Experience & Skills

Skills

 

Programming, Frameworks & Software:

  • Python
  • C, C++
  • Embedded C
  • Assembly
  • Verilog
  • SQL
  • MATLAB
  • Vivado, Quartus
  • PyTorch, TensorFlow, TensorRT
  • Networking
  • Qt Framework
  • System Administration
 Specializations:

  • IoT and Remote Monitoring
  • Edge Device application design
  • Industrial Automation
  • LoRaWAN Technology
  • AWS
 Embedded & Hardware:

  • NVIDIA Jetson (Xavier, Orin, Nano)
  • Raspberry Pi
  • Arduino
  • ESP32 / NodeMCU
  • PLCs

 

Experience

Mississippi State University | PhD Student

August 2022 – Present (Expected Graduation Date: May 2027)

 

  • Implementing runtime partition selection for neural networks using pre-profiled layer execution costs under varying network and temperature conditions, achieving a 2.06x FPS increase on NVIDIA Jetson Orin Nano running YOLOv8
  • Building an edge-assisted multi-camera 3D perception system that combines computer vision with camera geometry to estimate objects’ 3D position, size and orientation for real-time low-latency situational awareness and safety monitoring
  • Training YOLOv8 and YOLOv3-tiny with quantization-aware training to benchmark accuracy against baseline FP32 inference
  • Designing a wireless mesh network on Arduino using APC220 radios for reliable transmission of soil moisture data
  • Designing and instructing the course Construction Cyberinfrastructure (ConstructionCI), covering modules on IoT, edge AI and digital technologies for civil engineering applications
  • TA for classes: Microprocessors (Assembly & C), Digital System Design (SystemVerilog) and Embedded Systems (Embedded C)
  • Publication: Environment-Aware Dynamic Partitioning for Real-Time Vision Inference on Resource-Constrained Edge Devices (Submitted)

 

Xipiter UAS, Mississippi State University | Software Co-Lead

August 2022 – August 2024

 

  • Developed an autonomous flight system for a fixed-wing aircraft using ROS2 (Robot Operating System)
  • Deployed YOLOv8 on an NVIDIA Jetson Xavier for real-time object detection and localization using onboard vision and flight telemetry for autonomous in-flight payload delivery missions
  • Collaborated with airframe and controls teams to interface flight software with servo actuators and onboard avionics

 

Aerience Air Science & Contamination Control Pvt. Ltd. | Director (Embedded Systems)

April 2019 – August 2021

 

Embedded Development:

  • Built a Qt-based GUI application on the Raspberry Pi for a portable duct leakage tester with integrated wireless pressure sensors to measure pressure drop and locate duct leaks
  • Programmed a PLC to communicate with a Raspberry Pi for transmission to an AWS server and modification of PLC parameters for remote monitoring support
  • Reprogrammed the firmware of Dragino LSN50v2 LoRa node to add support for external I2C temperature and humidity sensors
  • Integrated LoRaWAN-based wireless temperature, humidity and pressure sensors to a standard LoRaWAN gateway as well as a Raspberry Pi-based gateway to assess proper functioning of field devices

Team Leader:

  • Led a team to design the front-end of a remote monitoring system to monitor the proper functionality of Air Handling Units

Industrial Automation & Electronics:

  • Designed a portable ‘Duct Leakage Tester’ using high RPM Brushless DC motors to find and seal leakages in ducting systems, ensuring efficiency
  • Designed and programmed the function logic of a VFD (Variable Frequency Drive) to control the speed of a fan (NOVENCO Axial Flow Fan ZerAx AZL) and transmit the same using a Raspberry Pi to control the fan speed remotely

System Administrator:

  • Deployed Windows Server 2019 and setup an Active Directory with Group Policy to better manage the devices within the organization
  • Setup a forwarding DNS server using AWS and OpenDNS for network filtering and security. Additionally, deployed DNSCrypt to prevent DNS Leak
  • Setup a PPTP and OpenVPN based VPN to have field devices connect and use the resources with the organization