Dhruv is a Silicon Design Engineer at AMD building scalable infrastructure systems, with a passion for creating technology that solves real-world problems.
Dhruv is a Silicon Design Engineer at AMD building scalable infrastructure systems, with a passion for creating technology that solves real-world problems.
Dhruv is a Silicon Design Engineer at AMD building scalable infrastructure systems, with a passion for creating technology that solves real-world problems.
Experience
Advanced Micro Devices
Silicon Design Engineer II
June 2022 to Present
At AMD, I focus on developing scalable infrastructure to improve the robustness of emulation-based verification for flagship x86 processors. I’ve developed automated systems in Python and Perl, leveraging RabbitMQ and Slurm Scheduler workflows, that have eliminated over 200 monthly engineering hours. Furthermore, I engineered tools to bridge gaps in regression infrastructure, effectively improving emulation-based debug rate to 98%.
I used Langchain and FastAPI to develop LLM tools to improve bug triaging and provide debug teams with co-pilot assistance. I've also debugged functional and infrastructural issues found by the testbench, working across RTL, Assembly, and SystemVerilog code, and have implemented 8 logging and verification modules to improve testbench robustness. My contributions were recognized with a Talent Spotlight Award in 2024.
Marvell Technology
Engineering Intern
June 2021 to August 2021
During my internship at Marvell Semiconductor, I acquired proficiency in SystemVerilog and UVM methodology, which I leveraged to resolve hardcoded nanosecond time delays into clock-based delays in pre-existing verification kits. I engineered a foundational testbench and verification kit for the UVM-based verification of elementary FIFO RTL components and extended its use across 21 FIFO types.
University of Massachusetts-Amherst
Bachelor of Science | Computer Engineering
August 2018 to May 2022
As an undergrad at UMass Amherst, I served multiple roles that helped me develop leadership and technical skills. As president of UMass' Graphic Design club for six semesters, I led a leadership team of six, oversaw the organizing of design contests and events, and helped register over 100 new members. I worked as a Teaching Assistant for ECE 371 (Security Engineering), where I created labs for students, assisted the professor with lectures, graded examinations, and held office hours. I also served as a Technical Assistant for the Nursing and Engineering Innovation Center, where I set up and managed the center's contacts database.
Projects
Vuetor
iOS Application
May 2023 - December 2023
I developed an AI-powered tutoring platform that enables users to scan physical text for customized genAI-based learning assistance. I designed and built the user interface using UIKit and SwiftUI frameworks, implemented real-time text detection with VisionKit, and constructed a Python-based Flask API with PostgreSQL database to handle user authentication and OpenAI API integration.
SafeX
Motorcycle Helmet System
August 2021 - May 2022
For my undergraduate capstone project, I worked as apart of an interdisciplinary engineering team to develop an intelligent helmet system for motorcyclist safety. As computer vision lead, I implemented computer vision algorithms using YOLOv5 and OpenCV that achieved 99% accuracy in blind spot detection. Incorporating BLE protocols for communication between cameras and the helmet module, I also designed and 3D-printed specialized helmet attachments with LED-based visual alerts using embedded C and SPI.
UDistance
iOS Application & Sensor System
December 2020
As a HackUMass project, I worked on UDistance a hardware-software system to help students social-distance effectively. I developed an iOS application using Swift to display real-time population density in campus buildings. This app sourced data from a Firebase RTDB, which was populated by a collection of embedded Arduino system with IR sensors to track foot traffic. I implemented geofencing functionality for individual buildings using the Radar.io API to provide in-app alerts for users entering overcrowded areas.