Machine Learning Electrical Engineering

DEVANSH ANNAPUREDDY

SUMMARY

A highly motivated and skilled professional pursuing a Master’s in Electrical Engineering with strong analytical and problem solving skills. Proficient in advanced technologies and eager to contribute to real-world projects.

WORK EXPERIENCE

EDUCATION

Master of Science in Electrical Engineering

University of New Haven - West Haven, CT, USA

Relevent coursework includes Embedded Systems, Digital Signal Processing, Discrete and Continuous Systems, Advanced Computed Networks, Electric Drives Jan 2024 - Present

Worked on integrating various electronic components into the overall electric vehicle system, ensuring seamless communication and functionality.. Gathering and analyzing requirements, conduct research on new technologies, testing and debugging software.

conduct tests to ensure that these components meet performance, reliability, and safety standards.

Provide technical support to other teams within Ola Electric. Graduate Engineer Trainee - OLA Electric, Bengaluru, India Dec 2021 - May 2022 SKILLS INFORMATION

Technical Skills: Python Programming, SQL, Data Structures Software: MS PowerPoint, MS Excel, Git, MS Word,

Soft Skills: Communication, Collaboration, Team-oriented, Analytical skills. Languages: English, Telugu

Bachelor of Technology in Electronics and Communication Engineering Vel Tech University - Avadi, Chennai, India

Relevant coursework includes Discrete Time Signal processing, Data Communication Networks, Embedded OS and Device Drivers, Signals and Systems, Linear Integrated Circuits, waveguides and Antennas.

July 2018 - June 2022

West Haven • 240-***-**** • ******@***.********.*** ACADEMIC PROJECTS

CLIMATE CHANGE PREDICTION USING DEEP LEARNING

Here we are focusing in climate prediction at farms by forecasting solar radiation which climate changes are directly dependent on by using meteorological conditions using Machine learning to anticipate the climatic change in advance. Farmers may use the predictions to schedule harvesting according to predictions.

MUSICAL TONES CLASSIFICATION USING MACHINE LEARNING The new method proposed in this project develops a machine learning model in combination with the Mel-frequency-cepstrum coefficient by extracting audio features to identify the musical instrument.

PUBLICATIONS

Published a journal in "International Journal for Research in Applied Science & Engineering Technology" (IJRASET) named "Musical Tones classification using Machine Learning".(Volume 10, Issue XII, December 2022 - ISSN No: 2321-9653). Published a Conference paper named "Climate Change Prediction Using Deep Learning" in

"Innovative Design, Analysis and Development practice in Engineering" (IDAD) conducted by Vel Tech Institution 2022.

Contact this candidate