PREETAM BAMANALLI

Phone:619-***-**** Email: adkgot@r.postjobfree.com LinkedIn: http://www.linkedin.com/in/preetambamanalli SUMMARY

2+ years of experience in the field of Information technology as Programmer Analyst. Seeking full-time entry-level opportunities in the field of Embedded firmware/application/device driver development to enhance and challenge my technical skills. EDUCATION

San Diego State University, CA Aug 2019-May 2021

Master of Science in Electrical and Computer Engineering Coursework: Embedded Operating Systems, Computer Data Networks, Stochastic Signals and Systems, Cyber Physical Systems, Machine Learning, Wireless Sensor Networks, Multimedia Wireless Networks, Database and Web Programming. School of Engineering and Technology- Jain University, Bangalore-India Aug 2011-Jun 2015 Bachelor of Engineering in Electronics and Communication Engineering Coursework: Data Structures using C, Microcontrollers and Microprocessors, Embedded System Design, ARM Processor, RF communications. TECHNICAL SKILLS

Programming Languages: C, Embedded C, Assembly, Bare-Metal, Python, MATLAB, C#, SQL, Verilog. Communication Protocols: UART, SPI, I2C, UDP, TCP/IP, CAN, 802.11 IEEE, DMA, TWI. Software and Tools: STM32 CUBE IDE, Eclipse, Microsoft Visual Studio. Hardware Platforms: Raspberry Pi, STM32 Discovery, Arduino, 8051. PROFESSIONAL EXPERIENCE

Teaching Associate at San Diego State University Aug 2020-Present Course: Computational and Statistical Methods for Electrical Engineers - EE300

• Conducted discussion sessions for 120 undergrads to assist them with conceptual doubts and taught them how to solve different problems related to probability and statistics.

• Quizzed and graded students regularly on the topics related to probability. Programmer Analyst Jan 2016-Oct 2018

Cognizant Technology Solutions, Bengaluru, India

• Developed automated test script using J unit for the Healthcare management application which increased test case execution by 70%.

• Analyzed functional and nonfunctional requirements of clients and developed test strategies, test plan and test cases for the requirements.

• Reported multiple critical defects and avoided the cost of defect fixing and defect leakage in the production environment by 10%.

• Preformed database testing to ensure correct data flow across multiple software modules.

• Assisted developers in debugging and fixing the defect to ensure timely delivery of software to the client. ACADEMIC PROJECTS

Condition Monitoring and Management System for Agricultural Crops (Python)

• Designed an FSM which automatically controls the temperature inside the green house plantation base on temperature sensor readings.

• Implemented the FSM on the Raspberry Pi which automatically turned on the heater or the fan based on temperature sensor readings.

• Developed a solution for sensor failures by adding redundant sensors, where sensors were interfaced using TWI protocol.

• Analyzed the reachability of the FSM using Linear Temporal Logic. Multipurpose LIDAR System for Vehicles (C)

• Developed an interrupt-based system to detect potholes, speed brakers and object detection for vehicles using the LIDAR sensor.

• Implemented the system on Arduino Uno by interfacing multiple LIDAR sensors by using I2C protocol.

• Implemented system which reduced the speed of the motor using PWM and warned driver upon detection of objects and potholes. Real-Time Traffic Management System using RFID Raspberry Pi (Python)

• Implemented traffic management system to control congestion and speed and calculate toll using RFID reader, interfaced using SPI.

• Implemented forks to create new process and different scheduling algorithm to manage processes such as toll calculation speed control.

• Compared the performance measured in terms of average turn around time and average response time of each tasks. Data Exchange Using UNIX Socket Programming (C)

• Implemented client and server-side code using UDP sockets to create an architecture of multiple clients and a server.

• Successfully executed the data transfer between the client and the server over the university servers which were connected by LAN. Ten Year Coronary Heart Disease Prediction (Python)

• Performed extensive data analysis on the factors that are associated to heart disease by data visualizing.

• Implemented Decision tree classifier which predicted the heart disease a person can develop in 10 years with an accuracy of 84.97% Integration of CBSR Architecture with Embedded Block RAM on Lattice iCE40 FPGA Platform for Sensing Falls Present

• Detection and prediction of a fall using data from accelerometer and gyroscope sensors feeding them to CNN for fall classification.

• Assembling the data from accelerometer and gyroscope sensors continuously in 2D vectors that are stored in Embedded Block RAM.

• Feeding the 2D vector data into the Convolutional Neural Network to classify the fall and predict the likelihood of the Fall.