jar filled with coins on a wooden deck with a plant growing out of it

Funding Opportunities

ICDS is no longer accepting proposals for its 2020 Seed Grant program. Awards will be announced at the ICDS Symposium on March 16 and 17.

If you have questions about the program, please refer to the ICDS Seed Grant FAQ. If your question has not been answered, please contact Guido Cervone, associate director of ICDS, at ics-seed-grants@ics.psu.edu.

To see what projects have been funded by ICDS in the past, view past seed grant recipients.


  • Projects can originate from tenured, tenure-track, or research faculty; however, either the PI or Co-PI must be a tenured or tenure-track faculty.
  • Recipients (either PI or Co-PI) of last year’s ICS Seed Grant are not eligible for funding under this solicitation.
  • Students and postdocs cannot serve as PIs or Co-PIs.


  • Up to $10,000 for awards to a single researcher
  • Up to $25,000 for awards that bring together two faculty members who engage in an interdisciplinary project
  • Up to $35,000 for awards whose PI is an ICDS Co-Hire or Associate faculty

Please refer to the competition webpage for additional budgetary information and restrictions.


  • Exascale Computing
  • Quantum Computing
  • High-Performance Computing and Numerical Simulations
  • Research on Cyberinfrastructure
  • AI/ML and Big Data Analytics
  • Data Assimilation
  • Data Visualization and Immersive Experience
  • Data Privacy and Law


Q: May I utilize seed grant funds to finance an international collaborator?
A: You may not allocate salary for visitors, but you may allocate travel funds up to the maximum allowed under the solicitation.

Q: May I utilize seed grant funds for an ICDS-ACI allocation (for example, access to GPU nodes)?
A: Yes, you are permitted to use seed grant $$ on ICDS-ACI computing resources.

Q: I’m a visiting professor. May I apply as a PI or Co-PI?
A: Unfortunately visiting professors are not eligible to be PIs or CoPIs, but they may be named in the proposal.

Q: Is there a limit to the number of investigators for an application?
A: There is a limit to two investigators, with a strong preference that they are at different ranks, such as a more senior investigator serving as a mentor for a more junior one.

Q: What ICDS affiliation is required to be eligible for the maximum grant ($35,000)?
A: The PI must be an ICDS Associate or Co-Hire.

Q: I am a research faculty, and I wish to apply as a lone PI.  Can I do that?
A: Please contact Dr. Guido Cervone at ics-seed-grants@ics.psu.edu.

Q: We are a group of two research faculty and wish to apply together as a PI – CoPI team. Can we do that?
A: Please contact Dr. Guido Cervone at ics-seed-grants@ics.psu.edu.

Q: Are there formatting requirements for the proposal in addition to what is specified in InfoReady?
A: No.  The only restrictions include number of pages, font size, spacing and margins.

Q: Can we use funds to purchase data and services?
A: Yes, as long as the funds are used in line with all applicable policies of Penn State and/or the PI’s college/unit. Please check with your unit’s financial officer if you are unsure of how the funds can be spent. 

Q: What are the review criteria for seed grants?
A: The criteria are:

  • Fit with the topics of the RFP
  • Scientific merit
  • Probability of success
  • Project sustainability (external funds)
  • Team expertise and makeup
  • Budget realism

Past Seed Grants Funded


  • Machine Learning and the Preservation of Cultural Heritage on Madagascar (PI: Kristina Douglass)
  • 2019 Complex Adaptive Systems Conference (PI: Nil Ergin)
  • Traffic signal control using reinforcement learning (PI: Vikash Varun Gayah)
  • BehAV: A computational framework for the automated analysis of human behavior and physiology from video (PI: Rick Gilmore)
  • Mathematics and Applications of Machine Learning (PI: John Harlim)
  • Leveraging AI for Game-Theoretic Models of Judicial Decision Making (PI: Ben Johnson)
  • Datafication of Human Behavior Through Immersive Technologies – xR / AI Analytics for Advancing the Human-Technology Frontier (PI: Alex Klippel)
  • Improving the Effectiveness of Team Peer Evaluations using Artificial Intelligence (PI: Abdullah Konak)
  • Using AI to Improve Youth Employment in Morocco and Beyond (PI: Dongwon Lee)
  • Improving Success Rate of Atrial Fibrillation Surgeries via Reinforcement Learning (PI: Eunhye Song)
  • AI for Identifying and Optimizing Interactions Between Transit Systems (PI: Elizabeth Traut)
  • Show Me or Tell Me: Robots that Learn Games from People (PI: Alan Wagner)
  • Numerical Modeling of Volcanic Flank Instability and Failure Forecasting using Machine Learning (PI: Christelle Wauthier)
  • Towards Accountable Decision-making in Cybersecurity via Explainable Machine Learning (PI: Xinyu Xing)
  • Deep Learning for CALPHAD Database Development and Uncertainty Quantification (PI: Jinchao Xu)
  • The Study and Simulation of the Mechanisms Driving Species Migration (PI: Katherine Zipp)


  • Individual-level brain parcellation using an integrative multi-network clustering approach (PI: Xiao Liu)
  • Harvesting Data and Models for Water Forecasting (PI: Li Li)
  • Predicting Relapse Onset in Bipolar Disorder from Online Behavioral Data (PI: Saeed Abdullah)
  • 2018 Astroinformatics Summer School (PI: G. Jogesh Babu)
  • Theoretical Study of Novel Dielectric Nanocomposites (PI: Adrianus Van Duin)
  • Combined experimental and multi-scale simulation investigation on binder jetting (PI: Guhaprasanna Manogharan)
  • Predictive Personalized Public Health (P3H): A Novel Paradigm to Treat Infectious Disease (PI: Steven Schiff)
  • The Generalizability and Replicability of Twitter Data for Population Research (PI: Guangqing Chi)
  • Fair Crowds: User-Centered Algorithms for Equitable Distribution of Work (PI: Benjamin Hanrahan)
  • Learning and Modeling of Fracture Mechanisms of Carbon Fiber Reinforced Polymer Composites from Spatiotemporal Image Data (PI: Jingjing Li)
  • A computational approach to predicting well-being through environmental, social, and physical measurement (PI: Catherine Mello)
  • Countrywide Rodent Densities In A Snap (PI: Kurt Vandegrift)
  • Coupled Statistical and Dynamical Models to Project Changing Risk of Extreme Floods due to Climate Change and Urbanization (PI: Ben Shaby)
  • Deep Learning for Astronomical Image Processing (PI: Derek Fox)
  • SETI@PSU: Partnering with the $100 million Breakthrough Listen Initiative (PI: Jason Wright)
  • Deep Learning and Parallel Computing to Accelerate Large-scale Simulation Modeling of Spatiotemporal Cardiac Systems (PI: Hui Yang)
  • Distributed Visual Perception for Urban Autonomous Driving (PI: Zihan Zhou)
  • Theory of fractional viscoelastic wave propagation and its efficient solver for processing ‘Large-N’ seismic data (PI: Tieyuan Zhu)