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Basics

Name Julian Gao
Label Robotics & Machine Learning Engineer, Data Curator, Pseudo-Athlete
Summary Engineer that works in field of autonomous driving, robotics, and loves explosive sports

Education

  • 2016.09 - 2018.06

    Palo Alto, CA

    Master of Science
    Stanford University
    Computer Science, 3.9/4
    • Specialization in Articifial Intelligence
  • 2012.08 - 2016.05

    Houston, TX

    Bachelor of Science
    Rice University
    Electrical Engineering, 3.9/4
    • Cum Laude
    • Distinction in Research and Creative Work

Work

  • 2023.07 - Present

    Santa Clara, CA

    Staff Machine Learning Engineer, Data Curation
    XMotors.ai
    Decision Making, Trajectory Planning, Foundation Model, Data Curation
    • Curated large-scale training datasets for foundation models, introducing subclip-level indexing, blacklist filtering, and data distribution adjustment; established a feedback loop between evaluation and sampling that improved model convergence across RL and supervised training
    • Designed and implemented scalable data processing & visualization tools for distributed data quality inspection, annotation readiness, and rapid dataset production; accelerated model iteration cycles and reduced evaluation latency across multiple teams
    • Built a plugin-based data processing framework with Ray, enabling reward modeling, trajectory metrics, and automated data quality checks; framework now widely adopted for post-training validation, quality gating, and rollout inspection across the foundation pipeline
    • Developed a bicycle-model-based trajectory smoother to convert ego pose sequences into continuous control variables (acceleration, curvature), improving RL policy alignment and stability during deployment
    • Enhanced lane-centering and speed control by deploying CiLQR-based trajectory generation for overseas OTA releases; restructured TJA (Traffic Jam Assist) to improve low-speed following and intersection handling, significantly reducing user complaints in Europe
    • Implemented core planning and control modules including traffic light handling logic and intersection strategies, reducing red-light violation counts from 0.6 to below 0.2 per 100 km
  • 2018.08 - 2023.07

    Redwood City, CA

    Senior Robotics Engineer, Product & Core Dev
    Dexterity Inc.
    Robot Control, Motion Planning
    • Designed and optimized motion planning and control frameworks in C++ for high-performance robotic systems
    • Implemented end-to-end trajectory tracking in C++, from velocity profiling to driver control, achieving fast, smooth, and precise robot movements
    • Developed robust collision detection and avoidance algorithms in C++ to ensure safe robotic navigation
    • Built custom simulation toolchains with integrated physics engines to replace ROS-based environments for robotic testing and development
    • Designed and deployed a Python-based line-kitting application for a major client, defining workflow logic and integrating it into operational environments
    • Integrated perception models, control logic, and sensor modules to deliver full-stack robotic applications

Consulting experience

  • 2023.01 - Present

    Santa Clara, CA

    Robotics Consultant
    AlphaSense
    Expert Insights Engagement
    • Provide consultation in industrial robotics and the growing adoption of AI-powered autonomous machinery

Apprenticeship

  • 2016.12 - 2018.06

    Palo Alto, CA

    Research Assistant
    Stanford Vision Lab
    Reinforcement Learning, Imitation Learning, Robotics, Sim2Real
    • Built robotics perception and learning infrastructure foundational to the Stanford Arm Farm project, enabling large-scale manipulation research
    • Deployed a virtual reality interface to scale task demonstration data collection, enhancing training data diversity and volume for imitation learning
    • Developed a MuJoCo-based virtual robot control environment with multi-modal interfaces (HTC Vive, keyboard, mouse) for scalable, crowd-sourced task demonstration collection
    • Designed a robot simulation environment in BulletPhysics to support efficient policy training and prototyping for manipulation tasks
    • Researched sim-to-real transfer in robotic manipulation using policy distillation and sample-efficient reinforcement learning to improve real-world deployment
  • 2015.05 - 2016.07

    Houston, TX

    Research Assistant
    Rice Efficient Computing Group
    GoogleNet, CNN, Caffe
    • Developed a simulation framework for energy-efficient image classification using the Caffe deep learning library
    • Augmented GoogLeNet architecture with custom noise and energy cost layers to evaluate noise-energy trade-offs during inference
    • Trained ImageNet models on the modified Caffe framework, optimizing for accuracy under energy and noise constraints
    • Designed on-chip memory layout using Cadence tools to support energy-efficient deep learning workloads
  • 2014.06 - 2014.10

    Houston, TX

    Research Assistant
    Rice Scalable Health Initiative
    Pattern Detection, Motion Recognition, Digital Health
    • Developed a wearable stride and motion detection system capable of real-time activity recognition and feedback generation
    • Integrated accelerometers, pressure sensors, and storage modules on the MSP430F6726 microcontroller for wearable data acquisition
    • Implemented real-time Bluetooth data streaming and digital signal processing in MATLAB, including sensor feature extraction and motion pattern recognition
    • Designed, validated, and iteratively refined motion recognition algorithms based on real-world sensor data

Projects

  • 2016.11 - 2016.12
    New York City Taxi Pick-up Strategy Generation
    Data Mining, Reinforcment Learning, pySpark
    • Employed Q-learning and Value Iteration to generate optimal passenger pick-up policy, based on 1.1 billion NYC taxi records
  • 2014.03 - 2014.05
    Photosensitive Motor Car
    Pulse-Width Modulation, Obstacle Avoidance, PCB
    • A small mobile vehicle that integrates ultrasonic sensors, motors, NeoPixel, and micro-speaker on SN754410; designed and installed from PCB, with amplifiers, voltage regulators, and PWM for motor control
  • 2013.12 - 2013.12
    Heart Rate Monitor
    FFT, Transmitter-Receiver
    • A simple heart rate monitor based on optocoupler

Publications

Patents

  • TBD
    Emulated Robot Peripherals
    No. 63/435,176
  • TBD
    Multiple Robot Simultaneous and Synchronous Pick and Place
    No. 18/393,504
  • TBD
    Robot Carriage Tray Table
    No. 17/960,544
  • TBD
    Robotic Handling of Soft Products in Non-Rigid Packaging
    No. 16/797,35
  • 2020.02
    Robotic Multi-Item Type Palletizing & Depalletizing
    US_10,549,928_V1

Awards

  • 2023
    Team of Excellence
    XMotors.ai
    Annual award for the outstanding XNGP team
  • 2016
    IEEE Eta Kappa Nu Rice Chapter
    IEEE-HKN
    The honor society of IEEE dedicated to recognizing individual excellence
  • 2014-2015
    Louis J. Walsh Scholarship in Engineering
    Rice University
    Scholarship for deserving students at Rice University
  • 2012-2015
    President's Honor Roll
    Rice University
    Recognition of undergraduate outstanding academic achievement
  • 2016-04-16
    ELEC Fitness Model Award
    Rice University Electrical Engineering Department
  • 2016
    Distinction in Research and Creative Work
    Rice University
    Awarded to the top ten percentile of graduating seniors
  • 2016
    Bill Wilson Best Senior Design Award
    Rice University
    Rice University Affiliates Day student award

Certificates

Chinese Calligraphy & Painting Test (CCPT) Level A
National Education Examinations Authority (NEEA) 2010

Skills

Programming Languages
C++
Python
C
Java
SQL
MATLAB

Languages

Chinese
Native Speaker
English
Business Proficiency
German
Fließend

Interests

Olympic Lifting
81 kg Snatch
106kg Clean & Jerk
69kg Bodyweight
Sprint
50M
100M
200M
Billiards
Eight-Ball
Nine-Ball
Snooker
GeoGuessr
Master Division