Events

The Massive Data Institute (MDI) invites you to take part in our Data Workshop series this spring. Please RSVP to any of the events that you are interested in attending.
 

Tea Time: Social Media Data in Social Science Research
Date and Time: Friday, March 22 from 3:00pm - 4:00pm
Location: Healy G-02, Massive Data Institute Suite, Healy Hall
Description: Listen and share research ideas and projects. Join a community of scholars working on massive data issues and questions. Lisa Singh, Leticia Bode, and Rebecca Ryan aim to discuss how to apply aggregated social media data to social science projects. Please note: The discussion is open to faculty, researchers, and postdocs. Thank you in advance for your understanding. 

Tea Time: Data Quality and Ethical Sourcing
Date and Time: Friday, March 29 from 3:00pm - 4:00pm
Location: Healy G-02, Massive Data Institute Suite, Healy Hall
Description: Listen and share research ideas and projects. Join a community of scholars working on massive data issues and questions. Amy O'Hara, Director of the Research Data Center and Research Professor at MDI, will lead a discussion on ethical data collection and usage. Please note: The discussion is open to faculty, researchers, and postdocs. Thank you in advance for your understanding. 

Tea Time: Foreign Investment and International Trade
Date and Time: Friday, April 5 from 3:00pm - 4:00pm
Location: Healy G-02, Massive Data Institute Suite, Healy Hall
Description: Listen and share research ideas and projects. Join a community of scholars working on massive data issues and questions. This discussion on international trade will be led by Brian Jensen, the McCrane/Shaker Chair in International Business. Please note: The discussion is open to faculty, researchers, and postdocs. Thank you in advance for your understanding. 

Tea Time: AI in Healthcare
Date and Time: Friday, April 12 from 3:00pm - 4:00pm
Location: Healy G-02, Massive Data Institute Suite, Healy Hall
Description: Listen and share research ideas and projects. Join a community of scholars working on massive data issues and questions. In this tea time, Professor Subha Madhavan will discuss the impact of AI in the healthcare industry. Please note: The discussion is open to faculty, researchers, and postdocs. Thank you in advance for your understanding. 

Mapping Infrastructure Categories from GIS Satellite imagery
Date and Time: Monday, April 15 from 10:00am - 12:00pm
Location: Arrupe Multipurpose Room, Arrupe Hall
RSVP Link: https://gissatelliteimagery.eventbrite.com 
Description: With increasing urbanization in many developing countries, understanding the evolution and spatial characteristics of informal settlements will be critical for both poverty targeting efforts and the provision of public services.
This workshop will provide practical tools and instructions for mapping informal settlements with satellite imagery using the open source geographic information systems application QGIS. It will introduce attendees to vector and raster layers, ways to create and import vector shapefiles, and methods for accessing online satellite imagery by drawing on research on Indian government-designated categories of unplanned settlements that can be easily identified using remote sensing imagery. No prior experience in GIS mapping is required.

Classifying Infrastructures within Satellite Imagery with Machine Learning
Date and Time: Friday, April 16 from 10:00am - 12:00pm
Location: Arrupe Multipurpose Room, Arrupe Hall
RSVP Link: https://gissatelliteimagery.eventbrite.com
Description: The explosion of satellite imagery and recent developments in machine learning create unprecedented opportunities to harness remote sensing for sustainable development and humanitarian efforts. This workshop will provide a practical introduction to machine learning for computer vision on remote sensing imagery using Python and the PyTorch deep learning framework. The workshop will begin with an introduction to remote sensing imagery, including data sources and different forms of resolution (e.g., spatial, temporal, radiometric, spectral). Given satellite imagery and map shapefiles with appropriately labeled polygons, the session will demonstrate how to preprocess the imagery, including rasterizing polygons, tiling rasters into image chips, and image resizing and augmentation. Next, the workshop will describe the machine learning workflow, with a focus on defining training and validation sets, classifying imagery with a neural network in PyTorch, and assessing accuracy of the classifier on the validation set. Python code will be provided in Jupyter notebooks for attendees to follow exercises and adapt for their own projects.

Tea Time: Algorithms for Real-Time Analysis of Massive Data
Date and Time: Friday, April 26 from 3:00pm - 4:00pm
Location: Healy G-02, Massive Data Institute Suite, Healy Hall
Description: Listen and share research ideas and projects. Join a community of scholars working on massive data issues and questions. In this discussion, Professor Justin Thaler of the Computer Science department will discuss his research. Please note: The discussion is open to faculty, researchers, and postdocs. Thank you in advance for your understanding. 

 

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