Akarsh Srivastava

Akarsh Srivastava

Thermal Vehicle Controls Engineer at Tesla

akarsh@example.com • +1-XXX-XXX-XXXX

Hi! I'm a Thermal Vehicle Controls Engineer at Tesla working on interesting thermal+controls+Data Science topics across various Tesla Fleets. I specialize in thermal systems, battery technology, and machine learning applications in automotive engineering.

Education

University of California, San Diego

M.S. in Mechanical Engineering (Fast-Track)

3.777/4.0 GPA

September 2023 – June 2025

BITS Pilani

B.E. in Mechanical Engineering (Early Graduation)

8.49/10 CGPA

August 2019 – December 2022

Experience

Tesla

Thermal Vehicle Controls Engineer

January 2025 – Present

Working on interesting thermal+controls+Data Science topics on various Tesla Fleets

  • Developed camera facing windshield glass thermal model to address fogging
  • Analyzed overnight test data to calibrate RC circuit parameters
  • Ran biased optimization loop on 100+ hours data with 1°C accuracy
  • Querying thermal vehicle data across fleets for analysis

Lennox International

Thermal System Modeling and Simulation Intern

September 2024 – December 2024

Advanced thermal system modeling and automation

  • Automated test data acquisition for HVAC simulation in under 4 seconds
  • Exploring Physics Informed Neural Networks (PINNs) for HVAC simulation
  • Created utility pricing data extraction and analysis scripts

Cuberg

Battery Cell Quality and Reliability Engineering Intern

June 2024 – August 2024

Computer vision and automation for battery analysis

  • Developed computer vision algorithms to compress (350x), denoise, and visualize CT scans
  • Built tool integrating visualization with Looker dataframe for cell tracking
  • Automated CT scan analysis for fault detection using denoising methods

Siemens Energy

Battery Cell Engineering Intern

February 2023 – July 2023

Electrochemical modeling and optimization

  • Developed electrochemical model for lithium-ion battery degradation
  • Utilized Nelder-Mead optimization for cell model fitting
  • Achieved 98% and 97% R-squared for capacity and internal resistance
  • Provided end-to-end synthetic data generator with ML extensions

National University of Singapore

Undergraduate Thesis

May 2022 – January 2023

Deep learning and dynamical systems research

  • Implemented deep learning algorithms with filters and Empirical Mode Decomposition
  • Extended work to real-world stock market, earthquake and COVID-19 datasets

JSW Energy Ltd

Summer Intern

May 2021 – July 2021

Machine learning for anomaly detection

  • Employed supervised ML algorithms for predicting slot sensor temperatures
  • Gradient-boosted tree regression achieved 98% R-squared value

Research

Thermal Analysis of Cooling Fins

Heat Transfer Coursework Project

Led a comprehensive transient analysis of electric motor fins, providing analytical solutions, validated with literature. Explored the impact of geometry, material, and dimensions on efficiency, heat flux, and time to steady state.

Solar Research: Predicting Longwave Radiation

Coimbra Research Group

Advanced research in radiative transfer and solar energy applications using shortwave radiation parameters as part of graduate studies at UC San Diego.