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Experience
I am currently pursuing Master of Science degree in Electrical Engineering and working as a Graduate Assistant at the University of South Florida. Through my coursework and projects, I have developed my technical knowledge in the control systems especially in signal processing and VHDL/Verilog systems with FPGA. During, the second semester of my Graduate Studies, me and my teammate worked on an audio signal processing using FPGA to eliminate the unwanted noise using peak picking algorithm and spectral subtraction. I strongly believe my experience with FPGA is plus in my application to this position. Other project on which I have worked is based on Advance Signal Processing. In that project, The Fetal
Phonocardiogram processing framework is used for processing real-time FPCG signal to separate the Maternal Heart Sounds (MHS) and Fetal Heart Sounds (FHS) from noisy FPCG signal using peak picking algorithm and spectral subtraction. I have also worked as Engineering Intern for 3 months.
With my current job as Graduate Assistant, I have escalated my technical skills as well as gained professional experience by working in an industrial work environment. I have worked JIRA and AGILE/ Waterfall methodologies which has helped me understand the importance of all the stepwise process of designing, deliverables, feedback, and improvisation. Also, working on projects of SCADA modernization on Niagara and Alerton platforms has elevated my knowledge of relation and synchronization between controllers, sensors, and HVAC units with the data feeding BACnet servers. The technical and management implementations together have provided me with a perfect exposure in the field of Electrical Engineering.
Moreover, my experience as an Engineering Intern for more than three months, provided me with the professional experience required for this kind of role. I have worked both on problem solving and implementing solution using different tools and developed the ability to work through tightest of deadlines. Adding to this the academic projects on which I have worked during my undergraduate studies as well as graduate studies has developed my skills in object-oriented programming and different programming platforms.
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Projects
1) DFT implementation for Audio signal on FPGA
Abstract— This project contains the implementation of an audio spectrum analyzer on a FPGA system. Using the FFT algorithm, the spectrum analyzer analyzes and measures the frequency components of a discrete time signal. FPGAs often supplement to their configurable logic array with specialized DSP hardware and may be more capable than general-purpose processors for such a task.
A system is designed using the Fast Fourier Transform block connected to the AUDIO CODEC with FIR filter. This implementation involves separate modules for obtaining and digitally sampling a continuous audio signal, applying FFT to obtain the frequency components of the digital signal, taking measurements pertaining to frequency, and the output data can be obtained by peaks in the output from speakers. Typical spectrum analyzer functionality includes a configurable frequency range and resolution bandwidth, peak detection, total spectrum intensity measurements, and noise measurements. The audio source file will be transmitted from the mobile phone to the line-in port Xilinx ATLYS spartan-6 FPGA board. The audio source will be recorded and processed through the FFT coded module and filter resulting in the processed audio signal containing no unwanted frequency components.
2) Self-Balanced Car using Wi-Fi Control
The car is designed to balance on two wheels and perform moving operations like forward, backward, right, left and stop. The car was mounted with 3 IC modules and was controlled with the Arduino Wi-Fi module. The chain of command and protocols works in following manner. Initially, we designed the web UI with the help of HTML back-end, and it communicates the command to ESP8266 Module via Wi-Fi. Then the ESP8266 module is connected to PIC18F45K50 microcontroller through a custom-built communication protocol. The PIC controller communicates with the Arduino MEGA via receiver transmitter protocol USART. Further, Arduino MEGA interfaces the motor via Motor driver IC and at the same time it interacts with the motion tracking or gyroscope device MPU6050 via I2C protocol which detects the axis parameters for balancing the car.