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Hi, I’m @JSLJ23
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I work on the intersection of deep learning and high-performance quantum chemistry, with a focus on accelerating electronic structure methods and molecular simulations.
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My research includes equivariant geometric deep learning for DFT, machine-learned exchange–correlation functionals, and neural network potentials for atomistic modeling.
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I’m particularly interested in combining physics-informed DL with efficient algorithms and CUDA/C++ implementations to push the scalability of quantum simulations—reducing computational cost while maintaining high accuracy for real-world chemical systems.
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đź“« How to reach me - joshuaslj231094@gmail.com / www.linkedin.com/in/joshuaslj .
đźŹ
Working from home
Pinned Loading
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libtorch_custom_function
libtorch_custom_function PublicSimple example of a custom function for libtorch with a custom cuda kernel
C++
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AG-JY-Lab/RNA-seq-analysis
AG-JY-Lab/RNA-seq-analysis PublicThis repository maintains an end to end downstream workflow (post FASTQ alignment) of bulk RNA sequencing analysis from gene read counts to functional enrichment analysis.
R 5
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