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September 29, 2022
In this issue:
Latest HDSR Podcast Episode
Read, Listen, + Watch
Featured Event
Upcoming Events
Postdoctoral Fellowship Opportunity

Full-Time Opportunities
Reserve your tickets now for the HDSI Annual Conference 2022!
Dear Friends, 

Tickets are selling fast for the HDSI Annual Conference 2022! Visit the conference website to view our confirmed speakers and reserve your spot for the tutorial, workshop, and plenary sessions. This event is free and open to the public!

Listen to the latest Harvard Data Science Review Podcast to learn about personalized treatments and what the data science can tell us about these types of clinical trials.


Apply now for the 2023-2024 Harvard Data Science Initiative Postdoctoral Fellows Program! Submit by November 11, 2022.

All the best,

The Harvard Data Science Initiative
Latest HDSR Podcast Episode
Personalized Treatments: Is That Possible and What Can Data Science Tell Us?
Episode 21 of the Harvard Data Science Review Podcast
Today we discuss the most important element of our lives: our health. We do so by diving into personalized medicine, or more specifically, personalized (N-of-1) trials—clinical trials in which a single patient is the entire trial. For this episode, we invited two editors of Harvard Data Science Review’s special issue on N-of-1 trials and data science to help us examine all aspects of these clinical trials designed for a population of one person.
 
Episode Guests:
  • Dr. Karina Davidson, Senior Vice President of Research and Dean of Academic Affairs at Northwell Health
  • Ken Cheung, Professor of Biostatistics at Mailman School of Public Health at Columbia University
LISTEN NOW
Read, Listen, + Watch
📖 HDSI Sponsors First Harvard Data + Society Summer Book Club

This past summer, the Harvard Data Science Initiative (HDSI) sponsored Harvard’s first “Data and Society Summer Book Club.” The Book Club was organized by Dr. Kelly McConville, senior lecturer in the Department of Statistics at Harvard University, to create a space for Harvard affiliates to connect regularly and discuss ideas related to data science and society.
🎧 Data analysis and intelligent policy design—not good intentions—will fix health care post COVID

HKS professors Amitabh Chandra and Soroush Saghafian (HDSI Faculty Affiliate) say we need data analysis and smart policy design to create transformational change in health care; without them even well-intentioned measures like the Inflation Reduction Act are destined to fall short.
🎥 Precision Medicine Annual Conference 2022: The New “Normal”?

Watch the livestream of the 8th annual Precision Medicine conference by the Department of Biomedical Informatics (DBMI) in the Blavatnik Institute at Harvard Medical School, which focused on genetic testing as thorny and long-standing challenges emerge anew. Featuring HDSI Faculty Affiliate Isaac Kohane.
Featured Event
Harvard Data Science Initiative Annual Conference 2022
Tuesday, November 15
9:00 AM – 5:00 PM EST

Science + Engineering Complex, Harvard SEAS
Wednesday, November 16, 2022
8:00 AM – 6:30 PM EST

Klarman Hall,
Harvard Business School
Two days of in-person workshops, tutorials, + plenary sessions
The Harvard Data Science Initiative Conference is a two-day event in Boston, MA that showcases data science in research and education through panels, keynotes, workshops, and tutorials featuring speakers from across Harvard, academia, and industry.
 
The Conference connects expert methodologists, data science professionals and educators across disciplines to ignite new discoveries with impacts on health, education, economics, social policy, business and the humanities.


This event is free and open to the public. Ticket required for admission. Please RSVP to reserve your spot.
REGISTER NOW
Upcoming Events
Level Up Your Plots
Thursday, September 29, 2022
5:00 PM EST
Virtual (Zoom)
Hosted by the R User Group (RUG): Tips and tricks to enhance the storytelling capabilities of your data visualizations
Polished annotations can make all the difference between a good plot that contains all the necessary information, and a great plot that engages readers with a clear story.

