Learn how the NSF CSGrad4US Fellowship supports early-career professionals pursuing a computing PhD. Join our live informational webinar on Wednesday, April 16, from 3:00–4:00 PM ET to hear from program leaders, ask questions, and explore how mentorship and NSF funding can support your return to academia.
Fellowship Applications: The 2025 application period for the NSF CSGrad4US Fellowship is now open. Applications close at 11:59 PM ET on May 31, 2025.
The NSF CSGrad4US Mentoring Program supports and mentors recipients of the NSF CSGrad4US Graduate Fellowships returning to graduate school for a PhD in computing.
The objective of the Computer and Information Science and Engineering (CISE) Graduate Fellowships (NSF CSGrad4US) is to increase the number of domestic graduate students pursuing research and innovation careers in the CISE fields: computer science, computer engineering, or information science.
The goals of the NSF CSGrad4US Mentoring Program are:
Specific topics include the admissions process, preparation of all components of a strong graduate application, differences between graduate programs at different institutions, how to compare programs with respect to the Fellow’s goals and background, and general guidelines on making a selection among admission acceptances.
The NSF CSGrad4US Mentoring Program will provide not only general graduate application advice and guidance, but also provide a missing larger context and network to students returning from the workforce. These goals are achieved through group mentoring sessions followed by individual coaching during the application and decision-making process and the first year in graduate school.
This material is based upon work supported by the National Science Foundation under Grant Numbers (2123180, 2231962, and 2313998). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Read the NSF CSGrad4US 2024 Annual Evaluation Report here: 2024.07.02 Evaluation Report Year 1 CRA CSGrad4US
Available Formats: PDF
Document Type: Program Announcements & Information.
Document Number: nsf23136
Public Comment:
Document History: Posted: August 16, 2023.
The Computing Research Association, in partnership with the National Science Foundation, is proud to announce the recipients of the NSF Computer and Information Science and Engineering Graduate Fellowship Program (NSF CSGrad4US). NSF CSGrad4US aims to increase the number of domestic graduate students pursuing research and innovation careers in computer and information science and engineering fields. Each year, a cohort of NSF CSGrad4US fellows is selected based on their demonstrated interest and potential in pursuing a doctorate in a CISE field. There are currently 116 NSF CSGrad4US Fellows enrolled in 57 institutions across the United States. Below, our Fellows have provided some information about themselves, their interests, and their research goals.
Max Aalto, Massachusetts Institute of Technology
Electrical Engineering and Computer Science — Materials Design
Giri Anantharaman, Carnegie Mellon University
Computer Science — Robotics
Samantha Archer, Stanford University
Electrical Engineering — Computer Architecture
Marcus Arnett, Kent State University
Computer Science — CS
David Atkinson, Northeastern University
Computer Science — Interpreting Deep Learning Models
Alexander Bandukwala, University of Michigan
Computer Science and Engineering — Programming Languages
Oliver Bentham, University of Utah
Kahlert School of Computing — Natural Language Processing
Alexander Bock, Rice University
Department of Computer Science — Computational Biology
Sarah Boelter, University of Minnesota
Computer Science and Engineering — AI and Robotics
Eric Bond, University of Michigan
Computer Science and Engineering — Programming Languages (Type Theory)
Toby Baratta, University of California Irvine
Information Science — IS
Eli Bronstein, University of California Berkeley
Computer Science — CS
Forrest Bucklew, Mississippi State University
Computer Science — Human Computer Interaction
Ilan Buzzetti, UT Dallas
Computer Science — Formal Methods
Alyssa Cantu, Rice University
Computer Science — Computational Biology
Miguel Angel Chapa, Arizona State University
Computer Engineering (Electrical Engineering) — Nano-scale electronics, sensors, and devices, computer engineering
Izzy Chaiken, University of Washington
Information School — IS
Peter Chang, MIT
EECS — Deep Learning, AI for Science
Miguel Chapa, Arizona State University
Computer Engineering — ECE
Jiahui Chen, University of Texas Austin
Electrical and Computer Engineering — AI
Andy Chung, University of Michigan
CSE — Machine Learning
Geofrrey Churchill, SUNY at Stony Brook
Computer Science — CS
Allee Clark, Howard University
Electrical Engineering and Computer Science — Affective Computing
