Xing Han
Postdoctoral Fellow at The Johns Hopkins University
Baltimore, Maryland, United States
Summary
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Senior🎓
Top SchoolXing Han is a Postdoctoral Fellow in the Department of Computer Science at Johns Hopkins University, focusing on statistical machine learning and deep learning. He pairs a strong mathematical foundation with practical software engineering, boasting 8 years of experience in Python, Java, Matlab/Octave, LaTeX, and ML frameworks such as PyTorch, TensorFlow, Scikit-Learn, Pandas, Numpy, and Seaborn. His research spans variational and Bayesian inference, MCMC, policy gradients, and time-series forecasting, with influential industry exposure from Google, Intuit, Salesforce, and CognitiveScale internships, alongside a current Hopkins appointment. He brings a rare hardware-aware dimension to ML, with experience in Verilog, Xilinx Vivado, and related tools, enabling end-to-end systems that integrate software and hardware. Based in Baltimore, MD, he earned a PhD in Machine Learning from UT Austin and a First Class Honors BE in Electrical/Electronic and Communications Engineering from the University of Edinburgh, underscoring a deep, interdisciplinary training.
9 years of coding experience
2 years of employment as a software developer
B.E., Electrical, Electronic and Communications Engineering Technology/Technician, Graduated with the First Class Honor, B.E., Electrical, Electronic and Communications Engineering Technology/Technician, Graduated with the First Class Honor at The University of EdinburghDoctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at The University of Texas at AustinHigh School Diploma, Math & Science, High School Diploma, Math & Science at Taian No.1 Senior High School
French, English, ChineseGithub contributions (5)
aaronhan223/SLCP
Sep 2021 - Jun 2022
Contributions:43 commits in 9 months
aaronhan223/htsf
Jan 2022 - Oct 2022
Contributions:34 commits, 18 pushes in 9 months
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