This talk with freelance data consultant Cara Thompson will build on the Introduction to ggplot session, exploring how we can make good use of design tips (and the coding tricks behind!) to help readers understand the key messages that our datavisualisations seek to convey. 
REGISTER NOW
AI and Social Impact in South Asia
Tuesday, October 4, 2022
10:00 AM EST
Virtual (Zoom)
Co-sponsored by the Center for Research on Computation and Society and the Lakshmi Mittal and Family South Asia Institute: Miniseries Part One
Panelists:
  • Tanuja Ganu, Principal Research SDE Manager, Microsoft Research
  • Shalmali Joshi, CRCS Postdoctoral Fellow, Harvard University
  • Shama Karkal, CEO, Swasti Health Catalyst
Moderator:
  • Professor Rem Koning, Harvard Business School 

This miniseries explores how AI technology becomes an integral part of South Asian society and considers the potential opportunities and concerns of its proliferation.

The first panel in this miniseries will explore the social impact of AI in the region. As AI is used to address social, environmental, and economic challenges in the region, how will practitioners aim to improve the lives of people and their communities while also evaluating the impact of their work?

REGISTER NOW
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
Thursday, October 20, 2022
3:30 AM – 5:30 PM EST
Hawes Hall, Classroom 203, Harvard Business School
HDSI Causal Seminar: Edward McFowland III, Harvard University
Speaker:
  • Edward McFowland III, Assistant Professor, Technology and Operations Management Unit, Harvard Business School
Abstract:

Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy uses predictive modeling techniques to "mine" variables of interest from available data, then includes those variables into an econometric framework to estimate causal effects. However, because the predictions from machine learning models are inevitably imperfect, econometric analyses based on the predicted variables likely suffer from bias due to measurement error. Read more.
REGISTER NOW
Optimal nonparametric estimation of heterogeneous
causal effects 
Thursday, November 3, 2022
3:30 AM – 5:30 PM EST
Hawes Hall, Classroom 203, Harvard Business School
HDSI Causal Seminar: Edward Kennedy, Carnegie Mellon
Speaker:
  • Edward Kennedy, Associate Professor of Statistics and Data Science, Carnegie Mellon University
Abstract:

Estimation of heterogeneous causal effects -- i.e., how effects of policies and treatments vary across units -- is fundamental to medical, social, and other sciences, and plays a crucial role in optimal treatment allocation, generalizability, subgroup effects, and more. Many methods for estimating conditional average treatment effects (CATEs) have been proposed in recent years, but there have remained important theoretical gaps in understanding if and when such methods make optimally efficient use of the data at hand. This is especially true when the CATE has nontrivial structure (e.g., smoothness or sparsity). Read more.
REGISTER NOW
Data and Economic Principles in Video Games
Thursday, November 10, 2022
1:30 PM – 2:30 PM EST
Virtual (Zoom)
HDSI Industry Seminar: Tammy Levy, Captain.tv
Speaker:
  • Tammy Levy, Chief Games Officer, Captain.tv
Abstract:

Underneath the fun of games we can find complex economies. In the last 15 years, with the rise of accessible broadband internet, video game developers have been able to regularly release game updates or "patches" through a process called live servicing. In addition to new content, game designers often add, remove, and rebalance the resources in the game– effectively manipulating the game's economy on a regular basis. In this talk, I will cover the basic principles of game economies and the core business KPIs used to monitor a game's performance. Then I'll walk through real examples behind the data-driven decisions for game optimization.
REGISTER NOW
Postdoctoral Fellowship Opportunity
Harvard Data Science Initiative Postdoctoral Fellowship Program 
Deadline: Monday, November 14th, 11:59 PM EST
The Harvard University Data Science Initiative is seeking applications for its Harvard Data Science Initiative Postdoctoral Fellows Program for the 2023-2024 academic year. The normal duration of the Fellowship is two years. Fellows will receive a generous salary as well as an annual allocation for research and travel expenses. 

We are looking for researchers whose interests are in data science, broadly construed, and including researchers with a primarily methodological focus as well as researchers who advance both methodology and application. Fellows will be provided with the opportunity to pursue their research agenda in an intellectually vibrant environment with ample mentorship. We are looking for independent researchers who will seek out collaborations with other fellows and with faculty across all schools of Harvard University.

We recognize that strength comes through diversity and actively seek and welcome people with diverse backgrounds, experiences, and identities.
APPLY NOW
Full-Time Opportunities
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