Stephen Crawford, Brown University
Computer Science — Robotics
Zach Cutler, University of Utah
Computer Science — Data Visualization
Jeremy Davis, University of California Santa Cruz
Computer Science and Engineering— CSE
Tonya Davis, Purdue University
Computer Information Technology — Computer Science Education
Melissa Dutz, Toyota Technological Institute at Chicago
Computer Science — Algorithms
Yara El-Tawil, University of Michigan
CSE — Speech, AI, Health, and HCI
Eduardo Escoto, University of California, San Diego
Computer Science — Machine Learning, AI
Jordan Esiason, North Carolina State University
Computer Science — Machine Learning/AI
Ekaterina Fedorova, University of Pennsylvania
Computer and Information Science — Algorithmic Game Theory, Incentive-Aware ML, Strategic Classification
Evan Frenklak, University of Texas at Austin
Electrical and Computer Engineering — Computational/Medical Imaging
Samsara Foubert, Carnegie Mellon University
Computer Science — CS
Kate Glazko, University of Washington
Computer Science — HCI
Steven Golob, University of Washington Tacoma
School of Engineering and Technology — Privacy-preserving machine learning, fair AI, differential privacy
Alfredo Gomez, Carnegie Mellon University
Language Technologies Institute — Natural Language Processing
Erica Goodwin, University of Chicago
Computer Science — Computer Science Education
Tim Goodwin, UC Santa Cruz
Computer Science — Distributed Systems and Programming Languages
Swati Govindaraju, University of Wisconsin-Madison
Computer Science — CS
Daniel Grzenda, University of Chicago
Computer Science — Systems, Machine Learning
Michael Hajostek, University of North Dakota
Computer Science
Seungwook Han, MIT
EECS — Generative Modeling, Foundation Models, LLM Alignment
Demetrius Hernandez, University of Notre Dame
Computer Science and Engineering — Cyber-Physical Systems and Assured Autonomy
David Hill, George Washington University
School of Engineering and Applied Sciences — Federated Machine Learning
Stella Holbrook, New York University Tandon School of Engineering
Computer Science — Big Data
Autumn Johnson, University of California Berkeley
Computer Science — CS
Raida Karim, University of Southern California
Computer Science — CS
Justin Kay, MIT
EECS — Computer vision, machine learning, sustainability
Eric Kapitanski, University of Southern California
Computer Science — Cybersecurity
Kei Kebreau, City University of New York
Computer Science — Virtual Reality and Visualization
Alexander Krentsel, UC Berkeley
EECS — Networked Systems
Yulia Kumar, Rutgers University
Electrical and Computer Engineering — Distributed Machine Learning, Models Quantization
Mora Labisi, Northwestern University
Computer Science & Learning Sciences — Computer Science Education, Software Engineering Education
Leah Lackey, Cornell University
Electrical & Computer Engineering — Robotics
Vihan Lakshman, Massachusetts Institute of Technology
EECS — Machine Learning and Systems
Medina Lamkin, University of Washington
Paul G Allen School of Computer Science and Engineering — Data Visualization
Ashton Larkin, University of Washington
Computer Science — Robotics
Robin Linzmayer, Columbia University
Computer Science — CS
Yucen Lily Li, NYU
Computer Science — Machine Learning
Travis Lloyd, Cornell University
Information Science — Social Computing & Computational Social Science
Cade Lueker, CU Boulder
Computer Science — Programming Languages
Nina Lutz, University of Washington
Human Centered Design Engineering Department — CSCW, HCI, Sociotechnical Systems, Computational Photography, Mis/Disinfo, Online Harm, Visual Media
Ian Magnusson, University of Washington
CSE — Language Models
Evanjelin Mahmoodi, University of California Los Angeles
Computer Science — Computational Biology
Joseph Majesky, University of Massachusetts Amherst
Computer Science — CS
Jessica Medina, Drexel University
Information Science — HCI
Antero Mejr, Tufts University
Computer Science — Formal Methods
Daniel Meyer, Columbia University
Computer Science — Computational Biology
Andres Meza, UC San Diego
Computer Science and Engineering — Hardware Security
Micah Morgan, University of Maryland
College of Information — HCI, Quantum Computation, and Health Information
Sarah Mundy, Columbia University
Computer Science — Malware in Quantum Computing
Natalie Neamtu, University of Washington
Computer Science and Engineering— CSE
Matt Nicholson, University of Colorado Boulder
Information Science — Social Computing
Daniel Ojeda, Rutgers University
Computer Science — CS
Krista Opsahl-Ong, Stanford University
Computer Science — CS
Kevin Ouyang, Northwestern University
Computer Science — CS
Juan Padilla, University of Puerto Rico
Computer Science and Engineering — Geolocation Management for AI and Autonomous Applications
