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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Machine Learning & Systems
Xinyu Wang — developing machine learning methods and the systems that make them useful. PhD candidate at UConn, seeking full-time ML and research engineering opportunities.
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Posts
Future Blog Post
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Blog Post number 4
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portfolio
Portfolio item number 1
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Portfolio item number 2
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publications
Collaborative Phenotype Inference from Comorbid Substance Use Disorders and Genotypes
Published, , 2017
Recommended citation: Jin Lu, Jiangwen Sun, Xinyu Wang, Henry R. Kranzler, Joel Gelernter, and Jinbo Bi Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 392-397, 2017. http://www.engr.uconn.edu/~jil14036/paper/bibm-lu-2017.pdf
Inferring Phenotypes from Substance Use via Collaborative Matrix Completion
Published, BMC Systems Biology, 2018
Collaborative matrix completion for phenotype inference from substance use.
Recommended citation: Jin Lu, Jiangwen Sun, Xinyu Wang, Henry R. Kranzler, Joel Gelernter, Jinbo Bi. Inferring phenotypes from substance use via collaborative matrix completion. BMC Systems Biology, 12, 15-27, 2018. https://bmcsystbiol.biomedcentral.com/articles/10.1186/s12918-018-0623-5
Fragment-based Deep Molecular Generation Using Hierarchical Chemical Graph Representation and Multi-resolution Graph Variational Autoencoder
Published, Molecular Informatics, 2023
Hierarchical chemical graph representation and multi-resolution graph VAE for molecular generation.
Recommended citation: Zhenxiang Gao, Xinyu Wang, Blake Blumenfeld Gaines, Xuetao Shi, Jinbo Bi, Minghu Song. Fragment-based deep molecular generation using hierarchical chemical graph representation and multi-resolution graph variational autoencoder. Molecular Informatics, 42(5), 2200215, 2023. https://onlinelibrary.wiley.com/doi/10.1002/minf.202200215
Polyhedron Attention Module: Learning Adaptive-Order Interactions
Published, Advances in Neural Information Processing Systems 36 (NeurIPS), 2023
Adaptive-order interaction modeling with a polyhedron attention module.
Recommended citation: T. Zhu, F. Dou, Xinyu Wang, Jiangwen Lu, Jinbo Bi. Polyhedron attention module: learning adaptive-order interactions. Advances in Neural Information Processing Systems 36 (NeurIPS), 9213-9225, 2023.
Cross-platform Prediction of Depression Treatment Outcome Using Location Sensory Data on Smartphones
Preprint, arXiv, 2025
Cross-platform mobile sensing and domain adaptation for depression treatment outcome prediction.
Recommended citation: Soumyashree Sahoo, Chinmaey Shende, Md. Zakir Hossain, Parit Patel, Yushuo Niu, Xinyu Wang, Shweta Ware, Jinbo Bi, Jayesh Kamath, Alexander Russel, Dongjin Song, Qian Yang, Bing Wang. Cross-platform Prediction of Depression Treatment Outcome Using Location Sensory Data on Smartphones. arXiv:2503.07883, 2025. https://arxiv.org/abs/2503.07883
Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks
Preprint, arXiv, 2025
Partial SMILES validation for reinforcement learning based molecular generation.
Recommended citation: Xinyu Wang, Jinbo Bi, Minghu Song. Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks. arXiv:2505.00530, 2025. https://arxiv.org/abs/2505.00530
Beyond Linear Depth Scaling: Diagnosing Piecewise Layer Reliability for Data-Free Model Merging (DIAL)
Submitted to NeurIPS 2026, Submitted to NeurIPS 2026, 2026
Data-free performance enhancement for task-vector model merging.
Recommended citation: X. Wang, K. Deng, F. Dou, J. Bi, J. Lu. Beyond Linear Depth Scaling: Diagnosing Piecewise Layer Reliability for Data-Free Model Merging (DIAL). Submitted to NeurIPS 2026.
SIGMA: Semantic Identifier Grouping for Molecular Autoregression
Submitted to AAAI 2027, Submitted to AAAI 2027, 2026
Structure-invariant alignment and isomorphic beam search for autoregressive molecular generation.
Recommended citation: X. Wang, F. Dou, J. Bi, M. Song. SIGMA: Semantic Identifier Grouping for Molecular Autoregression. Submitted to AAAI 2027. https://arxiv.org/abs/2603.25062
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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