# Quan Zhou (He/Him) > Latitude.ai Location: Sunnyvale, California, United States Profile: https://flows.cv/quanzhouhehim Quan's current interests are within the areas of machine learning, robot navigation, simultaneous localization and mapping (SLAM), computer vision, optimization, and multi-sensor fusion, with a concentration on enabling robots to perceive the world through fusing multi-modality information from different sensors (visual cameras, IMUs, sonar, wheel encoder, 2D/3D LiDAR, GPS and so forth). Specialties: State estimation with emphasis on localization and mapping Bayesian filtering (Kalman,/Extended Kalman/Unscented Kalman/Particle filters) Nonlinear state estimation on Lie group. Before that, Quan had worked in the wireless communications industry (with emphasis on physical layer signal processing) for more than 10 years. He had extensive experiences in the system architecture definition, algorithm design and implementation for wireless communications. And his solid background in applied mathematics / statistical signal processing / computer programming skills make him a great fit for the various algorithm design and implantation roles in the autonomous driving industry. His past industrial experiences including the following wireless standards and products: 1. IEEE 802.15.1, both classical Bluetooth and Bluetooth low energy (BLE), 2. IEEE802.15.4, Zigbee, 3. Global positioning system (GPS) receiver system design 4. 4G-LTE RF calibration algorithm design and implementation. Specialties: Modern digital signal processing. Digital/wireless communications theory. MIMO-OFDM based modern wireless communication system RF analog impairments modeling for wireless communications systems. Strong programming skills in C/C++, and Matlab Fixed-point wireless communication system modeling using Matlab or C/C++. ## Work Experience ### Software Engineer @ Latitude AI Jan 2023 – Present | Palo Alto, California, United States 1.Robust dead reckoning navigation algorithm. 2 Online vehicle-imu calibration algorithm. 3. Online radar-imu calibration algorithm. ### Software Engineer @ Argo AI Jan 2022 – Jan 2023 | Palo Alto, California, United States Update: We are acquired by Latitude.ai, a ford company. Target based camera radar calibration. Target based multi-lidar calibration. ### Sr. Software Engineer @ WeRide.ai Jan 2017 – Jan 2022 | San Jose, California, United States Deep understanding of the theory and practice of multi-sensor fusion based localization system for L4 autonomous driving system. Key results: 1. Start from scratch to design and implement an extended Kalman filtering based localization algorithm, which successfully fuses multiple sensors, e.g., GPS/IMU/Lidar/Wheel Speed Sensor into one framework. 2. Zero incident in the 10,000 kilometers localization pre-production test in the city of Guangzhou, China. 3. Zero incident in the 5,000 miles localization algorithm stress test in the highway environment around the bay area, California. 4. Employee of the quarter, 2018, for the first time successfully passing through the 1km underwater tunnel in GuangZhou (a totally GPS-denied environment) without any localization issue. ### Sr. Staff Architect Engineer @ Samsung Semiconductor Inc Jan 2014 – Jan 2017 | San Francisco Bay Area Delay calibration algorithm design and implementation for envelope tracking (ET) power amplifier (PA) 1. Key contributor to build the ADS Ptolemy simulator for ET-PA. 2. Key contributor to migrate the algorithms into mass production. Fast IQ imbalance calibration algorithm design and implementation 1. Propose and implement the joint transmitter and receiver IQ imbalance calibration algorithm for LTE FDD system based on the internal transmit loopback architecture. 2. Build the algorithm into the real product. 3. Submitted a patent based on the work. Fast IIP2 factory calibration based on two tone testing 1. Propose and implement a fast search (search IIP2 calibration DAC code) algorithm for IIP2 factory calibration based on the internal loopback architecture. 2. Build the algorithm into the real product. 3. Published a patent by Samsung as a first author. 4. Employee of the month award because of the production support based on this algorithm. IIP2 calibration based on adaptive signal processing algorithm 1. Propose and implement an adaptive IIP2 calibration DAC code searching algorithm based on the real-time LTE signals. IQ branch dependency information has also been considered to accelerate the searching speed. 2. Build the algorithm into the product as a candidate algorithm. 3. Published a patent by Samsung as a first author. ### Principal Engineer, WLAN system design @ Broadcom Jan 2012 – Jan 2014 | Sunnyvale 1. 5G Wireless LAN (IEEE802.11ac) system design and integration. 2. WLAN and Bluetooth coexistence performance tradeoff study and improvements. ### Senior/Staff/Sr. Staff Design Engineer @ Marvell Jan 2007 – Jan 2012 | Santa Clara, CA Working on the following wireless products: 1. Bluetooth (classical bluetooth and bluetooth low energy) 2. Global positioning system (GPS) 3. Zigbee (both sub1G and 2.4G) ## Education ### PhD in Electrical Engineering North Carolina State University ## Contact & Social - LinkedIn: https://linkedin.com/in/quan-zhou-he-him-a944b46 --- Source: https://flows.cv/quanzhouhehim JSON Resume: https://flows.cv/quanzhouhehim/resume.json Last updated: 2026-04-11