Elleen Pan, University of Chicago
Computer Science — CS
Samyak Parajuli, The University of Texas at Austin
Electrical and Computer Engineering — AI
Jeff Pflueger, Northeastern University
Computer Science — Robotics and AI
Caspar Popova, University of Maryland at College Park
Computer Science — CS
Amy Pu, Columbia University
Computer Science — CS
Grace Quaintance, Cleveland State University
Electrical & Computer Engineering — Computer Engineering – Open-RAN/NextG and Satellite Communications, Controls
Gabriella “Nikki” Ramirez, Virginia Tech
Computer Science — Dark Patterns and User Security and Privacy in Virtual Reality
Harine Ravichandiran, University of Washington
Computer Science — Robotics
Jay Rodolitz, Northeastern University
Khoury College of Computer Sciences — CS
Jamie Rosas-Smith, Johns Hopkins University
Computer Science — NLP and Speech Processing
Parya Roustaee, University of California Irvine
Computer Science — CS
Ryan Rubel, University of Southern California
Thomas Lord Department of Computer Science — Robotics, Machine Vision
Pravina Samaratunga, Boston University
Electrical and Computer Engineering — CE
Daniel Sainati, University of Pennsylvania
Computer and Information Science — Programming Language
Madelyn Shapiro, University of California Santa Barbara
Computer Science — CS
Hrishee Shastri, University of Chicago
Computer Science – Data, Data Science, Data Management
Eden Shaveet, Cornell University
Information Science — Multimodal Information
Filipp Shelobolin, Columbia University
Computer Science — Fairness & Explainability
Di Yang (Steven) Shi, The University of Texas at Austin
Computer Science — Robotics
Ashley Shin, University of California, San Diego
Computer Science and Engineering — Machine Learning
Kaleen Shrestha, University of Southern California
Computer Science — Human-Robot/Computer Interaction
Shani Spivak, Northeastern University
Khoury College of Computer Science — AI ethics and governance, Vis x ML
Shalini Sushri, Georgia Tech
Computer Science — AI/ML
Arghamitra Talukder, Columbia University
Computer Science — Computational Biology
Ian Michael Terry, UC Santa Cruz
Computer Science and Engineering — Computational Ecology
Kushal Tirumala, Stanford University
Computer Science — CS
Patrick Jose Toral, University of Southern California
Viterbi School of Engineering — Machine Learning for Healthcare
David M Torres-Mendoza, UC: Santa Cruz
Computer Science & Engineering — Data Science
Bernardo Trindade, George Washington University
Electrical and Computer Engineering — Cybersecurity
Bryan Wallace, Georgia Institute of Technology
Human Centered Computing — CS and AI Education
Kevin A. Wang, Brown University
Computer Science — Computational Game Theory (AI / ML / Game Theory)
Matthew West, University of Chicago
Computer Science — Systems
Anthony Wise, University of Washington
Computer Science and Engineering — Security and Privacy/Visualization
Caleb Wohn, Virginia Tech
Computer Science — CS
Alexander Xiong, University of California Berkeley
Electrical Engineering and Computer Science — EECS
Claire Yang, University of Washington
Computer Science and Engineering — Human-Robot Interaction, Computational Cognitive Science
Lirong Yuan, CMU
S3D — Software Engineering, Programming Languages, Systems, and Security
NSF CSGrad4US Fellowship applicants are strongly advised to read the entire DCL carefully to ensure that they understand all the requirements. NSF CSGrad4US Fellowship applicants must self-certify that they intend to pursue a research-based doctoral degree in an eligible field of study and that they meet all eligibility criteria.
To be eligible for the NSF CSGrad4US Fellowship program for the current application year, applicants MUST:
Individuals are not eligible to apply if they propose to enroll in a discipline outside of CISE.
Individuals who are enrolled, or will enroll, in a graduate degree program while on a leave of absence from a professional degree program or professional degree-graduate degree program are ineligible for an NSF CSGrad4US Fellowship.
To receive the NSF CSGrad4US Fellowship, individuals must participate in the NSF CSGrad4US Mentoring Program. For more information about the mentoring program and the preparation for CISE doctoral programs, please refer to the Mentoring Program webpage https://cra.org/cra-wp/cs-grad4us/#Guidance.
This page provides guidance on what PhD programs are generally recognized to be CISE PhD programs and it provides insight into the background CISE PhD programs expect from their incoming PhD students. We align our descriptions with CISE’s mission which states “The NSF CISE Directorate supports research and education projects that develop new knowledge in all aspects of computing, communications, and information science.”
