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WATER Summer School

June 24, 2024 June 28, 2024

W.A.T.E.R. — Hydrological Data Science Summer School

Workflow Automation and Techniques for Effective Research

Virtual | June 24–28, 2024 | 6–8 pm CT

Often, students overlook the profound shift that a PhD represents—it’s not a mere continuation of undergraduate or master’s studies, but the pivotal entry into a rigorous and transformative journey toward a professional career in academia and research. Consequently, they grapple with formidable challenges when confronted with the task of formulating hypotheses and venturing into the uncharted territory of seeking solutions! 

Organized by TAMIDS, the WATER Summer workshop aims to bring speakers specializing in various aspects of hydrology to share their work from a data analysis perspective, including sharing codes or notebooks. Given that students often struggle with obtaining and analyzing the right data for their research, this summer school will offer a unique opportunity for students to navigate through best practices of data collection, organization, and analysis methods in a hands-on workshop format. Participants will learn a good mix of “theoretical know-how” (how to formulate hypotheses) and “hands-on coding” (how to find the right data and how to analyze them) with hydrological and related environmental datasets. 


Organizing Team

  • Debasish Mishra, Data Science Student Ambassador, TAMIDS
  • Rishabh Prasad, Computer Science undergraduate student
  • Karan Bhalla, Computer Science undergraduate student

Presenters

June 24
Andrew Feldman, Assistant Research Scientist – NASA GSFC and Research Faculty (University of Maryland)

Tracking global vegetation responses to rainfall events

June 25
Danyka Byrnes, PhD Candidate at the University of Waterloo

Plotting Your Course with Effective Data Exploration

June 26
Tadd Bindas, PhD Candidate at Penn State University

How to Create a Differentiable Model

June 27
Toshiyuki Bandai, Postdoc Fellow at Lawrence Berkeley National Laboratory

Differentiable Modeling with Implicit Differentiation

June 28
Zhi Li, Postdoc Fellow at Standford Doerr School of Sustainability

Remote Sensing in Observing Hydrologic Water Cycle


Primary contact: Debasish Mishra, Data Science Student Ambassador (debmishra@tamu.edu)