Computational and Data Sciences

Computational and Data Sciences Welcome to the George Mason University's Computational Data Science Program page.

Join us for Mason Space Day 2023. During this FREE, open to the public event, attendees of all ages can meet the honorab...
10/16/2023

Join us for Mason Space Day 2023. During this FREE, open to the public event, attendees of all ages can meet the honorable NASA astronaut, Charles F. Bolden Jr., and attend presentations explaining the science and technology behind some of the area’s leading aerospace projects. Take a tour of the Mason Observatory and planetarium, or visit numerous organizations with hands-on space-related activities, and information. We look forward to seeing you October 22 from 3 to 9 p.m. on Mason's Fairfax Campus.
Learn more and register: science.gmu.edu/masonspaceday

CDS researchers conclude that Mars colony could survive with fewer than two dozen people:
09/26/2023

CDS researchers conclude that Mars colony could survive with fewer than two dozen people:

Using computer simulations, scientists also determined the personality types best suited for stays of up to 28 years on the Red Planet.

As the Women’s History Month celebration comes to an end, we ask you all to say hello to our very own Dr. Estela Blaiste...
03/31/2023

As the Women’s History Month celebration comes to an end, we ask you all to say hello to our very own Dr. Estela Blaisten-Barojas.

Dr. Estela Blaisten-Barojas holds a Ph.D. in Molecular Physics from Sorbonne University, Paris, France. Since joining the Mason professoriate, she has been a very active participant in the institution growth. She was a major driving force in the curriculum development of several doctoral programs, including the Ph.D. in Computational Sciences and Informatics. As a faculty senator for 8 years, she represented the School of Computational Sciences faculty with excellence. Through the coordination of the Mason Nanotechnology Initiative, she pioneered the establishment of cooperation agreements between the Mason Office of Research and several organizations, both national and international. She is the founding director of the Center for Simulation and Modeling within the College of Science that has brought significant external funding for research activities. Within the Department of Computational and Data Sciences, she has developed a battery of graduate courses on a variety of modeling and simulation approaches in the physical chemistry and materials sciences. As Graduate Coordinator/Program Director of the Ph.D. in Computational Sciences and Informatics, she was instrumental in advising and consolidating the success of hundreds of doctoral and master’s students along seven years of fruitful time investment. She has been the thesis research advisor of 16 doctoral students and 6 master students, who as Mason’s alumni have proudly incorporated themselves in the federal, corporate, and academic worlds.
Dr. Blaisten-Barojas has been recognized by several organizations: as a Fellow by the American Physical Society, as a member by the Academia Mexicana de Ciencias, and as a Fulbright senior awardee. She is part of the Advisory Board of two scientific journals and is Associate Editor of Frontiers in Nanotechnology. Currently, she is part of the Editorial team for the Women in Nanotechnology collection of Frontiers in Nanotechnology.

We asked her, “What words of wisdom do you have for other women who are just beginning their jouney’s in STEM?” Her response, “Follow your instincts and never give up.”

We begin the final week of Women’s History Month by saying hello to our very own Mason Korea professor Dr. Sohyun Park. ...
03/30/2023

We begin the final week of Women’s History Month by saying hello to our very own Mason Korea professor Dr. Sohyun Park.

Dr. Sohyun Park is an assistant professor of Computational and Data Sciences at George Mason University, Korea. She earned her doctorate in geography from The Ohio State University. Her research focused on the socio-environmental change in the Korean strawberry industry. Her research lies at the intersection of environmental science, economic geography, and spatial data analytics. She is interested in socio-environmental inequality in the context of the growing interdependency between places (e.g., linked via food trade and residential migration).

When we asked her, “What words of wisdom do you have for other women who are just beginning their journey’s in STEM?” Her response was,” Welcome aboard! I believe that it is essential to be open to learning and trying new things and never be afraid to ask for help or guidance. I would encourage women to find mentors and role models who can provide support, advice, and encouragement.”

