems, analog signal processing, etc
  • Learned to interface ADC, DAC, Keypad, GPS, and Graphical LCD with LPC812
  • Developed the software architecture for power management
  • Interpreted the hardware design using PCB schematic and datasheets

Technical Skills:
Programming languages: C
Hardware:  LPC812 (Arm cortex M0+ microcontroller)
OS: Windows
Software: LPCXpresso IDE

Project: Automated Weaving Machine

  • Researched the feasibility of an Automatic Weaving Machine
  • Studied various methods for weaving fabric
  • Researched the electrical designs of the machine and a simple electrical design was proposed using PLC, Servo Motors, and Motor Drivers.
  • Enhanced knowledge of Electrical Devices

Education

Highlights:

  • Participated in club MARS
  • Pursued Embedded Sytems specialization
  • Courses – Architecture and Synthesis of Hardware and Software Systems, Real-time Networks, Dynamic Systems, Embedded Systems, Systems Engineering( MBSE ), Algorithm and Computing, Cloud and Computer Networking, Modeling and Simulation, AI and Autonomous systems, Space Systems, Certification ( DO-178C)

Highlights:

  • Participated in the Music club, Robotics club, and Student Council
  • Courses – Microcontroller and its application, Embedded Systems Design, Analog and Digital Electronics, VLSI System Design, Digital Image processing, Digital Signal Processing

Technical Projects

  • The goal is to understand the implementation of deep learning algorithms for image classification on embedded devices with respect to memory and computation time.
  • Implemented deep learning algorithm from scratch in C language including Testing and Training for several epochs on the training dataset with CPU.
  • The implementation was modified for the CUDA platform and the trained algorithm was tested using Nvidia Jetson Nano 2GB RAM.
     Analysis was done on the memory, computation time, and hardware constraints (with or without GPU on the Nvidia hardware) for the implementation of different image classification Architectures.

Technical Skills:
Programming languages: C, CUDA C
Hardware:  Nvidia Jetson Nano
OS:  Linux4Tegra

  • Corodoro is a student project of a robotic system involving collaboration between a Rover and a Drone to navigate autonomously to explore sites of interest on the Moon. (The project video: Link)
  • A member of the SLAM (Simultaneous Localization and Mapping) team and worked on point-of-interest detection. 
  •  Implemented the algorithm of AR-tag detection on the drone and rover which involved camera calibration, AR-tag design, and C programming.
  • The testing was conducted in the ONERA lab, in France.
  • The project was presented for the IGLUNA event conducted in Lucerne, Switzerland in July 2021.

Technical Skills:
Programming languages: C
Hardware:  Odroid board, Intel D435 camera
OS:  Linux
Software: ROS

The design and implementation of the system-on-chip project that prints the acceleration values from the accelerometer on the computer screen and displays the direction of acceleration using two 7-segment displays.

Technical Skills:
Programming languages: VHDL
Hardware:  Zybo Development Board, 7- segment display, accelerometer
Software: Xilinx Vivado

The design and implementation of the Autonomous ground drone vehicle that has to move parts all around a factory. The drone must be able to follow a path marked by the black line on a white background. 

Technical Skills:
Programming languages: VHDL
Hardware:   Basys3 board, Infrared Sensors, 7-segment display
Software: Xilinx Vivado

The design and implementation of the Autonomous ground drone vehicle that has to move parts all around a factory. The drone must be able to follow a path marked by the black line on a white background. 

Technical Skills:
Programming languages: VHDL
Hardware:   Basys3 board, Infrared Sensors, 7-segment display
Software: Xilinx Vivado