Wenda Wang
Data AnalystAI + Robotics, Co-founder@NobleMachines
Noble Machines
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI + Robotics, Co-founder@NobleMachines
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Experienced in the field of robotics, deep learning, and autonomous system.
Carnegie Mellon University
Master's degree, Robotics
January 1, 2014 – January 1, 2015
Technische Hochschule Lübeck
Bachelor of Science (B.S.), Information Technology
January 1, 2013 – January 1, 2014
East China University of Science and Technology
Bachelor of Science (B.S.), Electrical Engineering and Automation
January 1, 2010 – January 1, 2013
South Park Commons
Founder Fellow
May 1, 2024 – Present
Noble Machines
Co-Founder
April 1, 2024 – Present
Apple
Staff Machine Learning Engineer
September 1, 2022 – May 1, 2024
Apple
Senior Machine Learning Engineer
October 1, 2017 – September 1, 2022
Apple
Machine Learning Engineer
February 1, 2016 – October 1, 2017
A9.com
Computer Vision Intern
May 1, 2015 – August 1, 2015
Pepperl+Fuchs GB Ltd
Software Engineer Intern
March 1, 2014 – June 1, 2014
Mannheim Area, Germany
Shanghai Institute of Process Automation Instrumentation
Internship
November 1, 2012 – January 1, 2013
Shanghai City, China
3M
Internship
July 1, 2012 – September 1, 2012
Shanghai City, China
fMRI Image Classification, Prediction, and Learning
August 1, 2015 – December 1, 2015
3-Part Machine Learning Final Project. Part 1: Given 501 training examples with 5903 voxels per example, classify 1001 test examples with either of 3 possible brain signal events -- "no event", "successful stop to early stop signal", and "correct button press". * used one-vs-all SVM and 10 fold cross validation * used Matlab's fitcsvm and predict. * achieved 64.8% accuracy on training and 60.1% accuracy on testing. Part 2: Given 3172 of 5903 voxels, predict the missing 2731 voxels of each fMRI image. * Attempted with unsupervised methods using PCA, ICA, k-means, and non-parametric method to build a dictionary. * Best RMSE achieved with Support Vector Regression. Final training RMSE is 0.4634 and testing RMSE is 0.4472. Part 3: Implemented autoencoder to improve upon parts 1 and 2.
Virtual Reality Application for Android
July 1, 2015 – Present
The application is able to blending 2D image content onto planar surface in real time through camera on the mobile phone. The core algorithm is implemented based on OpenCV
Autonomous Quad Rotors
March 1, 2015 – Present
Develop the whole software pipeline for an autonomous quad rotors. The software includes back stepping controller, energy optimized trajectory generation, stereo camera based visual odometry, and D* based planning algorithm to avoid obstacles.
Autonomous Kitchen Robot
September 1, 2014 – April 1, 2015
Develop a smart kitchen appliance, which is capable of peel and slice vegetable autonomously Responsible for the overall software architecture, motor control algorithm, and all the electrical components
Analysis of IP Metrics in German Education and Research Network
September 1, 2013 – Present
Implement the system to store and fetch network monitoring data from different service providers Design algorithm to automatically classify the links by its service quality
Developing Gesture-based Application used in Teaching Activity
November 1, 2012 – Present
The application is developed based on the Microsoft Kinect sensor, and provide functions like zooming, scrolling, switching between applications, simulation of the mouse Design and implement unified gesture managing framework, and define different gestures
Developing a new kind of Intelligent Blind Stick
May 1, 2012 – Present
The blind stick is able to detect obstacle and will turn the wheel mounted at the bottom of the stick to guide the user through it Modeling of the system,and design of PID Controller Design and implement obstacle avoiding algorithm, and sensor detection algorithm
Algorithms: Design and Analysis, Part 1
Coursera
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards robotics, machine learning, and computer vision, with significant experience in R&D and startup environments. While there are projects involving data analysis (fMRI, IP Metrics), the overall profile is not a direct fit for a traditional Data Analyst role, which typically emphasizes statistical analysis, data warehousing, business intelligence, and specific data manipulation tools. The candidate's experience suggests a preference for cutting-edge research and development, potentially indicating a mismatch with roles focused on routine data reporting or business-centric analysis. The diversity of projects shows adaptability, but the core focus is not aligned with the target role.
Soft Skills & Operational Fit
The candidate's project history demonstrates strong problem-solving abilities, initiative, and a hands-on approach to complex technical challenges. The co-founder and founder fellow roles suggest leadership and entrepreneurial drive. However, without specific psychometric test results or interview data, a detailed assessment of stress handling, team collaboration, and work attitude is not possible.