Everyone say hello to Dr. Annie HuiFor over ten years, Dr. Hui has had the opportunity to meet and talk with many women ...
03/30/2023

Everyone say hello to Dr. Annie Hui

For over ten years, Dr. Hui has had the opportunity to meet and talk with many women at the start of their STEM journey. Dr. Hui mentioned women starting in STEM come from all kinds of backgrounds and have very diverse expectations on what STEM has for them. Some do STEM because of personal interest. Some want to acquire useful skills that lead to better job prospects. The challenges and obstacles faced by women in STEM are many and diverse. Examples include, but are not limited to, inferiority feelings, stereotypes, debts, exhaustion, family, social unrest.

To Dr. Hui It seemed that the greatest encouragement that keep a woman going is the conviction that she is on a good path. Sometimes, this could mean putting all her energy into her work to make quick progress in her career. Other times, it could mean stepping back from the next big career opportunity to give priority to people she loves. Yet other times, it could mean persevering on doing good against the tide.

When we asked her, “What words of wisdom do you have for other women who are just beginning their journey’s in STEM?” Her response was, “Stand at the crossroads and look; ask for the ancient paths, ask where the good way is, and walk in it, and you will find rest for your souls.’ (Jeremiah 6:16)”

Up next for this Women’s History Month we have Dr. Carmen Iasiello! Dr. Carmen Iasiello’s research focuses on the practi...
03/21/2023

Up next for this Women’s History Month we have Dr. Carmen Iasiello!

Dr. Carmen Iasiello’s research focuses on the practical applications of agent-based modeling and database design. Previous and current topics have included early Chinese state formation, underrepresentation in labor markets, human resource management, and energy infrastructure systems.

When we asked her, “What words of wisdom do you have for other women who are just beginning their jouney’s in STEM?” Her response was, "We collectively accomplish more in STEM, when we each bring our whole selves. Do so honestly and unabashedly."

As Women’s History Month continues we ask everyone say hello to Dr. Sharmin AbdullahDr. Sharmin Abdullah recently joined...
03/16/2023

As Women’s History Month continues we ask everyone say hello to Dr. Sharmin Abdullah

Dr. Sharmin Abdullah recently joined the George Mason University faculty as an assistant professor in the department of Computational and Data Sciences.

Sharmin earned her bachelor’s degree in electrical and electronic engineering from Ahsanullah University of Science and Technology, Dhaka, Bangladesh in 2013. She received the Dean’s honor list award for her academic excellence.

She completed her Master’s in 2019 and Ph.D. in 2021 in Computational Science from The University of Texas at El Paso (UTEP). She worked as a teaching assistant for Computational Science program and as a research associate at the Nanomil Lab in the Electrical and Computer Engineering department of UTEP during her graduate studies. She completed her dissertation work with the prestigious 2021-2022 Diana Natalicio Dissertation Research Fellowship from UTEP Graduate School. She also received the Ph.D. Academic and Research Excellence Award from the Computation Science Program at UTEP in Fall 2021.

Sharmin’s research focus is on atomistic simulations of material characteristics. She has worked on analyzing the microstructures of photovoltaic thin film materials via molecular dynamics to improve the solar cell efficiency. She has performed research for a project funded by the U.S. Department of Energy and collaborated with a scientist from Sandia National Laboratories. She worked as a research fellow at the Lawrence Berkeley National Laboratory in the summer of 2019. Sharmin is the co-author of several publications in peer reviewed journals. She has attended several national and international research conferences including IEEE PVSC conference, MRS Fall and Spring Meetings and 2021 International High Performance Computing Summer School.

When we asked her, “What words of wisdom do you have for other women who are just beginning their journey’s in STEM?” Her response was, “Don't let anyone make you believe that you are not good enough for a career in STEM. You have the potential and ability to succeed in any field you choose. Embrace the challenges of your chosen field and keep pushing yourself to learn and grow.”

