# Yusef Shafi

> Staff Software Engineer/Tech Lead Manager at Waymo

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/yusef

I'm passionate about designing, building, and shipping scalable systems that leverage data and rigorous mathematical models to drive society-positive change. I am currently at Waymo working on simulation and evaluation. Previously, I built computer vision algorithms and software for Nest Cam and the Nest Learning Thermostat, and worked at Google Research on simulation and machine learning for global climate change impact mitigation and the Google Apple COVID-19 Exposure Notifications product.

Principal technologies/skills:
-Algorithm design (machine learning, computer vision, estimation and control, dynamical systems, simulation)
-Software engineering (C++, Python)
-Distributed data processing

## Work Experience
### Staff Software Engineer @ Waymo
Jan 2021 – Present

### Staff Software Engineer @ Google
Jan 2014 – Jan 2021
2019-2021: Large scale simulation and HPC on TPU, Google Research
2015-2019: Computer vision algorithms and infrastructure, Nest Cam
2014-2015: Machine learning and control, Nest Thermostat

### Senior Software Engineer @ Nest
Jan 2014 – Jan 2018
2015-2018: Nest Cam/Dropcam computer vision. Algorithms and infrastructure, embedded and cloud.
2014-2015: Algorithms engineer/data scientist, Thermostat/energy and presence/occupancy.

### Graduate Student Researcher @ UC Berkeley
Jan 2009 – Jan 2014 | Department of EECS
My graduate work centers around design and analysis of algorithms that facilitate our understanding of and ability to control complex networks. I make use of network structure and the local interactions between subsystems in order to guarantee safe and reliable operation of the complete system without centralized coordination. Employing tools from convex optimization, nonlinear dynamical systems theory, machine learning, spectral graph theory, and numerical analysis, my research enables distributed control and optimization of a variety of systems, including energy microgrids, aircraft formations, cellular reaction-diffusion networks, and social networks.

### Graduate Student Instructor @ UC Berkeley
Jan 2012 – Jan 2012
Responsible for weekly discussion sections, office hours, guest lectures, exam grading, and student integrity/dispute resolution.

Courses taught/planned: 
MFE 230, Optimization models in finance, Master of Financial Engineering, Winter 2014.
EE 120, Upper division signals and systems, Fall 2012.

### Research Engineer Intern @ Bosch Energy Storage Solutions
Jan 2013 – Jan 2013 | Palo Alto, CA
Predictive modeling and statistical learning for building energy consumption using neural networks, SVM, and kernel smoothing regression.
Regression and clustering models for predicting electric demand for grid storage and renewables.
Development of conditional density and variance estimators using GARCH, bootstrap, and mixture models. 
Implementation of OOP software and documentation with accompanying Excel analysis platform.

### Software Engineer @ Northrop Grumman Corporation
Jan 2008 – Jan 2009
Large scale software system implementation in C++ and Perl. Source control using git. Requirements definition and analysis.

### Research Assistant @ UCLA
Jan 2006 – Jan 2008
Software development and mathematical optimization for VERITAS (Very Energetic Radiation Imaging Telescope Array System)

Languages: C++, MATLAB. Distributed computing using a Beowulf cluster.

### Researcher @ Los Alamos National Laboratory and UCLA IPAM
Jan 2007 – Jan 2007
Cooperation among autonomous robots and occlusion video tracking

### Programmer/Analyst Intern @ General Atomics
Jan 2005 – Jan 2005


## Education
### PhD in EECS
University of California, Berkeley

### MS in EECS
University of California, Berkeley

### BS in Applied Mathemtics
UCLA


## Contact & Social
- LinkedIn: https://linkedin.com/in/yusefshafi

---
Source: https://flows.cv/yusef
JSON Resume: https://flows.cv/yusef/resume.json
Last updated: 2026-04-12