Tianshu Huang
Tianshu Huang

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.


University of Texas at Austin Aug 2017 - Present
GPA: 3.95
  • Convex Optimization
  • Probability and Stochastic Processes I (Graduate)
  • Theory of Probability (Graduate)
  • Geometric Foundations of Data Science (Graduate)
  • Real Analysis I, II
Computer Science:
  • Geometric Foundations of Data Science (Graudate)
  • Operating Systems
  • Computer Architecture
  • Algorithms
Electrical Engineering:
  • 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
  • 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


Scripting ► Python R JavaScript
Compiled ► C C++ CUDA Rust Java
Other ► ARM Assembly Verilog
Libraries and Frameworks
Web ► Django Celery D3.js Node.js
Data Science ► Python C API OpenCV Numpy SciKit-Learn
Web ► Apache RabbitMQ SQL
Platforms ► Ubuntu FreeBSD VirtualBox ESXi FreeRadius
Board Design ► EagleCAD Board Fabrication
Mechanical ► Sketchup SolidWorks 3D Printing