We continue our Women’s History Month Celebration this week with our next amazing faculty member, say hello to Dr. Holly...
03/14/2023

We continue our Women’s History Month Celebration this week with our next amazing faculty member, say hello to Dr. Holly Russo!

She has worked with the federal government in national security and defense since 2002 and she is a US Air Force veteran. After having been a researcher at the RAND Corp. and Center for Naval Analyses, and working at other large and small companies, she decided to start her own woman-owned, veteran-owned small consulting firm Cybélé Data Advisory LLC. They are now teamed with a larger firm providing support to DARPA, and with other large firms on other potential opportunities.

She is currently assisting a DARPA Program Manager in leading a $65M research project developing approaches to make it easier for scientists to build, maintain and reason over rich models of complex systems including physical, biological, social, engineered or hybrid systems.

Her broader passion is in facilitating team success in government research and data operations. She seeks to bridge the communication gap between the C-suite / Flag Officer leadership and data teams, to build sustainable and effective data operations that deliver real value.

We asked her, “What words of wisdom do you have for other women who are just beginning their journeys in STEM?” Her response:

Trust your vision: I think there are two key mistakes I’ve made throughout my career, which I want to help others avoid. These are things to which women are particularly susceptible:
1. Don’t stop working on something because someone else tells you that what you’re doing isn’t important; it could be that they lack the vision you have. Make your own decision about whether something is important.
2. Don’t assume that something you’ve developed is too simple or not novel or couldn’t be right. I failed to publish one paper that would’ve turned out to be pretty significant years later, simply because I didn’t trust that I could actually be right. Years later, things evolved just as I said they would in my paper, but I never published so I missed a major opportunity. I’ve failed to follow up on other things because I thought that they were too simple, or not new. I always wound up kicking myself years later.

We continue our Women’s History Month celebration with more outstanding Faculty members! Say hello to Dr. Hoda Bidkhori....
03/09/2023

We continue our Women’s History Month celebration with more outstanding Faculty members! Say hello to Dr. Hoda Bidkhori.

Dr. Bidkhori’s research focuses on data analytics, optimization, and artificial intelligence. Her mission is to utilize data to drive efficient decisions and tackle emerging social, environmental, and operational challenges.

For example, she has worked on:
Developing robust AI methods for kidney exchange and organ allocation.
Designing integrated learning and optimization frameworks for decision-making facing complex systems and environments.

We asked her, “What words of wisdom do you have for other women who are just beginning their journey’s in STEM?” Her response was,” Congratulations to all women in STEM! I acknowledge all their undeniable role in the success and well-being of our community. Please do not let anything deprive you of your dreams."

The Department of Computational and Data Sciences celebrates Women’s History Months by honoring the women within our pro...
03/09/2023

The Department of Computational and Data Sciences celebrates Women’s History Months by honoring the women within our program who have made an immense impact in science and who will continue to do extraordinary things. We begin this month’s celebrations by saying hello to one of the amazing women we have within the Computational and Data Sciences Department, Dr. Anamaria Berea.

Dr. Berea has an extensive background in Computational and Social Science and is currently doing research on applying data science and computational methods to astrobiology problems. Her larger research goal is to understand how humanity and space will coevolve together.

We asked her, “What words of wisdom do you have for other women who are just beginning their journey’s in STEM?” Her response, “Believe in yourself, adapt to opportunities, be open to multi- and inter-disciplinarity, and have an attitude of exploration in science.”

05/23/2022

Oral Defense of Doctoral Dissertation
Doctor of Philosophy in Computational Sciences and Informatics
Department of Computational and Data Sciences
College of Science
George Mason University

Jarrod K. Grewe

Bachelor of Science in Mathematics, College of the Ozarks, 2009
Master of Science in Applied Mathematics, University of Missouri-Columbia, 2011

Optimizing Search Plans for Teams of Mobile and Stationary
Searchers with a New Class of Searchers over a Multi-zoned
Domain and Finite Time

Thursday, June 2, 2022 - 11:00 a.m.
https://gmu.zoom.us/j/91474856728

All are invited to attend.

