Tianshu Huang
I'm an ECE student at UT Austin interested in Machine Learning. Specifically, I'm interested developing machine learning methods that decrease the cost to use machine learning such as hardware-aware methods that decrease the training or inference cost.
You can contact me at tianshu.huang@utexas.edu.
Education
| University of Texas at Austin | Aug 2017 - Present |
GPA: 3.95
Math:
Math:
- Convex Optimization
- Probability and Stochastic Processes I (Graduate)
- Theory of Probability (Graduate)
- Geometric Foundations of Data Science (Graduate)
- Real Analysis I, II
- Geometric Foundations of Data Science (Graudate)
- Operating Systems
- Computer Architecture
- Algorithms
- Digital Logic Design
- Introduction to Embedded Systems
- Linear Signals
- Automatic Control
| Texas A&M University | May 2016 - Aug 2017 |
GPA: 4.0
Concurrent enrollment while attending high school
Courses:
Concurrent enrollment while attending high school
Courses:
- Discrete Math
- Linear Algebra
Current Research
My current research with Prof. Atlas Wang on deep learning methodology is in Learning to Optimize. In this field, gradient-optimizers for deep learning models (i.e. Adam, RMSProp) are parameterized most often as recurrent neural networks which are treated as policies to be trained.In my individual work, I designed and implemented a learning to optimize framework in TensorFlow, combining four papers and tens of thousands of lines of code into a single library and API. I then showed that using multiple teachers in imitation learning improves performance in a way that cannot be explained by memorization of the teachers, and am currently working on further research regarding multiple teachers.
Research Experience
| Drilling Automation | Fall 2019 |
UT Austin
Petroleum Engineering
RAPID
Supervised by Dr. Pradeepkumar Ashok.
| Bayesian Clustering | Summer 2019 |
Texas A&M University
Statistics
Supervised by professors Debdeep Pati, Anirban Bhattacharya, and Bani Mallick.
| Geostatistical Analysis | Summer 2019 |
Texas A&M University
Construction Science
Supervised by Prof. David Jeong.
Work Experience
| Teaching Assistant | Spring 2020 - Fall 2020 |
UT Austin
ECE
TA for Probability and Random Processes (EE 351K)
| Test Analysis Systems Consultant | Summer 2018 - Summer 2019 |
SLD Laser
Maintain web app built previously
| Full Stack Developer Intern | Summer 2018 |
SLD Laser
Built full-stack web app to visualize and analyze laser test data
Skills
Languages
Other ►
ARM Assembly
Verilog
Libraries and Frameworks
Platforms
Hardware
Board Design ►
EagleCAD
Board Fabrication
Mechanical ►
Sketchup
SolidWorks
3D Printing
