Women in Data Science (WiDS) New Jersey
Friday, March 12, 2021
10:00 a.m. – 1:00 p.m., EST, Virtual
A virtual conference showcasing women in data science, and bringing people together to share experiences, inspire, and educate those interested in data science.
Edge, IEEE Women in Engineering Princeton, and Verizon are proud to collaborate with Stanford University to bring the Women in Data Science (WiDS) conference to New Jersey. The virtual one-day conference will feature speakers from academia and industry, to talk about the latest data science-related research in a number of domains, to learn how leading edge companies are leveraging data science for success, and to connect with potential mentors, collaborators and others in the field.
WiDS New Jersey is an independent event organized by New Jersey WiDS Ambassadors to coincide with the annual Global Women in Data Science (WiDS) Conference held at Stanford University and an estimated 150+ locations worldwide. All genders are invited to attend WiDS regional events, which features outstanding women doing outstanding work.
Opening Keynote Speaker
Anu Ramaswami, PhD
Data Science for Sustainable, Healthy, and Equitable Cities
Anu Ramaswami, Ph.D., is a professor at Princeton University in India studies, civil and environmental engineering, and the High Meadows Environmental Institute. She is an interdisciplinary environmental engineer recognized as a pioneer and leader on sustainable urban infrastructure systems. Her work explores how eight key sectors—water, energy, food, buildings, mobility, connectivity, waste management and green/public spaces—shape human and environmental wellbeing.
She is inaugural director of the M.S. Chadha Center for Global India at Princeton University, lead principal investigator and director of the National Science Foundation (NSF)-supported Sustainable Healthy Cities Network, and serves on United Nations Environment’s International Resource Panel and NSF’s Advisory Committee for Environmental Research and Education. She received her BS in chemical engineering from the Indian Institute of Technology Madras in Chennai and her PhD in civil and environmental engineering from Carnegie Mellon University.
Data Science Career Journeys
Principal Product Manager (DevDiv), Microsoft
Executive Director of Advanced Analytics, Verizon
Client Partner IQVIA, The Human Data Science Company
Moderated by Rashmi Ketha
AI/ML Engineer, Verizon
Data Science Research
Statistical Methods Accelerating Research
Zoe Leblanc, PhD
Research Associate, Princeton University
Zoe LeBlanc is a postdoctoral associate and Weld Fellow at the Center for Digital Humanities at Princeton University. She defended the first digital history dissertation at Vanderbilt University in August 2019, and previously worked as a digital humanities developer at the Scholars’ Lab, University of Virginia. At both UVA and Princeton, LeBlanc has taught undergraduate students, graduate fellows, and faculty on a wide range of topics, including the history of digital humanities and the foundations of humanities data analysis. LeBlanc currently serves on the editorial board of the Programming Historian and the executive committee of the Association for Computers and the Humanities.
Data Science in the Humanities
Meredith Martin, PhD
Director of the Center for Digital Humanities, Princeton University
Meredith Martin specializes in anglophone poetry, historical prosody, historical poetics, poetry and public culture, and disciplinary and pedagogical history. She is Associate Professor of English and the Faculty Director of the Center for Digital Humanities at Princeton which started under her leadership in 2014. Her book, The Rise and Fall of Meter, Poetry and English National Culture, 1860-1930 (Princeton UP, 2012), was the winner of the MLA Prize for a First Book, the Warren Brooks Prize for Literary Criticism, and co-winner of the Sonya Rudikoff Prize for the Best First Book in Victorian Studies. She received her Ph.D. in Comparative Literature from the University of Michigan, under the direction of Yopie Prins.
Closing Keynote Speaker
Wind Cowles, PhD
Data Science Across Multiple Disciplines
Dr. Wind Cowles is the founding director of the Office of Research Data and Open Scholarship at Princeton University, and heads the Princeton Research Data Service, a campus-wide initiative that provides training, services, and infrastructure to support effective research data management and stewardship, open data practices, and long-term preservation and reuse. Before joining Princeton, Wind worked at the National Institutes of Health in the Center for Scientific Review, where she oversaw the review of grant applications on research related to a number of areas, including language, cognition, and Alzheimer’s disease. Prior to NIH, Wind was an associate professor in Linguistics at the University of Florida and the director of the Language and Cognition Lab.
Her research interests included the role of working memory, predictive processing, and communicative intent in language use; second language acquisition; and the influence of sociolinguistic factors on speech production in children and adults. She received her PhD in Cognitive Science and Linguistics from UC San Diego, in addition to an MA in Linguistics. She received a BA in Linguistics from the University of Southern California, with minors in Neuroscience and English-Creative Writing.
WiDS Ambassadors and Hosts
The Women in Data Science (WiDS) initiative aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. WiDS started as a one-day technical conference at Stanford in November 2015. Five years later, WiDS is a global movement that includes a number of worldwide initiatives:
- A conference with 150+ regional events worldwide in more than 60 countries, reaching 100,000 participants annually online and in person
- A datathon, encouraging participants to hone their skills using a social impact challenge
- A podcast series, featuring data science leaders from around the world talking about their work, their journeys, and lessons learned along the way
- An education outreach program to encourage secondary school students to consider careers in data science, artificial intelligence (AI), and related fields