Expected background varies somewhat from program to program and the summary given below addresses the most common admission expectations. They include,
Research is the process of extending human knowledge beyond what is currently known. When we conduct research, we explore open problems, create a hypothesis for what we expect to observe, and then use techniques and tools developed for rigorous scientific study to test and evaluate our hypothesis for its validity. We write technical papers describing our research and then share our findings with experts in the field for critical assessment and feedback to further advance the research. This peer-review process is a key component of research as it can improve individual research and encourages continued exploration. Because not every hypothesis turns out to be correct, all research includes what appears to be failures or setbacks. While not being successful is generally frustrating, it often provides valuable information and insight that leads to ultimate success.
A Ph.D. is an in-depth research exploration of one topic that typically spans 5 to 6 years and produces new knowledge advancing the field. Pursuing a Ph.D. is a full-time endeavor with an emphasis on research, not on classes. At the time of graduation, the student will be an expert in the chosen field. Parallel to pursuing research, a student will take classes, either required or elective courses to gain the foundational knowledge needed in their research. Ph.D. students in CISE fields typically pay no tuition and receive a stipend, typically in the form of a fellowship, research assistantship, or teaching assistantship. Having a fellowship or research assistantship allows a student to dedicate fully to their research. Teaching assistants devote 20 hours per week to course-related activities like running lab sessions, holding office hours, and grading.
The expectation is that during the academic year, a student’s primary focus will be working full-time on research. This includes developing and refining research skills, discovering and learning new tools and techniques used in research, developing excellent communication skills, reviewing research done by others, conducting research experiments, preparing manuscripts for publication, and meeting all program requirements. As students start new research projects and their research skills grow, they work on more challenging problems and create more innovative solutions. Additionally, Ph.D. students pursue a range of professional development opportunities, including paid internships, participating in workshops, and attending conferences. They also become active members of the larger research community, learning how to communicate their ideas and critically assess and provide feedback on other researchers’ work. All these learning experiences expand their future career choices and prepare them for successful research careers.
Ph.D. program requirements vary across schools and departments. Specialized programs, such as interdisciplinary programs, may be distinctive in their requirements. Despite this variation, many CS/CE/IS programs have similar milestones and timelines.
Year 1:
During the first year, most Ph.D. programs require students to complete a core set of courses that provide them with foundational knowledge as well as knowledge in their chosen research area. Students are also expected to start working with a faculty advisor on an initial research project and become an engaged member of that faculty member’s research group.
Year 2:
During the second year, students will have completed the majority of their required coursework. Many Ph.D. programs require students to have completed qualifying requirements that demonstrate in-depth and breadth of knowledge. Qualifying requirements can take on different forms. In some programs, completing a set of courses is required. Alternatively, students may be required to complete oral or written examinations in multiple areas. Other programs assign students several research papers and require students to write and present a paper that summarizes, compares, and contrasts the results in those papers. Another approach is for students to present and defend the results of an initial research project. In addition to meeting these programmatic requirements, Ph.D. candidates are expected to have identified what research area they want to pursue, although they often will not have decided on the exact question(s) their doctoral thesis will explore and answer.
Years 3-4:
By the third and fourth years, students are expected to be actively conducting research in their research area. This includes publishing or preparing to publish preliminary results in peer-reviewed venues (i.e., conferences and journals). Based on the knowledge gained, Ph.D. candidates are expected to formulate a research plan for completing their thesis, including what research questions they expect to study and to begin writing their thesis proposals. Students are expected to continue doing research and publishing research results. Students should also start exploring future research career goals and make, jointly with the adviser, strategic decisions on how to best prepare. This can include internships with a particular focus, independently teaching a course, being a visiting student at another institution, and attending career mentoring workshops.
Remaining Years:
During the remaining years of a Ph.D. program, a student will continue to work on research problems, publish new research results, prepare conference presentations, revise submitted papers, and may start serving as a mentor for more junior students. They will participate in the larger research community, learning how to communicate their ideas and critically assess and provide feedback on other researchers’ work. This community engagement takes many exciting forms, including peer-reviewing papers on cutting-edge research and traveling to international conferences to present research and vigorously debate and be motivated by the work presented by others. Throughout this process, students are constantly learning from and collaborating with experts, honing their skills and knowledge until they become independently-capable experts in their own rights.
In parallel, they will write up their overall research contributions in the form of their dissertation, receiving and updating it with critical feedback from their dissertation committee members, and defend that research at a public presentation of their work. Their Ph.D. is complete once their dissertation committee is satisfied with the written work and oral presentation. The Ph.D. candidate will also be pursuing chosen job opportunities, preparing application materials, and finally interviewing for jobs. At this point, a student is fully prepared to embark on their independent research career.
Our intention is to recruit a set of coaches that is representative of the computing research community.
The CSGrad4US group mentoring focuses on the admissions process, preparation of all components of a strong graduate application, differences between graduate programs at different institutions and how to compare them with respect to the Fellow’s goals and background, and general guidelines on making a selection among admission acceptances.
