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WiDS New York @ IBM 2022 - A Recap

By Susan Malaika posted Mon May 16, 2022 10:59 AM


Many thanks to the speakers and panelists

In mid-December 2021, 7 women from IBM located in the Greater New York City region decided to sign up as Women in Data Science (WiDS) ambassadors and organize a Women in Data Science regional event

After over 4 months of planning and preparation, the WiDS NYC @ IBM 2022 event held on April 29, 2022, featuring 6 technical talks by women at the forefront of data science from industry and academia; including a keynote talk by IBM Fellow Aleksandra (Saska) Mojsilovic on  "Ethics vs. Trust vs. Governance vs. Good: Many facets of Beneficial and Responsible AI"; and a panel discussion on "Data Science Careers in industry and academia".

The topics covered by the speakers ranged from AI governance, Data Science certification to technical implementations of different data science and machine learning use cases. 

The Event Speakers and Panelists included:

Many different data science and machine learning use cases were covered by Dr. Isik, Kara Yang and Dr. Kaplan. Dr. Isik demonstrated how ML can be leveraged to perceive others' social interactions, and subsequently develop artificial systems that share this core human ability.  
Kara Yang presented natural science use cases developed on Amazon Sage Maker, that leveraged deep convolutional networks to detect and map solutions based on imagery collected from fixed wing aircraft surveying.
Dr. Kaplan's talk gave an overview of algorithms and methods of causal inference, and provided a practitioner's perspective on applicability of different causal inference methods. There was an added emphasis on the ethical implications of causal inferential methods.

The event was streamed on Watson Media channel and a recap is available -

Highlights from the event

  • A discussion on Ethics, Responsibility and Trustworthy AI - across Saska and Haniyeh's talks as well as the Q&A session with them
  • Samar/Maureen's presentation - and how they emphasized about driving your own career, getting a mentor, getting certified in Data Science
  • Spirited panel discussion on Data Science Careers in industry and academia between 4 industry professionals and 2 academics.
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