Navid Salehnamadi
Besides that, I enjoy reading comics/manga, solving puzzles, playing music
About me
I'm Navid, a Machine Learning Engineer at Tesla AI, where I design and develop scalable frameworks for processing and curating massive video datasets to train generative models for self-driving technology. My work includes building data pipelines and orchestration frameworks to automate the ingestion, curation, training, and deployment of machine learning models, which are now deployed in Tesla vehicles worldwide.
I completed my Ph.D. in Software Engineering at the University of California, Irvine, under the guidance of Prof. Sam Malek. My research focused on leveraging program analysis and machine learning techniques to automate software testing and detect accessibility issues in mobile apps.
I'm passionate about automating manual processes and am skilled in Python, Java, and various machine learning and data engineering frameworks.
Work Experience
Tesla AI
Senior Machine Learning Engineer
February 2023 - now
- Designed and developed a scalable dataset generation and validation framework, processing tens of millions of video clips on a daily basis to produce high-quality datasets for generative models in self-driving software.
- Led the creation of data pipelines and datasets for the end-to-end self-driving model deployed in all Tesla vehicles (version 12+).
University of California, Irvine
Graduate Research Assistant
October 2017 - September 2022
- Designed and created novel testing techniques to detect accessibility and delivery issues in android apps
- Devised a scalable and accurate static analysis technique to detect event races
- Investigated light-weight model checkers to formally analyze uncertainty in models
Microsoft Research
Research Intern
June 2021 - September 2021
- Designed a multi-level job caching mechanism, improved the response time +30 times faster than the baseline model
- Implemented a scalable caching service using ASP.NET, CosmosDB, and Azure Storage
Avaye Hamrah Hooshmand Hezardastan
Software Engineer
October 2015 - August 2017
- Coordinated a number of teams (with 6 to 11 members) in CafeBazaar, a local Android app market, to create tools for developers
- Established a developers panel based on microservice architecture (using Django, Docker, and Kubernetes)
- Redesigned and developed a system to automate the process of filtering out malwares and low-quality apps
- Inspected technical teams' performance issues at a company-wide level
Publications
Assistive-Technology Aided Manual Accessibility Testing in Mobile Apps, Powered by Record-and-Replay
Published in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
Authors: Navid Salehnamadi, Ziyao He, and Sam Malek
Published in ACM Transactions on Software Engineering and Methodology (TOSEM)
Authors: Jun-Wei Lin, Navid Salehnamadi, and Sam Malek
Published in ASE 2022, 37th International Conference on Automated Software Engineering, October 2022
Authors: Navid Salehnamadi*, Forough Mehralian*, and Sam Malek
Published in ASE 2022, 37th International Conference on Automated Software Engineering, October 2022
Authors: Forough Mehralian*, Navid Salehnamadi*, Syed Fatiul Huq, and Sam Malek
Published in ACM Transactions on Software Engineering and Methodology (TOSEM)
Authors: Negar Ghorbani, Reyhaneh Jabbarvand, Navid Salehnamadi, Joshua Garcia, and Sam Malek
Published in ESEC/FSE 2021, he ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, August 2021
Authors: Forough Mehralian, Navid Salehnamadi, and Sam Malek
Published in CHI 2021, Virtual Conference on Human Factors in Computing Systems, May 2021, 26% acceptance rate
Authors: Navid Salehnamadi, Abdulaziz Alshayban, Jun-Wei Lin, Iftekhar Ahmed, Stacy Branham, and Sam Malek
Published in ASE 2020, 35th International Conference on Automated Software Engineering, September 2020, 23% acceptance rate
Authors: Navid Salehnamadi, Abdulaziz Alshayban, Iftekhar Ahmed, and Sam Malek
Published in ASE 2020, 35th International Conference on Automated Software Engineering, September 2020, 23% acceptance rate
Authors: Jun-Wei Lin, Navid Salehnamadi, and Sam Malek
Published in MobiSys 2020, 18th International Conference on Mobile Systems, Aplications, and Services, June 2020
Authors: Navid Salehnamadi, Abdulaziz Alshayban, Iftekhar Ahmed, and Sam Malek
Projects
A step-by-step tutorial for Soot, a Java and Android static analysis framework
A web app designed to translate contest questions of the International Olympiad in Informatics (IOI 2017)
A simple tool emulating the black-box testing, used in the Introduction to Software Engineering course in UCI
An online contest platform applying active learning techniques for mathematic courses
A Ruby on Rails web app for students in University of Tehran to schedule their courses in the following semester