Northeast Big Data Hub Newsletter | March 31, 2021
  • New Jersey Institute of Technology's Institute for Data Science Spring 2021 Seminar Series - March-April
  • Data Science Seminar: Data Science for Good - Creating Meaningful Societal and Scientific Impact Through Data Science - April 5
  • Cybersecurity as Big Data Science Interactive Workshop - April 12
  • 2021 COVID-19 Research Webinar: Lightning Talks and Q&A - April 14
  • Northeast Student Data Corps Panel - April 16
  • Privacy, Ethics & Trust in Connected Healthcare Workshop - April 28
  • BARI Conference 2021: Building Back Smarter - April 30
  • COVID Information Commons Student Paper Challenge - Due April 1
  • Apply to the NIH DATA Scholars Program - Due April 9
  • Instructional Faculty Position in Data Science


Data Science Seminar: Data Science for Good - Creating Meaningful Societal and Scientific Impact Through Data Science

Date: April 5, 2021 10:00 am ET


The Data Science seminar series Cohosted by the University of Rhode Island's Data Science Program, the University of Rhode Island's AI Lab, and the Rhode Island AI Meetup Group will be hosting it's next speaker, Florence Hudson, who will be focusing on Data Science for Good - Creating Meaningful Societal and Scientific Impact Through Data Science. 

Data science is a valuable tool we can leverage across many disciplines to enable positive societal and scientific impact in many ways. From healthcare to environmental studies, security to ethics, criminal justice to economics, developing valuable insights from data can enable more informed decision making and improved outcomes which touch many dimensions of our lives. Increasing data science literacy will enable our students, citizens, industry and government leaders to leverage the vast amounts of data which are increasingly available to us from the past, present and future in order to gain insights which enable us to make our world a better place. In this workshop you will learn about the goals and activities led by the community of the Northeast Big Data Innovation Hub to leverage data science for good, and ways that you can get involved and be part of the solution. The speaker will also share her personal and professional journey. In preparation for the workshop, please read about the Northeast Big Data Innovation hub strategy and projects here.

 Learn more about the event details here and find the meet up link for the event here.

Florence Hudson is Executive Director of the Northeast Big Data Innovation Hub at
Columbia University, and Founder & CEO of FDHint, LLC, a global advanced
technology and diversity & inclusion consulting firm. She leads the COVID Information
 funded by NSF, providing an open resource
to explore research and enable global collaboration to address the COVID-19

Florence is also available to present at other institutions around the Northeast on how to leverage Data Science for good. If you are interested in hosting Florence please send us an email at 
New Jersey Institute of Technology's Institute for Data Science Spring 2021 Seminar Series
New Jersey Institute of Technology's Institute for Data Science invites you to their Spring 2021 seminar series, held Wednesdays at 4 PM Eastern Time. The series includes data science thought leaders from academia and industry.

The schedule of events and speakers is as follows:

March 31 - Danai Koutra, University of Michigan
April 7 - Charles Leiserson, Massachusetts Institute of Technology
April 14 - Aydin Buluc, Lawrence Berkeley National Lab
University of California, Berkeley
April 21 - Tina Eliassi-Rad, Northeastern University
April 28 - Joseph JaJa, University of Maryland

You can find out more information about the series here.
Follow the series on Eventbrite here
Subscribe to the YouTube channel here

Cybersecurity as Big Data Science Interactive Workshop 

Date: April 12, 2021, 3:00-4:30pm EDT (UTC-4)

We welcome you to join us for an interactive workshop to discuss and design data science techniques to address current and emerging cybersecurity challenges.  

The workshop objectives are to: 

  • Understand common and unique data science challenges for cybersecurity data.
  • Share best data science practices, technical and non-technical, for cybersecurity challenges.

Cybersecurity challenges we will discuss and determine how to address with data science tools and techniques include:

  • Ever-evolving data from sources such as log files, intrusion alerts, vulnerability databases, dark web, and GitHub.
  • Data quality issues such as susceptibility to adversarial attacks, lack of labeled data, high signal-to-noise ratios, and data fragmentation.

Experts in data science, databases, visualization, statistics, feature engineering, modeling, reproducibility, streaming data, heterogeneous data, irregular data, explainable AI, and human-centered computing in all application areas, and cybersecurity are encouraged to join the workshop. 

See the full agenda and register here.

