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March 23, 2023
Dear Friends,
Don't forget to join us TODAY at 1:30 PM EST for the third HDSI + Harvard SEAS Special Seminar,Data Ethics – Leaders and Frameworks, to learn how leaders make choices around data and organize internal frameworks on data ethics with our speakers from QuantumBlack, AI by McKinsey and Reckitt, and our moderator HDSI Faculty Co-Director David C. Parkes. We hope to see you there!
Visit the HDSI YouTube channel to access the recordings from the first two seminars in this series.
Happy Spring!
The Harvard Data Science Initiative
Today's Special Seminar: Data Leadership, Spring 2023
Join us in the Spring 2023 Term for a series of conversations with McKinsey & Company on digital trust, AI, data governance, ethics, and regulation, featuring industry experts from across sectors like life sciences, NGOs, finance, and more. This series is free and open to the public. View all scheduled seminars on the series page.
Data Ethics – Leaders and Frameworks Hosted by Harvard Data Science Initiative | Co-hosted by Harvard John A. Paulson School of Engineering and Applied Sciences | Featuring McKinsey & Company
Thursday, March 23, 2023
1:30 PM – 2:30 PM EST
Virtual: Zoom
In this recap of CrisisReady’s “Data in Crises” event, co-hosted by the HDSI, learn how experts have used novel data sources in their earthquake response efforts and what challenges continue to hamper these relief efforts.
HDSI funding awarded to HDSI Faculty Affiliate Marinka Zitnik and Harvard Business School Assistant Professor Himabindu Lakkaraju supported recent research which introduces a synthetic graph data generator, SHAPEGGEN, which can generate a variety of benchmark datasets accompanied by ground-truth explanations.
Researchers, including HDSI Faculty Affiliate Ata Kiapour, use machine learning models to predict anterior cruciate ligament (ACL) failure load from MRIs and to determine if those predictions were related to revision surgery incidence.
HDSI Steering Committee Member Isaac Kohane, founding chair of the Department of Biomedical Informatics (DBMI) in the Blavatnik Institute at Harvard Medical School, will be the inaugural editor-in-chief of NEJM AI, the new AI-themed journal from NEJM Group, the publisher of the New England Journal of Medicine. The journal's mission is to generate evidence for medical uses of AI.
Researchers, includingHDSI Faculty Affiliate Michael Baym, modified a strain of Escherichia coli bacteria to be immune to natural viral infections and employed two methods to safely restrain the bacteria and their modified genes. Results from this study may provide the basis for a general strategy to make any organism safely resistant to all natural viruses and prevent genetic information flow into and out of genetically modified organisms.
Friday, March 24, 2023
9:00 AM – 3:30 PM EST
In-person: Linda K. Paresky Conference Center
This year’s annual symposium will focus on recent efforts by quantitative scientists to better understand the complex mechanisms that contribute to health disparities and to develop interventions to reduce or eliminate these disparities. Speakers from Harvard T.H. Chan School of Public Health, Brown University, Cornell Medical College, Drexel University, University of North Carolina at Chapel Hill, and the National Institutes of Health will describe advances that have been made as well as challenges that remain. View agenda, speaker abstracts, and bios.
Friday, March 24, 2023
10:30 AM – 11:30 AM EST
Hybrid: Library Commons or Zoom
At this session of Data + Donuts, Professor Goel will talk about his recent empirical work on access to education. He'll discuss a series of inter-related empirical projects aimed at understanding and reducing disparities in college applications and admissions. Professor Goel will start by showing that a popular college-planning tool dissuades many high-achieving high schoolers from applying to competitive colleges for which they are qualified. Then, shifting gears, he'll examine the ongoing debate over whether Asian American students are disadvantaged relative to white students when applying to Ivy League universities and similarly selective colleges. Finally, Professor Goel will discuss the dearth of low-income students at selective schools.
Sharad Goel, Professor of Public Policy, Harvard Kennedy School
Thursday, March 30, 2023
4:00 PM – 5:00 PM EST
In-person: Harvard SEC LL2.224
From racial profiling through facial recognition software used by law enforcement to algorithms that unfairly target Black and brown users with subpar services and subprime financial practices, biases in the way technology is developed and used are rampant and must be intercepted before they do further damage. The Metaverse – a new combination of emerging technologies including artificial intelligence (AI), extended reality (XR), and blockchain – will create a virtual world for various aspects of human life, from social connections to e-commerce. But will the same algorithmic biases of our current technology carry over to a virtual world? Drawing from his extensive research and fieldwork, Dr. Desmond Upton Patton, Penn Integrates Knowledge University Professor at the University of Pennsylvania, founder of SAFElab explains how data scientists, designers, and engineers can prevent bias in AI by collaborating with social science professionals who can help them become more aware of the unintended harms being built into technologies they develop. He also highlights the many ways organizations, developers, users, and society stand to benefit from such collaboration. This important presentation is geared toward organizations, professionals, and policymakers involved in the development and regulation of emerging technologies.
