Speakers and Panelists
Besmira Nushi
Besmira Nushi is a Principal Researcher in the Adaptive Systems and Interaction group at Microsoft Research. Her interests lie at the intersection of human and machine intelligence focusing on Reliable Machine Learning and Human-AI Collaboration. In the last five years, she has made practical and scientific contributions on implementing and deploying Responsible AI tools for debugging and troubleshooting ML systems. Prior to Microsoft, Besmira completed her doctoral studies at ETH Zurich in 2016 on optimizing data collection processes for Machine Learning.
Sara Hooker
Sara Hooker is a researcher at Google Brain doing deep learning research on training models beyond test-set accuracy to fulfill multiple desiderata. Her main research interests gravitate to deep neural network interpretability, model compression and security. In 2014, she founded Delta Analytics, a non-profit that works with non-profits and communities all over the world to build technical capacity and empower others to use data.
Kush Varshney
Kush R. Varshney is a distinguished research staff member and manager with IBM Research at the Thomas J. Watson Research Center, Yorktown Heights, NY, where he leads the machine learning group in the Foundations of Trustworthy AI department. He was a visiting scientist at IBM Research - Africa, Nairobi, Kenya in 2019. He is the founding co-director of the IBM Science for Social Good initiative. He applies data science and predictive analytics to human capital management, healthcare, olfaction, computational creativity, public affairs, international development, and algorithmic fairness, which has led to recognitions such as the 2013 Gerstner Award for Client Excellence for contributions to the WellPoint team and the Extraordinary IBM Research Technical Accomplishment for contributions to workforce innovation and enterprise transformation, and Harvard Belfer Center Tech Spotlight runner-up for AI Fairness 360. His work has been recognized through best paper awards at the Fusion 2009, SOLI 2013, KDD 2014, and SDM 2015 conferences and the 2019 Computing Community Consortium / Schmidt Futures Computer Science for Social Good White Paper Competition. He is currently writing a book entitled 'Trust in Machine Learning' with Manning Publications. He is a senior member of the IEEE and a member of the Partnership on AI's Safety-Critical AI expert group.
Sarah Bird
Sarah Bird is currently leading Responsible AI for the Azure Cognitive Services. Prior to joining the Cognitive Services, Sarah lead the development of responsible AI tools in Azure Machine Learning. She is an active member of the Microsoft AETHER committee, where she works to develop and drive company-wide adoption of responsible AI principles, best practices, and technologies. Sarah was one of the founding researchers in the Microsoft FATE research group and prior to joining Microsoft worked on AI fairness in Facebook. Sarah’s work focuses on research and emerging technology strategy for AI products in Azure. Sarah works to accelerate the adoption and positive impact of AI by bringing together the latest innovations in research with the best of open source and product expertise to create new tools and technologies.
Nashlie H. Sephus
Dr. Nashlie H. Sephus is the former Applied Science Manager/current Tech Evangelist for Amazon AI focusing on fairness and identifying biases at AWS AI. She formerly led the Amazon Visual Search team in Atlanta, which launched visual search for replacement parts on the Amazon Shopping app in June 2018. This technology was a result of former Atlanta-based startup Partpic being acquired by Amazon, for which she was the Chief Technology Officer. Prior to working at Partpic, she received her Ph.D. from the School of Electrical and Computer Engineering at the Georgia Institute of Technology in 2014 and worked for a year with Exponent, a technical consulting firm, in New York City. Her core research areas were digital signal processing, machine learning, and computer engineering. She received her B.S. in Computer Engineering from Mississippi State University (MSU) in 2007. She was featured as Georgia Tech’s inaugural top 40 under 40 alumni in 2020 and received MSU's College of Engineering Young Emerging Leader Award in 2019. In 2018, Dr. Sephus became the founder and CEO of The Bean Path non-profit organization based in Jackson, MS, her hometown, assisting individuals and startups with technical expertise and guidance.
Julia Stoyanovich
Data science technology promises to improve people's lives, accelerate scientific discovery and innovation, and bring about positive societal change. Yet, if not used responsibly, this same technology can reinforce inequity, limit accountability, and infringe on the privacy of individuals. In my talk I will give an overview of the "Data, Responsibly" project that aims to operationalize ethics and legal compliance in data science systems. In particular, I will speak about my involvement in efforts to regulate the use of data science and AI in New York City, and about the imperative to establish a broad and inclusive educational agenda around responsible data science.
Bio: Julia Stoyanovich is an Assistant Professor of Computer Science & Engineering, and of Data Science at New York University (NYU). She directs the Center for Responsible AI at NYU, a hub for interdisciplinary research, public education, and advocacy that aims to make responsible AI synonymous with AI. Julia's research focuses on responsible data management and analysis: on operationalizing fairness, diversity, transparency, and data protection in all stages of the data science lifecycle. Julia developed and has been teaching courses on Responsible Data Science at NYU, and is a co-creator of an award-winning comic book series on this topic. In addition to data ethics, Julia works on the management and analysis of preference data, and on querying large evolving graphs. She holds M.S. and Ph.D. degrees in Computer Science from Columbia University, and a B.S. in Computer Science and in Mathematics & Statistics from the University of Massachusetts at Amherst. Julia is a recipient of an NSF CAREER award and of an NSF/CRA CI Fellowship.