April 2021 COVID-19 Research Webinar: Lightning Talks and Q&A

Date: Wednesday, April 14th, at 2:30-3:30 pm Eastern Time. 
Click here to learn more and register.

Meet the scientists seeking new insights on COVID-19. Every month, we bring together a group of researchers studying wide-ranging aspects of the current pandemic, to share their research and answer questions from our community. Learn more about their ongoing efforts in the fight against COVID-19, including opportunities for collaboration.

Join us to hear from the following speakers. Register here for your unique Zoom link and calendar information.

Brian Chang, Clark University: Predicting Coronavirus Disease (COVID-19) Impact with Multiscale Contact and Transmission Mitigation. Funded by NSF Mathematical and Physical Sciences / Division of Materials Research.

Lalitha Sankar, Arizona State University: Federated Analytics based Contact Tracing for COVID-19. Funded by NSF Computer and Information Science and Engineering / Computer and Network Systems.

Song Gao, University of Wisconsin-Madison: Geospatial Modeling of COVID-19 Spread and Risk Communication by Integrating Human Mobility and Social Media Big Data. Funded by NSF Social, Behavioral and Economic Sciences / Division of Behavioral and Cognitive Sciences.

Dan O'Brien, Northeastern University: Infection Transmission of COVID19 in Urban Neighborhoods. Funded by NSF Social, Behavioral and Economic Sciences / Division of Behavioral and Cognitive Sciences.

Kollbe Ahn, ACatechol, Inc.: Virucidal surface coatings for prevention of COVID-19 transmission. Funded by NSF Engineering / Industrial Innovation and Partnerships.

Jaideep Vaidya, Rutgers University-Newark: Privacy-Preserving Crowdsensing of COVID-19 and its Sociological and Epidemiological Implications. Funded by NSF Computer and Information Science and Engineering / Division of Computer and Network Systems.

Olga Wilhelmi, University Corporation For Atmospheric Research: Responding to extreme heat in the time of COVID-19. Funded by NSF Social, Behavioral and Economic Sciences / Division of Behavioral and Cognitive Sciences.

Northeast Student Data Corps: Data Science Career Panel 

Date: April 16, 2021, 3:00pm ET - 4:00pm ET


If you are currently pursuing a data science career, or aspire to, please join us for this Data Science Career Panel. Learn more about why you should leverage data science for good from those who are pursuing and working in data science. Newly launched by our Northeast Student Data Corps (NSDC), the Data Science Career Panel webinar series features experts from academia, government, industry, and nonprofits who share their experiences learning and using data science. These virtual events aim to highlight the wide range of educational opportunities and career paths available in data science and data analytics. You will learn about the learner, educator and career resources available to you on the NSDC website as well. 

Join us at our upcoming Data Science Career Panel virtual event on Friday, April 16, 2021, 3-4 pm Eastern Time to hear the following speakers discuss their career experiences in data science.

Panelists will include:

Sanjana Reddy Pasnuri, data scientist for the Expert Labs Learning Team, IBM, North Carolina, US. 

Jason Williams, Assistant Director, External Collaborations at the Cold Spring Harbor Laboratory DNA Learning Center in Long Island, NY.

Dr. Patricia OrdóñezAssociate Professor in the Computer Science faculty at the University of Puerto Rico Río Piedras.

Martin Pavlovski, Ph.D. candidate and a Research Assistant at the Center for Data Analytics and Biomedical Informatics at Temple University in Philidelphia.

To learn more about the event and speaker details please visit the event page here.

Privacy, Ethics and Trust in Connected Healthcare Workshop
Date: April 28, 2021, 11:00am–2:00pm ET


The Global Connected Healthcare Cybersecurity Virtual 2021 Workshop Series is presented by the IEEE SA, IEEE/UL P2933™ Standards Working Group, and the Northeast Big Data Innovation Hub headquartered at Columbia University. The second workshop in the series will focus on Privacy, Ethics and Trust in Connected Healthcare.

Addressing Privacy and Ethics requirements in connected healthcare and IoT systems design and development is vital to develop trust in using IoT based systems in the healthcare domain. IoT based connected healthcare systems require an appreciation of both the ethico-legal milieu and the sociopolitical landscape. It has been noticed that one of the issues in the low adoption of IoT applications among end-users is the lack of trust in connected healthcare and IoT devices concerning data protection, privacy and safety.

