Mírian Silva

Research Interest

• Fairness and Bias in AI, Ethics & Trustworthy AI. Interdiciplinary research in AI and Law, AI and Social Sciences, AI and Public Policy are currently my main topic of interest. If you are working on these or related topics, and search for research collaborations feel free to reach out to me.

TLDR: Academic and Professional background

• I've been an AI Engineer at IBM Research since 2021. I work with the AI Models Team and the MIT-IBM Watson AI Lab, mainly programming cool stuff related to foundation models, generative AI, doing a lot of AI engineering.
  • Open-source projects: github.com/IBM/ibm-generative-ai. A Python library built on IBM's large language model REST interface to seamlessly integrate and extend this service in Python programs.
  • Research publications from my work, can be found in my page at the IBM Research profile.
• I recently received a Master's Degree in Computer Science at the Federal University of Minas Gerais (UFMG, Brazil), with research based on AI focused on machine learning fairness, bias mitigations, and evaluation practices. I also hold a B.Sc in Computational Mathematics, a degree based on computer science and applied mathematics, from the same university (UFMG).
  • Mírian Silva. (2024). A study of the nuances of ai fairness development in practice: A framework for designing bias mitigation interventions (Master’s Thesis, Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil). Available at http://hdl.handle.net/1843/78989.
• Previous Research Fellow and Visiting Scholar at the University of California, Berkeley, in the Berkeley Equity and Access in Algorithms, Mechanisms, and Optimization (BEAAMO) Research Group. Working on auditing and evaluating algorithmic tools and evidentiary statistical software used in criminal legal systems. Supervised by Prof. Rediet Abebe, Ph.D.
• I usually organize workshops at top-tier AI conferences such as NeurIPS, ICML, and NAACL, as chair organizer of Black in AI affinity groups.