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October 13, 2022
In this issue:
Astronomy + Data
Featured Event

Upcoming Events
Postdoctoral Fellowship Opportunity
Full-Time Opportunities
Engage + Connect
Dear Friends, 

The first Causal Seminar of the year, "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," takes place next week on Thursday, October 20 at 3:30 PM EST! We are thrilled to welcome Harvard Business School Assistant Professor Edward McFowland III as this seminar's speaker. Read about Professor McFowland and register now.

Thank you to everyone who registered for the HDSI Annual Conference 2022 Day 1 workshop and tutorial! Tickets are now sold out for Day 1, but we still have tickets available for the Day 2 Plenary Sessions, which will be co-hosted by the Digital, Data, and Design (D^3) Institute at HarvardReserve your tickets now.

This week we are celebrating data science in astronomy! Read, listen, watch, and learn about astronomy and space exploration research using the resources collected below.

All the best,

The Harvard Data Science Initiative
Read, Listen, Learn + Watch: Astronomy + Data
🔭 Read:
Nested dust shells around the Wolf–Rayet binary WR 140 observed with JWST
Nature Astronomy

The latest image from NASA‘s James Webb Space Telescope is a new perspective on the binary star Wolf-Rayet 140, revealing details and structure in a new light.
Study: Astronomers risk misinterpreting planetary signals in JWST data
MIT News Office

Refining current opacity models will be key to unearthing details of exoplanet properties — and signs of life — in data from the powerful new telescope.
A generalizable and accessible approach to machine learning with global satellite imagery
Nature Communications

Research team at University of California, Berkeley, which included 2022 HDSI Postdoctoral Fellow Esther Rolf, developed new system that uses machine learning to drive low-cost, easy-to-use technology that one person could run on a laptop, without advanced training, to address their local problems.
SpaceX: Enabling Space Exploration through Data and Analytics
D^3 Institute at Harvard

SpaceX has disrupted the space industry by making launches more accessible – data has been key to their success.
Machine learning scours the X-ray sky
Nature Italy

Astronomers in Milan have shown that AI can help classify high-energy sources, and even identify celestial objects that were previously overlooked by researchers.
An Exploratory Analysis on 7 Decades of Space Exploration Data
Towards Data Science

Insights and compelling stories from humanity’s first 7 decades in space
The latest developments in computer science and their impact on space exploration

Discussion of new possibilities and approaches to conducting research in the field of astronomy and astrophysics with the use of cloud computing and advanced data visualization techniques.
Killer Asteroids Are Hiding in Plain Sight. A New Tool Helps Spot Them.
The New York Times

Researchers have built an algorithm that can scan old astronomical images for unnoticed space rocks, helping to detect objects that could one day imperil Earth.
🪐 Listen:
NASA Webb’s First Full-Color Images, Data Are Set to Sound

A new, immersive way to explore the first full-color infrared images and data from NASA’s James Webb Space Telescope – through sound.
The Deep Learning Revolution in Space Science

Justin Fletcher joins the show to talk about how the US Space Force is using deep learning with telescope data to monitor satellites, potentially lethal space debris, and identify and prevent catastrophic collisions. 
🛰 Learn:
NASA's Data Portal

Catalog of publicly available NASA Datasets, APIs, visualizations, and more. Includes space science, aerospace, earth sciences, applied science, and management data.

Space industry worldwide - statistics & facts

The global space economy, valued at around 423.8 billion U.S. dollars in 2019, includes a range of activities involved in the researching, exploring, and utilization of space. 
Discover the role of Python in space exploration

This learning path introduces you to the world of Python, with the goal to understand how Python impacts NASA's innovative solutions.

How To Download The James Webb Space Telescope Data & Analyze It With Python

Learn about the connection between astronomy and data science and the programming languages to learn if you want to get into the field.
🚀 Watch:
Data from NASA’s Chandra X-ray Observatory and James Webb Space Telescope have been combined. These images are from some of the earliest observations made by Webb. Chandra had previously observed these objects in X-ray light. These composites demonstrate how these two telescopes can work together. Read more via Chandra X-ray Observatory
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
Tickets are sold out for the Harvard Data Science Initiative Conference Day 1 tutorial and workshop, but there are still tickets available for the Day 2 Plenary Sessions! Day 2 will be co-hosted by the Digital, Data, and Design Institute (D^3) at Harvard and we are delighted that Day 2's plenary sessions will take place in Harvard Business School's Klarman Hall.

Day 2 Plenary Sessions:
  • Panel 1: Communicating Data Science – Trust with complexity
  • Panel 2: Social Impact Computing – Building an emerging field
  • Panel 3: Agent-Based Modeling – Complex ecosystems in silico
  • Panel 4: Data Science and Climate – Connecting planetary and human health
This event is free and open to the public. Ticket required for admission. Please RSVP to reserve your spot.
Upcoming Events
From content moderation to school assignment: What do theories of justice teach us about design?
Monday, October 17, 2022
11:00 AM – 12:00 PM EST
Science and Engineering Complex, Harvard SEAS
HCRCS Social Impact Seminar Series: Niloufar Salehi, University of California, Berkeley
  • Niloufar Salehi, Assistant Professor, School of Information, University of California, Berkeley
The Harvard Center for Research on Computation and Society (HCRCS) Social Impact Seminar Series explores how artificial intelligence can equitably solve social problems.


Computational systems have a complex relationship with justice: they may be designed with the intent to promote justice, tasked to resolve injustices, or actively contribute to injustice itself. In this talk I will take two theories of justice, restorative and distributive justice, as frameworks to analyze and imagine alternatives to two real-world systems. Read more.
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
Thursday, October 20, 2022
3:30 PM – 5:30 PM EST
Hawes Hall, Classroom 203, Harvard Business School
HDSI Causal Seminar: Edward McFowland III, Harvard University
Edward McFowland III is an Assistant Professor in the Technology and Operations Management Unit at Harvard Business School. He teaches the first-year TOM course in the required curriculum. 

As a data and computational social scientist, Professor McFowland aims to bridge the gap between machine learning and the social sciences.
Read more.
  • Edward McFowland III, Assistant Professor, Technology and Operations Management Unit, Harvard Business School

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.
Optimal nonparametric estimation of heterogeneous
causal effects 
Thursday, November 3, 2022
3:30 PM – 5:30 PM EST
Hawes Hall, Classroom 203, Harvard Business School
HDSI Causal Seminar: Edward Kennedy, Carnegie Mellon
  • Edward Kennedy, Associate Professor of Statistics and Data Science, Carnegie Mellon University

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.
Symposium on Science, Technology, + the Human Future
November 3 – 5, 2022
Harvard University
Hosted by the Program on Science, Technology + Society at Harvard University in celebration of its 20th Anniversary
The Program on Science, Technology & Society is celebrating its 20th anniversary with a Symposium on Science, Technology and the Human Future, to be held at Harvard from November 3-5, 2022. This major event will feature a wide range of high profile speakers across political, academic, and broader society. 
The Symposium begins at 5pm on Thursday, November 3 with a keynote lecture by novelist Arundhati Roy, including performances of original music and fiction written by Harvard students. We continue on Friday with panels on the role of science and technology in shaping the human future, including the future of knowledge, life, policy, and cities. Saturday includes open discussions on how STS can position us to better understand and govern ourselves, our societies, and our Earth.
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,
  • Tammy Levy, Chief Games Officer,

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.
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.
Full-Time Job Opportunities
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Engage + Connect
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