Workshop participants will explore the latest technologies, challenges, and regulations regarding privacy, ethics and trust for connected health IoT systems, and make recommendations for the future. The learning outcomes and topics for  discussion will include but are not limited to:

  • Identifying data protection and privacy consideration when designing and developing new devices and connections to legacy systems and devices , to improve trust among people using IoT devices and systems, and trust in device to device connections.
  • Identification of the ethical issues that need to be addressed with connected health IoT.  E.g Individual rights; autonomy, privacy and confidentiality; ownership of the data;  necessity and proportionality; beneficence and nonmaleficence. How do we satisfy these ethical requirements in designing and developing connected health IoT solutions? 
  •  Identification of frameworks, standards and legal regulations related to privacy in Connected Health IoT based system

The expert panel includes Jeannette WingDirector, Data Science Institute, Columbia University; Julia Stoyanovich , New York University, Responsible Data Science and Co-Leader, Institute for a Framework for Integrative Data Equity SystemsShaneel Pathak, CEO & Co-Founder, Zoe Insights; and Dipak Kalra, President at The European Institute for Innovation through Health Data, moderated by Deborah Peel, Founder and President at Patient Privacy Rights.

Visit the event page for updates and registration details for the entire Global Connected Healthcare Cybersecurity Virtual Workshop Series from February through November 2021.

Thank you to those who joined us as part of the first workshop of the Global Connected Healthcare Cybersecurity Virtual 2021 Workshop Series presented by the IEEE SA, IEEE/UL P2933™ Standards Working Group, and the Northeast Big Data Innovation Hub headquartered at Columbia University. The first workshop in the series, Global Connected Healthcare Cybersecurity Risks and Roadmap, was held on February 24th 2021.

Watch recordings of the workshop assessing and addressing cybersecurity risks in the growing connected healthcare ecosystem and discuss a potential roadmap to address these risks.

Be sure to join us for second workshop in the series workshop which will focus on Privacy, Ethics and Trust in Connected Healthcare.

BARI Conference 2021: Building Back Smarter

Date: April 30, 2021

Over the last ten years, BARI’s annual conference has been a unique forum for sharing how greater Boston’s civic data community is advancing a more equitable, just, and democratic society–and setting an agenda for what we need to do now. In 2021 this mission is more critical than ever. As the world builds back from a crippling pandemic and grapples with revelations of racial injustice and inequities, BARI wants to highlight efforts where data and technology are catalyzing recovery as the world looks toward the future. 

To find out more, please visit the conference page here.


COVID Information Commons
Undergraduate Student Paper Challenge


The COVID Information Commons (CIC) is an NSF-funded research collaboration and knowledge hub designed to facilitate knowledge sharing and collaboration across various COVID research efforts. The CIC Student Paper Challenge is an opportunity for undergraduate students to leverage the CIC NSF Award search tools and the global COVID-19 resources the CIC offers to learn how the scientific research community is working to address the widespread impacts of the pandemic and offer their own insights on the next steps for COVID-19 research.

Student Papers due April 1, 2021 at 11:59 PM ET 
Judges will review submissions through April

For full details about the Challenge, please visit the CIC Student Paper Challenge webpage
. If you have any questions, please feel free to contact

NIH DATA Scholars Program Now Accepting Applications
Applications due: April 9, 2021

The National Institutes of Health (NIH) Office of Data Science Strategy (ODSS) Data and Technology Advancement (DATA) National Service Scholar Program is seeking experienced data and computer scientists and engineers to tackle challenging biomedical data problems with the potential for substantial public health impact.

Applicants should possess technical skills in one or more of the following areas, as relevant to their proposed project area(s): artificial intelligence, cloud computing, data engineering, data science, database management, project management, software design, supercomputing, and/or bioinformatics. Industry experience is desired. Applicants should have an M.D., Ph.D. or equivalent doctoral degree and have advanced experience in data science or related fields. Appointees may be U.S. citizens, resident aliens, or non-resident aliens with, or eligible to obtain, a valid employment-authorization visa. Applications from women, minorities, and persons with disabilities are strongly encouraged

Learn more here.
Goergen Institute for Data Science at the University of Rochester: Instructional Faculty Position in Data Science
Spring 2021
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Thank you, and be well — Northeast Big Data Innovation Hub Team
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