Devang Sharma

• RTL to GDSII ASIC Design Flow:Hands-on training in full and semi-custom ASIC design using Cadence tools suite from RTL to tapeout, including STA.
• Digital IC Design: Gained deep practical understanding of transistors (MOSFET/BJT) and built optimized ICs from scratch using CMOS, pass transistor, and transmission gate logic.
• Verilog for an FPGA Engineer: Designed FSMs, ALU and sequential circuits in Verilog synthesized and implemented them on Xilinx Zedboard using Vivado.

UVM verification of the APB protocol

• Verified an APB master DUT using two agents, one acting as an APB slave, receiving commands, and the other as an AXI slave, giving commands to our APB master.

Designed a five-stage pipelined RISC processor

• A processor consisting of 21-Instruction set encoded and fed to the RISC Processor in the form of a 32-bit command.

Design & Verification of SPI Protocol

• Designed an SPI Master & 2 SPI Slaves and verified them.

Implementation of 16-bit ALU on FPGA Board

• Designed a 16-bit ALU using verilog, then synthesized, implemented and uploaded it on Xillinx Zedboard FPGA using Xillinx Vivado.

Designed a 14T Full Adder using dynamic CMOS logic on Cadence Virtuoso

• This was an implementation of a research paper: "A high speed 14 transistor full adder cell using novel 4 transistor XOR/XNOR gates based on dynamic CMOS logic" built using minimum possible transistors but maximum performance.

Implemented a 1101 sequence detector from its RTL design to STA till Tapeout

• Followed the RTL to GDS2 flow for the FSM. Starting with its RTL design through verilog to verification(Xcelium), then synthesis of the code(Genus)

Smart Parking Maintenance & Assistance System

• Developed a robust IoT & ML-based Smart Parking maintenance system for housing societies and parking lots. Incorporated on-chip ML on Raspberri Pi 4 for surveillance and gatekeeping and RFID along with Realtime Database to ensure vehicles are parked at their respective spaces only.

Research paper Implementation project: Fine Air

• Developed an IoT and ML-based system using an MQ2 sensor to monitor vehicle emissions. Real-time gas data is stored in Google’s Realtime Database and visualized on a website. A regression model predicts emissions for the next 3 days, triggering user alerts if limits are exceeded. Both users and authorities can access this data via the web portal.

• Won 3 Hardware Hackathons
• Got seed-funding by my college for an ECE project
• Tech ECE Head of IEEE SB JIIT