Tiancheng Zhao
Teaching Assistant at Machine Learning Department at CMU
Greater Pittsburgh Region United States
Summary
🤩
Rockstar🎓
Top SchoolTiancheng Zhao is a PhD-trained machine learning researcher and practitioner with 11 years of experience building deep learning and reinforcement learning systems, currently serving as a teaching assistant in CMU’s Machine Learning Department. He founded Om AI and focuses on deep multimodal agents, bridging cutting-edge research with practical implementations for education and industry. At CMU he supports advanced courses spanning generative AI, deep RL, optimization, and deep learning systems, and has applied RL methods to develop training frameworks for game AI during a stint at Tencent Americas. With interdisciplinary graduate training in architectural robotics and advanced infrastructure systems, he brings a systems-oriented perspective to multimodal agent design and deployment. Notably, he combines rigorous academic mentorship with hands-on engineering—mentoring students while shipping research-grade code and frameworks.
11 years of coding experience
Master of Science - MS, Advanced Infrastructure Systems, Master of Science - MS, Advanced Infrastructure Systems at Carnegie Mellon University's College of EngineeringMaster of Science - MS, Machine Learning, Master of Science - MS, Machine Learning at Machine Learning Department at CMUDoctor of Philosophy - PhD, Architectural Robotics, Doctor of Philosophy - PhD, Architectural Robotics at Carnegie Mellon University
Github Skills (124)
transformers10
language-model10
lti10
python10
mscoco10
dialog10
deep-learning10
backbone10
multimodal10
transformer10
nlp10
jax10
tensorflow10
natural-language-processing10
pytorch10
Programming languages (8)
Github contributions (5)
soco-ai/R2Base
Apr 2021 - Jul 2021
A GPU-accelerated ranking & reducing engine for dense or sparse vectors indexes.
Contributions:1 release, 63 PRs, 54 pushes in 3 months
indexesgpuvectorsacceleratedsparse
snakeztc/NeuralDialog-LAED
Apr 2018 - Jan 2019
PyTorch implementation for Interpretable Dialog Generation ACL 2018, It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU
Contributions:24 commits, 1 PR, 19 pushes in 8 months
pytorchcenterdialogmeta-learningunsupervised-learning
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