# Yi Lan

> Sr. Software Engineer, Autonomy - Localization & Mapping @ Cyngn

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

My passion is about solving problems of 3D Computer Vision and Image Understanding, building impressive applications sensing the real world. I have good experience in augmented reality, Visual Odometry, and visual SLAM techniques. I'm going to graduate in April 2019 and currently seeking for the entry-level full-time job.

## Work Experience
### Senior Software Engineer, Autonomy - Localization & Mapping @ Cyngn
Jan 2022 – Present | Menlo Park, California, United States

### R&D Engineer @ Trifo
Jan 2019 – Jan 2022
Perception Team
- SLAM for home robot vacuum
- Indoor Semantic Mapping
- Depth data based indoor obstacle detection.

### R&D Engineer Intern, Augmented Reality @ Baidu Inc.
Jan 2018 – Jan 2018
AR Lab of Baidu AI Group.

- Researched and developed 3D model localization and tracking prototype with the moving edge method. Applied a particle filter model during tracking and a simulated annealing step during initialization. Integrated with other methods as 3D model tracking and pose estimation module for our AR SDK.

- Using ARKit API, developed an iOS client tool collecting and sending ARKit tracking data with Protobuf for our Visual Positioning System experiments.

### Computer Vision Engineer, Augmented Reality @ OppenFuture Technologies
Jan 2016 – Jan 2017 | Beijing City, China
- Developed mobile Mixed Reality engine and visual odometry system. Responded for 2D target detecting and tracking module. With given image template, selected feature based 2d-2d correspondence during initialization and solved the optimized camera pose. During the tracking step, applied the Optical Flow method to track key points and updated poses with the nonlinear optimizer. The re-projection error is used as the metrics threshold for entering re-initialization.

- Launched iOS AR game MuzzBloc. With CNN model, detected and classified objects in the already segmented image bounding boxes. Used features correspondence with image template for target localization and tracking.

- Demo: https://www.muzzbloc.com/

### Intern Research Assistant @ Institute of Software, Chinese Academy of Sciences
Jan 2015 – Jan 2016 | Beijing, China
- Researched adaptive sampling and reconstruction problems in Monte Carlo rendering in Computer Graphics.

- Presented a novel method sampling ray adaptively utilizing spatial and material features of the scene. Developed these work into my bachelor thesis.


## Education
### Master of Science - MS in Computer Science
UC Irvine

### Bachelor of Engineering - BE in Computer Science
Beijing University of Posts and Telecommunications

### The Attached Middle School of Jiangxi Normal University


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

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Source: https://flows.cv/yilan
JSON Resume: https://flows.cv/yilan/resume.json
Last updated: 2026-03-29