Speakers:
Desmond Upton Patton, PhD, MSW Brian and Randi Schwartz University Professor of Social Policy, Communications, and Medicine, University of Pennsylvania
Friday, April 14, 2023
10:30 AM – 3:00 PM EST Hybrid: Snyder Auditorium or Zoom
CAUSALab is excited to invite you to the 15th Kolokotrones Symposium at the Harvard T.H. Chan School of Public Health. CAUSALab’s partner for the 15th Kolokotrones Symposium, Smith Center for Outcomes Research at BIDMC, combines novel analytical approaches with deep clinical expertise to understand and improve outcomes for patients with cardiovascular disease worldwide and advance healthcare delivery. You can learn more about the Center here.
Thursday, April 20, 2023 5:00 PM – 6:00 PM EST Virtual: Zoom
The R software has a rich, dynamic and mature spatial ecosystem. Several R packages allow to leverage the power of major FOSS libraries (like GDAL, GEOS or PROJ) for spatial data management and {mapsf} takes advantage of this ecosystem to create thematic maps. It helps designing various cartographic representations and offers several functions to display layout elements improving the graphic presentation of maps. In this talk, we will present the thematic cartography package {mapsf} and a set of smaller packages dedicated to more specific map types. Spatial representations created with R are fully reproducible and we argue that they can reach the same visual quality level as those built with a classical mapping or GIS software.
Speaker:
Timothée Giraud, Spatial Data Science Engineer, French National Center for Scientific Research (CNRS)
Application Deadline: Friday, March 31, 2023, 5:00 PM PST
Delfina Care helps bridge the maternal health gap by standardizing access to quality care to enable better outcomes for families, while also reducing healthcare costs.
Delfina is looking for data scientists passionate about reproductive health to join the data science team! Data scientists will work in concert with our product, engineering, and clinical teams to implement machine learning models in clinical practice, evaluate the impact of Delfina Care, and conduct cutting-edge reproductive health research.
Responsibilities:
Develop machine learning models for various pregnancy-related outcomes.
Implement and evaluate our proprietary machine learning models in clinical practice.
Create data visualizations and dashboards to monitor implementation of Delfina Care.
Collaborate with academic partners to develop and execute research studies.
Support the development of manuscripts for publication and abstracts for academic conferences.
Requirements:
Current undergraduate, masters, or doctoral student in biostatistics, epidemiology, data science, computer science, or related field.
Available to work full-time for a 12-week internship (flexible start date).
Experience conducting statistical analyses using health data.
Familiarity with versioning and code collaboration with Git.
Proficiency in R, Python, or SQL.
Demonstrated interest in developing data science tools to improve pregnancy and postpartum care.
Sponsored by the Spatial Data Lab, this workshop is to promote replicable and expandable spatiotemporal data science with advanced methodology and technology. The workshop will discuss methodology, functions and workflow-based tools for spatiotemporal data analysis as well as case studies for their applications across different fields, including public health, business, social media, remote sensing, and environmental science. There will be a spatiotemporal innovation symposium at the end of the workshop with presentations by workshop participants on their research work. The workshop will offer an excellent opportunity for participants to network, collaborate, and further develop their domain knowledge and leadership skills.
Workshop Dates:
Monday, July 10 – Friday, July 14, 9:00 AM – 5:00 PM EST
Topics:
An Introduction to Workflow-Based Tools: KNIME Analytics Platform, KNIME Server and KNIME WebPortal
Open Data Access, Integration, Online Data Sharing and Visualization
Spatiotemporal Analysis with Geospatial Analytics for KNIME
Artificial Intelligence Analysis for Spatiotemporal Data
Workflow-based Remote Sensing Analysis
Business Intelligence Analysis with Spatiotemporal Data
Spatiotemporal Analysis with Social Media Data
Spatiotemporal Analysis with Healthcare Data
Introduction to Affiliate Labs on Spatiotemporal Innovation
Discussion on Future Collaborations
Registration Fee:
$2,980 registered/paid before May 1, 2023
$3,680 registered/paid after (including) May 1, 2023
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