Jiacheng Lin
Research Assistant at University of Illinois Urbana-Champaign
Urbana, Illinois, United States
Summary
👤
Senior🎓
Top SchoolJiacheng Lin is a CS Ph.D. candidate at UIUC with eight years of research and industry experience applying deep learning to coding, reasoning, drug discovery, recommendation systems, and combinatorial optimization. He currently works as an AI Research Scientist Intern at MiroMind.ai focusing on mid/post-training and evaluation for coding and reasoning models while also conducting research at UIUC. His background spans top labs and companies—Microsoft, Amazon, ByteDance, and Keiji AI—where he shipped applied models for foundational AI, recommendation, and DDI prediction. Earlier work at Tsinghua combined transformers with MILP techniques for variable selection in branch-and-bound and optimization problems, reflecting a rare blend of ML and mathematical programming. He is comfortable transitioning ideas from theory to production, having implemented systems ranging from real-time depth estimation to transformer-based decision modules. Outside the lab, his homepage and GitHub showcase an academic-to-industry trajectory that emphasizes reproducible research and practical model evaluation.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Illinois Urbana-ChampaignMaster's degree Automation, Master's degree Automation at Tsinghua University
Chinese, English
Github Skills (32)
stereo7
docking7
proteins7
nonlinear-optimization6
self-supervised-learning6
supervised-learning6
graph6
python-interface6
molecule6
chainer6
modeling5
science5
deep-learning5
discovery5
scip5
Programming languages (2)
Github contributions (5)
linjc16/R2-DDI
Jun 2022 - Dec 2022
Official implementation of "R2-DDI: Relation-aware Feature Refinement for Drug-drug Interaction Prediction".
Contributions:8 commits, 1 PR, 9 pushes in 6 months
linjc16/ActiveStereoNet
Aug 2019 - Apr 2020
Customized Implementation of ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems
Contributions:22 commits, 22 PRs, 19 pushes in 8 months
pytorchsupervised-learningend-to-endsupervisedstereo
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