Each year IDIES – The Institute for Data Intensive Engineering and Science offers its members and students funding opportunities through their Seed Funding Initiative and Summer Student Fellowships.
The goal of the Seed Funding initiative is to provide pilot funding for data-intensive computing projects that (a) will involve areas relevant to IDIES and JHU institutional research priorities; (b) are multidisciplinary; and (c) build ideas and teams with good prospects for successful proposals to attract external research support by leveraging IDIES intellectual and physical infrastructure.
IDIES is excited to support the following researchers and their work in 2021:
An Unsupervised Neural Framework for Multi-Modal Literary and Historical
PI: Thomas Lippincott (Computer Science)
Co-Is: Sharon Achinstein (English), Jacob Lauinger (Near Eastern Studies)
The Search for Elusive Progenitors of Type Ia Supernovae
PI: Nadia Zakamska (Physics and Astronomy)
Co-I: Tamás Budavári (Applied Mathematics and Statistics)
Real-Time Prediction of Long-term Cardiovascular Complications in COVID-19 Patients
Post Hospital Discharge
PI: Natalia Trayanova (Biomedical Engineering and Medicine)
Co-I: Allison Hayes (Cardiology)
Comprehensive Analysis of Public Sequencing Archives to Uncover Novel Mechanisms
of Pathogenesis in Amyotrophic Lateral Sclerosis
PI: Jonathan Ling (Pathology)
Co-I: Benjamin Langmead (Computer Science)
The IDIES Summer Student Fellowship supports summer research projects lead by undergraduate students with the guidance of an IDIES faculty member mentor. These projects are meant to provide an opportunity for students to participate in a 10-week (June – August) full-time data science focused research project in collaboration with an IDIES faculty member.
The 2021 student fellowship recipients are:
Faculty Mentor: Tinglong Dai, Kimia Ghobadi
Using Machine Learning to Predict Surgical Case Duration in Operating Room Scheduling
Chengkai (Tony) Tian
Faculty Mentor: Jian Ni
Optimizing Resource Distribution Based on Sales Price Data Through Machine Learning
Faculty Mentor: Jonathan Weiner, Chintan Pandya
Humanizing Our Data: Proposal on Integrating Social and Behavioral Determinants of
Health into Population Health Analytics
IDIES is a major interdisciplinary program, a large, diverse effort, where faculty and students work together to solve data-intensive problems, from genes to galaxies to materials science and urban planning. The IDIES funding programs seek to encourage new ideas and grow these efforts across the University, while giving JHU researchers and students the opportunity to expand their data science analysis and projects to the next level.