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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, LLM Agents, and Applied AI Systems
PhD researcher building reliable agentic AI and production-oriented ML systems.
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Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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portfolio
Portfolio item number 1
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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
DIAL: Data-Free Interference-Aware Layer-Scaling via Diagnostic Composition for Task-Vector Model Merging
Under review, Manuscript under review, 2026
Data-free performance enhancement for task-vector model merging.
Recommended citation: Xinyu Wang, Kangwei Deng, Fei Dou, Jinbo Bi, Jiangwen Lu. DIAL: Data-Free Interference-Aware Layer-Scaling via Diagnostic Composition for Task-Vector Model Merging. Manuscript under review, 2026.
SIGMA: Structure-Invariant Generative Molecular Alignment for Chemical Language Models via Autoregressive Contrastive Learning
Preprint, arXiv, 2026
Structure-invariant alignment and isomorphic beam search for autoregressive molecular generation.
Recommended citation: Xinyu Wang, Fei Dou, Jinbo Bi, Minghu Song. SIGMA: Structure-Invariant Generative Molecular Alignment for Chemical Language Models via Autoregressive Contrastive Learning. arXiv:2603.25062, 2026. 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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