Mitigating Bias in Machine Learning

Dana Thimons is a librarian on the McGraw Hill Customer Success team. Prior to joining McGraw Hill, Dana has worked as a health sciences librarian in academic and hospital libraries. Dana earned a Master of Science in Library and Information Studies from Florida State University and a Master of Science in Health Law from Nova Southeastern University.

Wesley Holloway is a Customer Success Librarian at McGraw Hill. He served as a library specialist and health sciences librarian with the University of Tennessee for four years. Wesley earned his MLS from Indiana University and is dedicated to user education.

Ashley Weinheimer is a Customer Success Librarian at McGraw Hill. She has served as a STEM librarian at a variety of institutions, including at an academic engineering library, a corporate R&D center library, and a public library. Ashley earned her MLIS from University of Pittsburgh and has a Bachelor of Science degree in Chemistry.

Dr. Carlotta A. Berry is a Professor in the Department of Electrical and Computer Engineering at Rose-Hulman Institute of Technology. Dr. Berry is the first Black woman to earn tenure, full professor, and endowed chairship at Rose-Hulman. She has a bachelor’s degree in mathematics from Spelman College, bachelor’s degree in electrical engineering from Georgia Institute of Technology, master’s in electrical engineering from Wayne State University, and PhD from Vanderbilt University. Her research interests are in robotics education, interface design, human-robot interaction, and increasing historically marginalized and minoritized populations in STEM fields. She is author of the book Mobile Robotics for Multidisciplinary Study and co-editor of Mitigating Bias in Machine Learning.

Brandeis Marshall is an entrepreneur, author and data equity strategist. Formerly a college professor, she brings her instructional design and delivery expertise to help leaders, across sectors and industries, clarify their data strategy in order to align people, processes, practices and policies. She also founded Black Women in Data in 2020 to help Black women invest in their career and leadership development as data entrepreneurs, leaders, managers and practitioners.

Jazmia Henry is an AI Research Engineer specializing in AI alignment, MLOps for Large Language Models, and experimental design. As the Founder and Principal AI Researcher at Iso AI, she developed innovative tools including IsoPro and IsoZero for multi-agent reinforcement learning and adversarial testing. Previously, she served as Senior Data and Applied Science Lead at Microsoft and Head of Machine Learning and AI Strategy at Motley Fool. Her research contributions include significant work on LLM calibration and decision-making, published in NeurIPS and other prominent venues. Currently pursuing a DPhil in Social Data Science at Oxford University, Henry combines deep technical expertise in AI safety and interpretability with practical experience in deploying ethical AI systems at scale. Her work has notably advanced the field of AI alignment through the development of robust simulations and testing frameworks that help ensure safe and reliable AI deployment. She is a contributor to Mitigating Bias in Machine Learning.

Thema Monroe-White is an Associate Professor of Artificial Intelligence, and Innovation Policy at the Schar School of Policy and Government and the Department of Computer Science (joint) at George Mason University. Her interests include bias mitigation in artificial intelligence (AI), critical quantitative and computational methods, and racial equity in innovation and entrepreneurship (I&E). She is particularly concerned with understanding the pathways to achieving social and economic empowerment for minoritized groups via I&E, AI education, and emancipatory data science. She has received multiple NSF awards to investigate issues of racial equity in the STEM ecosystem, including serving as a lead member of the research team for the Inclusion in Innovation Initiative (i4), a $3.5 million cooperative partnership to develop a national infrastructure for diversity and inclusion within the NSF Innovation Corps (I-Corps™) Program.  Inspired by her work on intersectional inequalities in science, she has also received funding to investigate the harms of structural racism on the scientific enterprise, and the benefits derived by the inclusion of historically marginalized groups in the scientific workforce. Thema holds a Ph.D. in Science, Technology, and Innovation Policy from the Georgia Institute of Technology, as well as Master's and Bachelor’s degrees in Psychology from Howard University.