Vikas Parameswaran

Passionate B.Tech graduate looking to leverage my creative problem-solving skills and versatile thinking processes to learn, innovate, and make meaningful contributions, while consistently striving for self-improvement and growth.

• Data Analytics using Excel

• Electronic system level Design and Verification
• Digital Electronics
• Microcontroller programming
• Artificial intelligence and Machine Learning

• Captain of the school squash team.
• Competed in a national-level squash tournament and two state-level tournaments.
• Actively participated in multiple social service initiatives through the National Cadet Corps (NCC), fostering community engagement and leadership skills.

I would like to assure you that all the information provided in this document is true and free of any fraudulent/untrue entries.

• Designed and implemented a Digital Signal Oscilloscope capable of amplitude scaling, time scaling, and Fast Fourier Transform (FFT) operations.
• Used Figma to design a custom user interface, which was integrated into Python using the tkinter-designer library to convert the design into functional Tkinter components.
• Leveraged matplotlib.animation to dynamically visualize real-time signal manipulation such as shifting and scaling.

• Developed an intelligent parking space detector using a binary Support Vector Machine (SVM) classifier and OpenCV in Python.
• Constructed a custom dataset by extracting frames of occupied and unoccupied parking spots from a drone-captured parking lot video at different timestamps.
• Processed live video input using OpenCV to overlay color-coded indicators (green for empty, red for occupied) on detected parking spaces in real time.

• Designed an analog beta (β) meter to measure the current gain of NPN and PNP transistors.
• Implemented a Widlar current source to provide a constant current to the transistor base, with a 1kΩ resistor at the collector.
• Measured the collector voltage (proportional to β) using an ADC and displayed the value via a 7-segment display module.

• Deployed a quantized RESNET-18 model for image classification on the Zynq UltraScale+ ZCU104 FPGA.
• Converted a pretrained floating-point model to INT8 precision for optimized inference on hardware.
• Compiled the quantized .xmodel to generate the deployable DPU.xmodel, compatible with the DPUCZDX8G IP core.
• Executed the model on the FPGA's DPU for efficient, high-speed image classification.

• VLSI
• Computer Networks

• Captain of the school squash team.
• Competed in a national-level squash tournament and two state-level tournaments.
• Actively participated in multiple social service initiatives through the National Cadet Corps (NCC), fostering community engagement and leadership skills.

• Tamil
• English

I would like to assure you that all the information provided in this document is true and free of any fraudulent/untrue entries.