Committee
Dr. Igor Griva, Dissertation Director
Dr. Estela Blaisten, Committee Chair
Dr. Andrew Crooks, Committee Member
Dr. Hamdi Kavak Committee Member


This dissertation introduces a new search theory methodology, nicknamed Pathfinder, that can optimize teams of heterogeneous mobile and stationary searchers as well as searchers that can transport other searchers. In addition, Pathfinder can optimize searches over a multi-zone domain and model target behavior based on environmental and behavioral factors. Pathfinder accomplishes this by using an agent-based model to estimate target movement; then it uses nonlinear optimization, teamed with a genetic algorithm, to find optimal search plans. The optimization model considers that search plans should be easy to both implement and create in reality, in addition to having a high probability of finding a target. Thus, the optimization model includes movement constraints that make search plans easier to implement and more cost effective. The obtained results from numerous simulations demonstrate that the methodology has the potential to advance current search theory as well as to enhance current maritime search operations.

Zoom is the leader in modern enterprise video communications, with an easy, reliable cloud platform for video and audio conferencing, chat, and webinars across mobile, desktop, and room systems. Zoom Rooms is the original software-based conference room solution used around the world in board, confer...

08/05/2021

Are you interested in urban analytics and ABM? Looking for a two-year postdoc? Former CSS Faculty member Andrew Crooks has such a position open at the University at Buffalo. For further details see: https://www.ubjobs.buffalo.edu/postings/29858

04/27/2021

Mason's Online Pandemic MODeling Forum
Friday, April 30, 3-4:30 p.m.

Elise Jing, Scientist
Sirius XM and Pandora

Characterizing Partisan Political Narratives about COVID-19 on Twitter

The COVID-19 pandemic is a global crisis that has been testing every society and exposing the critical role of local politics in crisis response. In the United States, there has been a strong partisan divide which resulted in polarization of individual behaviors and divergent policy adoption across regions. Here, to better understand such divide, we characterize and compare the pandemic narratives of the Democratic and Republican politicians on social media using novel computational methods including computational framing analysis and semantic role analysis. By analyzing tweets from the politicians in the U.S., including the former president, members of Congress, and state governors, we systematically uncover the contrasting narratives in terms of topics, frames, and agents that shape their narratives. We found that the Democrats' narrative tends to be more concerned with the pandemic as well as financial and social support, while the Republicans discuss more about other political entities such as China. By using contrasting framing and semantic roles, the Democrats emphasize the government's role in responding to the pandemic, and the Republicans emphasize the roles of individuals and support for small businesses. Both parties' narratives also include shout-outs to their followers and blaming of the other party. Our findings concretely expose the gaps in the "elusive consensus" between the two parties. Our methodologies may be applied to computationally study narratives in various domains.

04/07/2021

Oral Defense of Doctoral Dissertation
Doctor of Philosophy in Computational Social Science
Department of Computational and Data Sciences
College of Science
George Mason University

Carmen Arleth Iasiello
Bachelor of Arts, American University, 2001
Master of Arts, Columbia University, 2003

An Agent-Based Modeling Approach for Human Resource Management

Tuesday, April 20, 2021
9:30 - 11:30 AM
All are welcome to attend.
Join Zoom Meeting https://gmu.zoom.us/j/99433798372... Meeting ID: 994 3379 8372
Passcode: 050180