Timeline:
Coaches will provide individual advice and mentoring for fellows.
The CSGrad4US group mentoring sessions will be coupled with regular individual coaching sessions taking place from mid-September through mid-December and additional sessions in the spring. Serving as coaches, experienced CS faculty will provide individual help with graduate application development and identification of PhD programs matching the student’s interest and background. Individual coaching builds on the material covered in the group mentoring sessions.
Timeline:
The sequencing of the objectives is based on using earlier prepared materials to help with later prepared materials. Thus, we start with the resume to help with learning about the mentee’s experiences, strengths, and weaknesses and we discuss the strengths and weaknesses an admission committee will see on the transcript. We then discuss and determine whom to request letters of reference from so that the requests can be made early. We spend time researching and choosing targeted schools. If any schools require GRE general and/or subject test scores, we determine how to prepare for those tests and when to take them. We then focus on the content outlining and writing of the statement of purpose essay. The resume and statement of purpose are both needed to provide to reference letter writers. We discuss and draft requests for references. We determine if additional essays are needed and work toward completing those essays.
The coaches will mimic the quick assessment of the week’s materials and provide feedback from the perspective of the admissions review committee, then discuss how to modify the materials to improve the admission committee review outcome.
Coaches will be paid a stipend for their service in two equal installments. The first payment will be processed in week 7, and the second will be processed after week 12.
The training will start with the co-PIs providing relevant publications and studies to the coaches, and organizing online discussion sessions based on the material shared. We plan on having two 90-minute sessions with the coaches. A repository of the material provided in advance plus notes from the training sessions will be created and shared with the coaches. Training will draw from existing material providing insights and recommendations on successfully mentoring graduate students in computing research and education.
The topics to be addressed in the training sessions will be presented as situational case studies. Coaches will be given a short description of a potential fellow’s situation, with an example of a CV and a transcript. This will help ground the discussion on a specific, even if fictional, case.
For questions, please email csgrad4us@cra.org
The CSGrad4US Fellowship Online Module is the official platform of the Computer and Information Science and Engineering Graduate Fellowship Program (CSGrad4US). The module is used by CSGrad4US Fellows, as well as their associated Academic/Research Advisor(s), Coordinating Official (CO), and Financial Official (FO) at the Institution of Higher Education (IHE) where they are enrolled, to complete required tasks (see list below) of the CSGrad4US Fellowship Program.
Please direct questions about the CSGrad4US Online Module to us at csgrad4us@cra.org.
Fellows:
Contact information, institution and major/program
Annual Activities Report (signed by Academic/Research Advisor)
Fellowship Status Declaration (Annual)
Fellowship Status Change (Optional)
Change in Field of Study, Research Direction, or Degree Plan (Optional)
Academic/Research Advisor Confirmation Form (Annual)
Request to terminate the Fellowship (Optional)
Institution:
AOR Certification Form
Grants Roster Report
Program Expense Report
Completion Report
IHE Directory where they can update the PI, CO, FO, AOR (authorized organizational representative)
Group Mentoring Session Slides
Session 3_ Process of PhD Application Preparation
Session 4_ Application and Decision Process
Session 5_ From Your Application To Your Decision
Panel Sessions
Session 1: What I Wish I Would Have Known Before Applying
Session 2: Q&A with Cohort 1 & 2 CSGrad4US Fellows
Session 3: What I Wish I Would Have Known Before Attending Graduate School
| Question | Answer |
| Can I change institutions while in the program? | Fellows are permitted to change IHEs. It is the Fellow’s responsibility to arrange for admission to a graduate program and to request approval from the CO and CRA, via the CSGrad4US Online Module, for any Institutional changes. Fellows should ensure that their profile in the CSGrad4US Online Module reflects their correct IHE. |
| Can I change fields of study/academic focus while in the program? | Major changes in scope (i.e., changes in major field of study) during the graduate career may be proposed after the completion of the first year of graduate study and require CRA approval. |
| Can I change my status after making an initial declaration? | Fellows must declare their status for the next Fellowship year by the deadline specified in the CSGrad4US Online Module. Requests to change from Tenure to Reserve or vice versa after the Fellowship year has begun are not permitted. |
| Can I pursue other activities outside of my discipline while participating in the program? | Fellows may pursue other activities off campus during the academic year if the activities are part of their graduate degree program. While pursuing these activities, Fellows must maintain full time enrollment. These activities are subject to the approval of the CO who confirms that these activities are part of the Fellows’ graduate education program and normal degree progress.
