Hardware Engineer with experience in Analog VLSI Design (SF Bay Area)

Programming Foundations with HTML, CSS and JavaScript Java Programming: Solving Problems with Software Object-Oriented C++: Inheritance and Encapsulation Advanced Digital Design ASIC Implementation of Motion Estimator in 32/28 nm CMOS After verification of the RTL code with a testbench using Verilog, the design was taken to the ASIC flow starting with front-end synthesis and timing check (using Design Compiler), followed by back-end physical design (using IC Compiler II) involving placement, clock-tree synthesis, and routing.
The parasitics were extracted from layout for final timing check using PrimeTime and a post-synthesis PrimeTime check was also done for accuracy checks Did front-end synthesis along with timing check using PrimeTime.
Also did the physical design Nanoscale Circuits and Systems Design and Characterization of Non-Volatile Latch using Resistive Memory Technologies and 28nm CMOS Simulated netlist of single-bit non-volatile D-latch, using RRAM technology in 28nm CMOS, using HSpice.
Under a reliability constraint to achieve a success rate greater than 99.
9%, the design optimization goal was to minimize layout area and standby leakage power Embedded Systems A Modular and Custom Robot Arm with Real-Time Feature and Gesture Recognition using Machine Learning Collaborated with a team to 3D print a custom robot arm that was to be programmed by the TM4C123GH6PM microcontroller.
EMG sensors were used to record the muscle movements of an actual arm into 3 distinct features: Sum of all Values, Standard Deviation, and Arc Length.
This data was sent to MATLAB.
MATLAB trained the robotic arm using Linear Discriminant Analysis (LDA) to perform a few hand gestures: open palm, closed fist, hang loose, and a relaxed position.
On Tiva board, following modules were implemented: UART, PWM, ADC, and µDMA.
Applied Research Project Intelligent Room Lighting Control System Using IoT and Home Automation Intelligent control of room brightness by controlling external light source (sunlight) by creating an automated blinds system and controlling internal room lighting (LEDs).
Blinds Control using a Stepper motor controlled by NodeMCU and created LED brightness control using digital potentiometer controlled by NodeMCU Messaging protocol used: MQTT over Wi-Fi between Home Assistant and NodeMCU Interfaces used: I2C for light sensor to NodeMCU, SPI for NodeMCU to potentiometer.
Implemented state-machine based automation.