Yali Bian
I am a senior research scientist at Human & AI Systems Research Lab (HAR), Intel Labs. I am working on designing systems that enable effective collaborations between human and interactive deep learning models. I got my Ph.D. in Computer Science, at Virginia Tech, working with Dr. Chris North at InfoVis Lab. Before that, I got an M.S. degree in Computer Science at Zhejiang University.
Human-AI Collaboration Interactive ML, eXplainable AI, Visual Analytics,
Professional Experience
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Establishing an AI-assisted image annotation system to reduce annotation efforts and accelerate DL model building for object detection tasks;
Building an exploratory data analysis platform with interpretable DL to help help stakeholders for decision making process. -
Built the ML pipeline to standardize the ML development life cycle and fully utilize existing ML platforms.
Built a Feature Store (Marketplace) system to manage, monitor, and serve batch and streaming features. -
Akuna Capital
Software Development Engineer2019 – 2020Led a team in building trade surveillance and compliance application to monitor and analyze live trading behaviors from the message streaming platform, and optimized the system processing efficiency by 72%. -
Facebook
Machine Learning Engineer InternMay 2018 – Aug 2018Machine Learning Group, Facebook, Seattle.Building alumni groups recommendation model for Facebook users through Sparse Neural Networks (SparseNN) and Gradient Boosting Decision Tree(GBDT). -
NOKIA Bell Labs
Machine Learning Research InternJun 2017 – Aug 2017Supervisor: Chitra Phadke; Huseyin UzunaliogluBuilding a smarter visual analytics system through semantic interaction and data-driven model selection to reduce human’s efforts on gaining insights from big and complex data.
Selected Publications
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Self-label correction for image classification with noisy labelsPattern Analysis and Applications
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Towards Human-Centered Pavement Quality Annotation with Crowdsourcing.The 20th International Conference on Mobile Systems and Pervasive Computing (MOBISPC 2023). (Accepted)
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Semantic Explanation of Interactive Dimensionality Reduction.IEEE VIS 2021
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Semantic Explanation of Interactive Dimensionality Reduction.IEEE VIS 2021
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DeepVA: Bridging Cognition and Computation through Semantic Interaction and Deep Learning.Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19.
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Evaluating Semantic Interaction on Word Embeddings via SimulationEValuation of Interactive VisuAl Machine Learning systems, an IEEE VIS 2019 Workshop
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CKGHV: A comprehensive knowledge graph for history visualization.Proceedings of the 14th ACM/IEEE-CS Joint Conference on Digital Libraries. IEEE Press, 2014
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Discovering Treatment Pattern in Traditional Chinese Medicine Clinical Cases by Exploiting Supervised Topic Model and Domain Knowledge.Journal of Biomedical Informatics 58: 260-267 (2015)Concept over time: the combination of probabilistic topic model with wikipedia knowledge.Expert Systems with Applications, Volume 60, 27-38 (2016)
Featured Projects