Committee
Andrew Crooks, Chair
Robert Axtell
William Kennedy
Sarah Wittman

Abstract: Computational social science methods and specifically agent-based modeling have increasingly been used within applied social science fields. A significant contributor to this trend has been the availability of fine-grained data about individual and social behavior. While data availability may aid this process, the true power of computational social science arises when data and theory are combined. Theories derived from different social science traditions vary in their development, testing methods, and interpretation of data. The applications of computational methods have largely excluded explicit consideration of what is gained or lost in the translation of theory derived from epistemic traditions that differ from that in computational social science. This dissertation addresses this gap in three ways. First, it defines a framework that may be used in the process of applying inductively-derived, qualitatively-developed theories. Second, it applies this framework by exploring management science theory. Third, it presents an agent-based model informed by a management science theory and validates it based on human resource management data. This application is presented as a replicable example of both epistemological translation and the computational methods applied.

Zoom is the leader in modern enterprise video communications, with an easy, reliable cloud platform for video and audio conferencing, chat, and webinars across mobile, desktop, and room systems. Zoom Rooms is the original software-based conference room solution used around the world in board, confer...

04/07/2021

Mason’s Online Pandemic MODeling Forum
Friday, April 9, 2021
3:00 pm - 4:30 pm EDT (UTC-4:00)

Murat Tasci, Senior Research Economist, Research Department, Federal Reserve Bank of Cleveland

Unemployment in the Time of COVID-19: A Flow-Based Approach to Real-time Unemployment Projections | NBER

This paper presents a flow-based methodology for real-time unemployment rate projections and shows that this approach performed considerably better at the onset of the COVID-19 recession in the spring 2020 in predicting the peak unemployment rate as well as its rapid decline over the year. It presents an alternative scenario analysis for 2021 based on this methodology and argues that the unemployment rate is likely to decline to 5.4 percent by the end of 2021. The predictive power of the methodology comes from its combined use of real-time data with the flow approach.

Murat Tasci is a senior research economist in the Research Department of the Federal Reserve Bank of Cleveland. He is primarily interested in macroeconomics and labor economics. His current work focuses on labor market fluctuations over the business cycle, labor market policies and search frictions. Prior to joining the Cleveland Reserve Bank in 2006, Dr. Tasci was a Teaching and Research Assistant at the University of Texas at Austin. Dr. Tasci received a bachelor's degree in economics at Koc University in Istanbul, Turkey, and an MS and PhD in economics from the University of Texas at Austin.

Join WebEx meeting
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04/07/2021

Oral Defense of Doctoral Dissertation - John Leung

Doctor of Philosophy in Computational Sciences and Informatics
Department of Computational and Data Sciences
College of Science
George Mason University

Thursday, 4/22/2021
10:00 AM - 12:00 PM

John Kalung Leung

Bachelor of Science, American University, 1984
Master of Science, Johns Hopkins University, 1990
Executive Master Business of Administration, University of Texas at Arlington, 2008

Emotion Aware Recommender Systems

Committee

Igor Griva, Chair
Jason Kinser
Estela Blaisten-Barojas
William Kennedy

ABSTRACT: Recommender Systems help users to overcome information overload by making predictions and recommendations that meet users' tastes and preferences. A user's mood influences his/her decision-making in choosing from a list of top-N recommended items. However, Recommenders do not track users' moods state when making top-N recommendations to users. Thus, users often found stale recommendations in the top-N list.

I proposed to enhance Recommender Systems by tracking users' moods state and make top-N recommendations based on the updated users’ and items’ emotion profiles. In recognition of several limitations: (1) emotion-labeled attributes are not readily available in datasets, (2) lack of standard definition for emotions and procedure to collect and label emotion metadata, (3) not all objects have a face for facial emotion detection and recognition despite facial micro-expression detection and recognition of basic human emotions are popular methodology to label a person's primary facial emotional expressions, I developed a text-based Tweets Affective Classifier model capable of emotion detection and recognition based on Ekman's six basic human emotions and neutral emotion. This model is then used to extrapolate basic human emotions from the subjective text of objects such as movie overview or product descriptions. Furthermore, I developed an innovative Affective Aware Pseudo Association Method (AAPAM) to pseudo connect disjoint objects in datasets within the same or different information domains.