Internships and traineeships may be permitted. While On Reserve, Fellows may receive a stipend associated with an internship or traineeship. |
| Can I utilize additional funding while participating in CSGrad4US? | CSGrad4US Fellowships cannot be concurrently accepted or combined with support from another individual federal graduate fellowship irrespective of the Fellow’s status. Fellows are however allowed to accept non-federal funding, and are permitted to solicit and accept from other federal sources support for research expenses. |
| Can I work full-time while pursuing my PhD? | Fellows must be enrolled full-time in their doctoral degree program as defined by the institution. In accepting CSGrad4US funds, the institution will also certify that the Fellows are eligible to receive the Fellowship. Fellows declare Tenure Status for three years, in 12-month increments, during the five-year Fellowship Period. During Tenure Years, Fellows actively utilize Fellowship support – receiving a stipend and institutional cost-of-education allowance – both of which are paid to the institution and the institution will disperse the stipend payments to fellows. The Fellowship includes a maximum of three Tenure Years. This includes situations where all or part of the support is forfeited (lost). Tenure includes periods of full-time research and/or coursework under the direction of an Academic/Research Advisor at the Institution, whether or not the Institution is in session, as well as any normal, short vacation periods. Summer is not considered a “short vacation period,” and to be eligible to receive stipend payments during the summer, Fellows are expected to be actively engaged in their graduate program through coursework or research under the direction of an Academic/Research Advisor, with summer enrollment status as required by the Institution. Fellowship Tenure Status is granted in 12-month increments corresponding to a Fellowship year (summer or fall start) and may not be broken into smaller units spread across more than one year, except in cases of NSF-approved Medical or Military Deferral (see below). Given the full-time nature of the fellowship, opportunities to maintain external work arrangements may be limited and must have the approval of the Institution. Full-time status is established by each Institution and may include reduced course load requirements, such as following admission to candidacy or equivalent status. In cases where a Fellow on Tenure has a period of non-enrollment during the academic year, the non-enrollment period is subject to the approval of the CO. Approval confirms that the activities conducted are part of the Fellow’s graduate education program and normal degree progress. These non-enrollment periods may include professional development opportunities such as field courses, extended workshops, and other activities as deemed appropriate by the CO and the Fellow’s institution and conform to the terms in this Guide. |
| Can I work in a department of my University while being a fellow? | Given the full-time nature of the fellowship, opportunities to maintain external work arrangements may be limited and must have the approval of the Institution. Full-time status is established by each Institution and may include reduced course load requirements, such as following admission to candidacy or equivalent status. In cases where a Fellow on Tenure has a period of non-enrollment during the academic year, the non-enrollment period is subject to the approval of the CO. Approval confirms that the activities conducted are part of the Fellow’s graduate education program and normal degree progress. These non-enrollment periods may include professional development opportunities such as field courses, extended workshops, and other activities as deemed appropriate by the CO and the Fellow’s institution and conform to the terms in this Guide. |
| Can I also apply to the NSF GRFP if I am awarded the CSGrad4US Fellowship? | No. CSGrad4US Fellowships cannot be concurrently accepted or combined with support from another individual federal graduate fellowship irrespective of the Fellow’s status. |
| How do I declare my fellowship status? | All Fellows must declare their status for the next Fellowship year by the deadline specified in the CSGrad4US Online Module. Fellows must certify that they continue to meet the eligibility requirements, as described in the CSGrad4US Dear Colleague Letter and annual certifications. The annual status declaration also confirms that the Fellow accepts the Terms and Conditions in the current Administrative Guide. |
| What are the consequences of not complying with the Terms and Conditions of the Fellowship | Failure to comply with the Fellowship Terms and Conditions will result in termination of the Fellowship offer and render individuals ineligible to re‐apply. In cases where Fellows have misrepresented their eligibility or have failed to comply with the Fellowship Terms and Conditions, the Fellowship will be terminated, and the case may be referred to the NSF Office of Inspector General for investigation.
Failure to comply with the following Fellowship Terms and Conditions also will result in termination of the Fellowship: |
| What are the Enrollment requirements? | All Fellows must be enrolled, full time, in an eligible research-based graduate degree program at a degree granting IHE accredited in, and at a campus located in, the US, its territories, or possessions, or the Commonwealth of Puerto Rico, except in the case of Military or Medical Leave. Full-time status is established by each IHE and may include reduced course load requirements, such as following admission to candidacy or equivalent status. The IHE’s registrar must consider the Fellow enrolled, and the Fellow must provide to NSF a transcript that reflects enrollment status upon request.
