This document contains summaries of several projects related to data analysis, machine learning, control systems, mechanical design, and solving differential equations: 1) A price prediction model for Austin real estate that achieves over 80% accuracy and an interactive visualization of the results. 2) Implementing and visualizing stochastic gradient descent algorithms on 70,000 images of handwritten digits. 3) Comparing controllers for synchronizing Chua's oscillator system and synchronizing the nonlinear system with sliding mode and backstepping controllers. 4) System identification and forecasting of a series-elastic actuator using a recurrent neural network model.

1. Distance to The Closest Hospital Near Austin (m) Price Plot Prediction Plot
 Scraped Austin Real Estate data from zillow.com and OpenStreetMap, building a price prediction model in Python, the
model can achieve over 80% accuracy within error range of 0.15.
 Created an interactive visualization for the result with Bokeh package.
Austin Real Estate
Data Scrappy, Analysis and Interactive Visualization

2. Digit Example Squared Loss Gradient Method Multinomial Logistic Gradient Method
 Implemented and visualized the stochastic gradient descent with K-Means and Multinomial logistic classifier on 70,000
handwritten digits images.
 Built parallel code and executed it on multiple engines to solve the large scale problems.
Handwritten Digits Classification

3. Chua's Circuit Schematic Synchronization Two perfect model Phase Trajectory of the Two Sychronized Oscillator
 Compared performance of Linear Feedback, Sliding Mode, Back Stepping and different controllers on Chuas's Oscillator.
 Synchronized the the nonlinear system with one input using Sliding Mode and Lypunov Function based Back Stepping
controller with MATLAB.
Cubic Nonlinearity Chua's Oscillator
Control and Synchronization

4. SEA(Series-Elastic Actuator)
Designed and built by Nicholas Paine in the HCRL
Recurrent Network testing result(Mixed Sinusoid Input)
 Designed a recurrent network to model the actuator
system with Neuro-Bondgraph.
 Trained and tested the model with MATLAB Neural
Network Toolbox to identify the actual constitutive
relations of the system, spring force and damping force.
System Identification and Forecasting
of Series-Elastic Actuator
Recurrent Network (Neuro-Bondgraph) Representation

5. CAD Layout Final Product
 Completed the CAD design of a
moving Castle in the Games of
Thrones opening theme(The Eyrie).
Finished building it with laser cutter,
3D printer, lathe, drill and other
machine tools.
Games of Thrones Castle Design

6. DaNI(NI LabVIEW Robotics Starter Kit) Schematic of closed loop control with Kalman Filter Actual trajectory of DaNI
 Implemented Real-Time closed loop path control on NI Single-Board RIO Robot with LabView
Full-state Closed Loop Control of DaNI

7. Schematic of Fully Differential Op-Amp Integrator)
Solution for Second Order ODE
HxC Analog Integrator Voltage
 Designed and Simulated the algorithm to solve ODEs with
UT hybrid computer (mixed signal computer) prototype
board in MATLAB environment.
HxC Scaling Algorithm Applied to
First and Second Order Ordinary Differential Equations