This research has shown that an Emotion Aware Recommender could track users' moods in making subsequent top-N recommendations that contain serendipitous items, thus overcoming the cold-start and staleness issues confronted in the field. Using the Affective Index Indicator (AII) to pseudo connect disjoint users or items for making recommendations in Collaborative Filtering is shown to be more efficient than the traditional Collaborative Filtering computing through rating matrix. I further extended the APPAM to support decision-making strategies in a multi-user group. Finally, I found by applying users' and items' emotion profiles in a system simulcast group can improve the throughput of top-N recommendations.

Thursday, 4/22/2021
10:00 AM - 12:00 PM

Join Zoom Meeting
https://zoom.us/j/95391587292?pwd=ejRrRzFTbnAwaFFlTk82a2Q1R0JVZz09

Meeting ID: 953 9158 7292
Passcode: cv8iJ4

All are invited to attend.

Zoom is the leader in modern enterprise video communications, with an easy, reliable cloud platform for video and audio conferencing, chat, and webinars across mobile, desktop, and room systems. Zoom Rooms is the original software-based conference room solution used around the world in board, confer...

03/22/2021

Mason Online Pandemic MODeling Forum
Friday, March 26, 2021

Eric Winsberg, Professor of Philosophy, University of South Florida

Models, Values, and Precaution: How should models guide policy?

Models have a played a prominent role in guiding Covid-19 mitigation policy, often being used to make confident and dire predictions. But models such as these often embed assumptions about values. They also can encode precautionary reasoning that emphasizes a particular balance of risks. How can we optimize the use of models to guide policy in a crisis? What has the last year taught us about expert testimony and “following the science”?

03/18/2021

Colloquium on Computational Social Science/Computational Data Sciences - Mason Online Pandemic MODeling Forum

March 19, 2021
11:00 a.m. (EDT)

Verónica Acurio Vásconez
Associate Professor, University of Lorraine
Member of the Bureau d’Economie Théorique et Appliquée (BETA)

Macroepidemics and unconventional monetary policy

Despite the fact that the current covid-19 pandemic was neither the first nor the last disease to threaten a pandemic, only recently have studies incorporated epidemiology into macroeconomic theory. In our paper, we use a dynamic stochastic general equilibrium (DSGE) model with a financial sector to study the economic impacts of epidemics and the potential for unconventional monetary policy to remedy those effects. By coupling a macroeconomic model to a traditional epidemiological model, we are able to evaluate the pathways by which an epidemic affects a national economy. We find that no unconventional monetary policy can completely remove the negative effects of an epidemic crisis, save perhaps an exogenous increase in the shares of claims coming from the Central Bank (“epi loans”). To the best of our knowledge, our paper is the first to incorporate disease dynamics into a DSGE-SIR model with a financial sector and examine the effects of unconventional monetary policy.

03/08/2021

Colloquium on Computational Social Science/Computational Data Sciences - Mason Online Pandemic MODeling Forum

Mar 12, 2021, 3:00 - 4:30 PM

Jidong Zhou, Associate Professor, Economics, Yale University and Fei Li, Associate Professor, Economics, University of North Carolina Chapel Hill

A Model of Crisis Management

We propose a model of how multiple societies respond to a common crisis. A government faces a ``damned-either-way'' policy-making dilemma: aggressive intervention contains the crisis, but the resulting good outcome makes people skeptical of the costly response; light intervention worsens the crisis and causes the government to be faulted for not doing enough. This dilemma can be mitigated for the society that encounters the crisis first if another society faces it afterward. Our model predicts that the later society does not necessarily perform better despite having more information, while the earlier society might benefit from a dynamic counterfactual effect.

03/08/2021

CSS/CSI Colloquium - Mason Online Pandemic MODeling Forum

March 12, 2021
3:00-4:30 p.m.