Fellows must be enrolled full-time in their doctoral degree program as defined by the institution. |
| What does “Active – On Tenure” mean? | Declaring status as “Active – On Tenure” signifies that the fellow is enrolled in an eligible degree granting program and is actively receiving the CSGrad4US stipend during the period. Fellows use On Tenure Status for a maximum of three years, in 12‐month increments, during the five‐year Fellowship period. |
| What does “Active – On Reserve” mean? | Declaring status as “Active – On Reserve” signifies that the fellow is enrolled full‐time in an eligible degree granting program but is not receiving a CSGrad4US stipend during the period. Reserve status allows Fellows the flexibility of incorporating professional development opportunities into their graduate programs. Fellows may use Reserve status for two years, in 12-month increments, during the five-year Fellowship Period. Fellows On Reserve remain enrolled as full-time students and actively engage in research or coursework, as part of the graduate degree program. |
| What deliverables am I responsible for on Canvas? | Fellows are required to complete separate tasks described in the CSGrad4US Administrative Guide by the specified due date via the CSGrad4US Online Module. These include: 1) submit the Annual Activities Report with the signed Academic/Research Advisor Confirmation Form; and 2) declare Fellowship year status. |
| What is the Annual Activities Report? | The Annual Activities Report includes information on research accomplishments and activities related to broader impacts, presentations, publications, teaching and research assistantships, awards and recognitions, and other scholarly and service accomplishments. Fellows must complete the certifications on the e-signature page when the Annual Activities Report is submitted. To complete this requirement, the Fellow must provide a copy of the Annual Activities Report to their Academic/Research Advisor for review, approval, and signature prior to submission, well in advance of the deadline. The signed form is uploaded into the CSGrad4US Online Module. |
| What is an ORCID ID? | All Fellows are encouraged to include an Open Researcher and Contributor ID (ORCID®, https://orcid.org/) identifier in their Fellow record. An ORCID identifier provides a persistent digital identifier that distinguishes you from every other researcher and, through integration in key research workflows such as manuscript and grant submission, supports automated linkages between you and your professional activities ensuring that your work is recognized. Submitting ORCID IDs, while encouraged, is optional. |
| What happens if I have to terminate my fellowship or end my participation in the mentoring program? | Should a Fellow find it necessary to voluntarily discontinue their Fellowship before completion of the Fellowship, the Fellow is required to initiate and submit a Request to Terminate the Fellowship, via the CSGrad4US Online Module. |
| Is health insurance at the institution covered by the fellowship? | It depends on the institution and how it handles health insurance for graduate students of similar academic standing. If health insurance is typically handled as a part of mandatory tuition and/or fees, then they cannot charge the fellow for health insurance as they have agreed to exempt them and only accept the $16,000 COE Allowance. However, if health insurance is not a “mandatory fee” as clarified by some institutions, then the fellow may be responsible for purchasing health insurance separately. |
| If the tuition at the institution will be less than $16k per academic year, what will happen to the remaining tuition dollars? | The NSF CSGrad4US Fellow’s institution is required to exempt the Fellow from paying tuition and fees normally charged to students of similar academic standing, unless such charges are optional or are refundable. The institution is responsible for tuition and required fees in excess of the cost-of-education allowance. |
| Question | Answer |
| Can I be automatically re-added to next year’s group of CSGrad4US fellows if I cannot participate in preparing applications this year? | Mentoring program participants who are unable to prepare graduate school applications during the year they are selected for the program may participate in the mentoring program the following fall; however, doing so does not extend the time requirement to begin a CISE PhD program no later than the Fall of the second year beyond your year of selection. (i.e., apply and selected for CSGrad4US Fellowship Program in 2024 = must begin CISE PhD program no later than Fall 2026) |
| How can I meet the basic enrollment requirements of the fellowship? | Fellows must be enrolled full-time in their doctoral degree program as defined by the institution. In accepting CSGrad4US funds, the institution will also certify that the Fellows are eligible to receive the Fellowship. Fellows declare Tenure Status for three years, in 12-month increments, during the five-year Fellowship Period. During Tenure Years, Fellows actively utilize Fellowship support – receiving a stipend and institutional cost-of-education allowance – both of which are paid to the institution and the institution will disperse the stipend payments to fellows. |
| What is the official title of the fellowship we should be using? | NSF Computer and Information Science and Engineering Graduate Fellowship Program (CSGrad4US) |
| How many courses does a PHD student typically take? | That depends on the program stage of the student (a first year student often takes a higher course load), the course requirements of the program, the courses the student wants to take/the adviser recommends, and possibly other factors. In addition, a PhD student will register for research courses (doing his/her own research). International graduate students need to register for at least two courses. Registering for 2 courses is common, but that can include research courses. For a not-first-year PhD student, taking two regular courses in a semester is considered a high course load (often discouraged by the adviser).
