Yunfeng Zhang | 张云峰

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I am a Senior ML engineer at EvolutionIQ. Previously, I worked at Twitter and IBM Research. At Twitter, I developed a distributed model evaluation system for evaluating model performance and fairness. I am passionate about developing fair, transparent, and trustworthy AI, as well as making machine learning systems more understandable and user friendly. My recent projects include AI Fairness 360 and AI Explainability 360 toolkits, chatbot development framework, multi-modal interactive systems, modeling social interactions, and understanding and remediating cognitive biases.

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selected publications

  1. FAccT
    De-Biasing “Bias” Measurement
    Lum, Kristian,  Zhang, Yunfeng, and Bower, Amanda
    In 2022 ACM Conference on Fairness, Accountability, and Transparency 2022
  2. arXiv
    One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
    Arya, Vijay, Bellamy, Rachel K. E., Chen, Pin-Yu, Dhurandhar, Amit, Hind, Michael, Hoffman, Samuel C., Houde, Stephanie, Liao, Q. Vera, Luss, Ronny, Mojsilović, Aleksandra, Mourad, Sami, Pedemonte, Pablo, Raghavendra, Ramya, Richards, John, Sattigeri, Prasanna, Shanmugam, Karthikeyan, Singh, Moninder, Varshney, Kush R., Wei, Dennis, and Zhang, Yunfeng
    arXiv:1909.03012 [cs, stat] Sep 2019
  3. arXiv
    AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
    Bellamy, Rachel K. E., Dey, Kuntal, Hind, Michael, Hoffman, Samuel C., Houde, Stephanie, Kannan, Kalapriya, Lohia, Pranay, Martino, Jacquelyn, Mehta, Sameep, Mojsilovic, Aleksandra, Nagar, Seema, Ramamurthy, Karthikeyan Natesan, Richards, John, Saha, Diptikalyan, Sattigeri, Prasanna, Singh, Moninder, Varshney, Kush R., and Zhang, Yunfeng
    arXiv:1810.01943 [cs] Oct 2018
  4. NeurIPS
    Model Agnostic Multilevel Explanations
    Natesan Ramamurthy, Karthikeyan, Vinzamuri, Bhanukiran,  Zhang, Yunfeng, and Dhurandhar, Amit
    In Advances in Neural Information Processing Systems Oct 2020
  5. FAccT
    Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making
    Zhang, Yunfeng, Liao, Q. Vera, and Bellamy, Rachel K. E.
    In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency Jan 2020