Jidong Zhou, Associate Professor, Economics, Yale University and Fei Li, Associate Professor, Economics, University of North Carolina Chapel Hill

A Model of Crisis Management

We propose a model of how multiple societies respond to a common crisis. A government faces a ``damned-either-way'' policy-making dilemma: aggressive intervention contains the crisis, but the resulting good outcome makes people skeptical of the costly response; light intervention worsens the crisis and causes the government to be faulted for not doing enough. This dilemma can be mitigated for the society that encounters the crisis first if another society faces it afterward. Our model predicts that the later society does not necessarily perform better despite having more information, while the earlier society might benefit from a dynamic counterfactual effect

Colloquium on Computational Social Science/Computational Data SciencesMar 5, 2021, 3:00 - 4:30 PMBenefit-Cost Analysis o...
02/17/2021

Colloquium on Computational Social Science/Computational Data Sciences

Mar 5, 2021, 3:00 - 4:30 PM

Benefit-Cost Analysis of COVID Policy Intervention at the State and National Level: Dr. James L. Doti is President Emeritus and Professor of Economics at Chapman University

https://science.gmu.edu/events/colloquium-computational-social-sciencecomputational-data-sciences-9

Benefit-Cost Analysis of COVID Policy Intervention at the State and National Level: Dr. James L. Doti is President Emeritus and Professor of Economics at Chapman University

02/11/2021

Data Analytics Intern with Teleworld Solutions for students graduating 2021

All students in following majors with interest in the opportunity to be hired immediately:

Field of Study: Computer Science/Applied Computing, Data Analytics Engineering, Electrical/Computer Engineering, Computational Data Science, Mathematics or Related Fields.

Intern Job Description:

Working with Teleworld's client team to develop machine learning models, developing python code, data analytics
Learning how to run the backend IT systems for client applications.
The role will start out as an Internship and the candidate needs to be graduating between May and September 2021.
US and Green Card Holders only please
Please send resumes immediately to:

[email protected]

https://science.gmu.edu/news/data-analytics-intern-teleworld-solutions-students-graduating-2021

Repperger Research Intern Program - Deadline Approaching!Repperger Research Intern ProgramNow accepting applications for...
02/11/2021

Repperger Research Intern Program - Deadline Approaching!

Repperger Research Intern Program

Now accepting applications for summer 2021!

Deadline: February 15, 2021

The Repperger Research Intern Program is a 10-week educational experience, providing research opportunities for students at one of three Air Force research facilities under the mentorship of an Air Force scientist. The program posthumously honors Dr. Daniel W. Repperger, who mentored many young people during his 35-year research career with the Air Force Research Laboratory (AFRL).

Eligibility

Applicants need to meet the following eligibility criteria at the time of application:

· Be a U.S. citizen

· Be enrolled as an undergraduate or graduate student at an accredited institution of higher education during the 2020-2021 academic year

· Be pursuing a degree in a science, technology, engineering or mathematics (STEM) discipline

· Have a cumulative GPA of 2.50 or higher on a 4.00 scale

Research Locations

· Wright-Patterson Air Force Base, Dayton, OH

· Joint Base San Antonio-Fort Sam Houston, San Antonio, TX

· Carnegie Mellon University, Pittsburgh, PA

Program Dates

June 7 – August 13, 2021

How to Apply

Submit your application at the following link: https://www.zintellect.com/Opportunity/Details/AFRL-711HPW-2021-Repperger

Application Deadline

February 15, 2021, at 8 a.m. ET

Want to Learn More?

For additional information, visit the Repperger Research Intern Program website. If you have any questions, please contact [email protected].

The U.S. Air Force Research Laboratory (AFRL) leads the discovery, development and integration of affordable warfighting technologies for America's air, space and cyberspace forces. AFRL is a full-spectrum laboratory, responsible for planning and executing the Air Force's science and technology prog...

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