Fellows must be enrolled full-time in their doctoral degree program as defined by the institution. |
| How often are Mentoring Sessions? What If I am unable to attend any or all of the sessions? | The CSGrad4US Fellowship Mentoring Program offers Group Mentoring sessions throughout the Fall. Additionally, mentees will be meeting on a weekly basis with their mentoring coach. |
| How do I access the Online Module? | CSGrad4US Mentees will be added to the CSGrad4US Online Module in April and will receive an email invitation to join. |
| Where can I find CIP codes? | Mentees and Fellows can look up and access a complete list of CIP codes on the National Center for Education Statistics’ CIP Code webpage. |
| What is a CIP code? | A CIP code is a Classification of Instructional Program code. |
| What are the primary CIP codes that apply to the CSGrad4US Fellowship? | The primary CIP codes that apply to the CSGrad4US Fellowship are as follows:
11.01 (CIS) 11.04 (IS) 11.07 (CS) 14.09 (CE) |
| What should I do if I do not know and cannot find the CIP code of the department I am interested in? | Should a mentee have questions or concerns regarding the eligibility of a specific department’s CIP code and is unable to find information online, the recommended course of action is to directly contact the department of interest and ask for their CIP codes. If a member of the department informs the mentee that their program is eligible, it will most likely be accepted by NSF. |
| What happens if the program has a different CIP code than those listed? | If the PhD Program under consideration has a CIP code that is different from the primary CIP codes (11.01, 11.04, 11.07, or 14.09), then a letter will be required from the department chair/head describing the program and certifying that the program is in fact an eligible CISE-related program. The letter must be sent to CRA at CSGrad4US-support@cra.org for consideration. |
| Is health insurance at the institution covered by the fellowship? | It depends on the institution and how it handles health insurance for graduate students of similar academic standing. If health insurance is typically handled as a part of mandatory tuition and/or fees, then they cannot charge the fellow for health insurance as they have agreed to exempt them and only accept the $16,000 COE Allowance. However, if health insurance is not a “mandatory fee” as clarified by some institutions, then the fellow may be responsible for purchasing health insurance separately. |
| If the tuition at the institution will be less than $16k per academic year, what will happen to the remaining tuition dollars? | The NSF CSGrad4US Fellow’s institution is required to exempt the Fellow from paying tuition and fees normally charged to students of similar academic standing, unless such charges are optional or are refundable. The institution is responsible for tuition and required fees in excess of the cost-of-education allowance. |
| Question | Answer |
| What is the “CISE” Discipline? |
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| What is a CISE PhD Program? |
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| What does not qualify as a CISE PhD Program? |
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| What is needed to apply for the CSGrad4US Fellowship? | All CSGrad4US Fellowship applicants must submit the following information through NSF ETAP: before the application deadline:
To view full guidance about application materials, please visit: https://www.nsf.gov/pubs/2024/nsf24033/nsf24033.pdf |
| Is there a page limit for my application materials? | Yes, the length of the two personal statements must together total no more than five (5) pages. Statements must be written with the following criteria:
To view full guidance about application materials, please visit: https://www.nsf.gov/pubs/2024/nsf24033/nsf24033.pdf |
| Can I use the fellowship at a For-Profit institution? | CSGrad4US Fellowship applicants are advised that, to eventually receive a fellowship, they must pursue graduate study in a doctoral degree-granting program in a CISE discipline at an accredited, non-profit institution of higher education having a campus located in the United States, its territories or possessions, or the Commonwealth of Puerto Rico. |
| Can I still apply to this fellowship if I was accepted into a PhD program for the following year? | Eligible applicants must not have a pending application or offer of admission to a CISE Ph.D. program. |
| How will I be notIfied of my acceptance into the program? What is my next step? | CSGrad4US Fellowship applicants who are selected for the program will be sent a Fellowship Offer Letter by e-mail in June/July, and must formally accept and agree to the Fellowship Terms and Conditions using the CSGrad4US Online Module by the specified due date. Acceptance of the fellowship implies that the Fellow is aware of the consequences of not complying with the Terms and Conditions. |
| How will I get matched with my coach? | The CSGrad4US Fellowship Mentoring Program Leadership will use the information provided in your application (including research interests) to match you with a coach. |
CRA is reviewing all programs and practices and will implement any necessary revisions due to federal Executive Orders and/or federal funding agency guidance.
We remain dedicated to our mission and service to the computing research community.
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Erik Russell
Susanne Hambrusch
Russ Joseph
Kelly Shaw
