Cybersecurity is a priority area of national need. As a multidisciplinary field, cybersecurity requires that the professionals have knowledge and skills in various disciplines. The REU site program offers unique multidisciplinary learning and research opportunities for undergraduate students in an inherently multidisciplinary cybersecurity discipline. Each student will be able to select his/her preferred mentor and work with the mentor to select an REU research project based on his/her interests and background. The students will master research methodologies and obtain valuable research experiences in an area of critical national need, and also better prepare for graduate studies. The REU program is also enriched through various seminars, social activities, and field trips to Naval Base Norfolk, and Navy Cyber Defense Operation Command (NCDOC).
Applying
Deadline: Preferred by Mar. 1, 2023. Early applications are strongly encouraged. The applications will be reviewed on a rolling basis. You will need to have a google or gmail account to log in, in order to upload the following documents in the application process.
i) Resume: list education (post secondary), academic and research achievement (honor, awards, etc.),
research experience, skills, and other special qualifications if any.
ii) The transcripts from the post secondary institutions you have attended. Unofficial transcripts are
good for the application. If you are selected to join the program, the official transcripts will be needed.
iii) Cover letter (optional): describe your interest in cybersecurity, your career goal, etc.
After you have resume and transcripts ready, please click the following link to start your application. You will have the opportunity to select three prefered mentors during the application. Hence you are suggested to review the research areas of the mentors below, and make your selection. You will work with your mentor to select a research project in the beginning of the REU program (early June). Please feel free to reach out to the mentor or Dr. Xin if you have any questions.
In addition, please request a recommendation letter from a professor of your college. You
can either upload in the application form (preferred), or arrange to send it to Peng Jiang (pjiang@odu.edu)
Contact
Mr. Peng Jiang, School of Cybersecurity, 1133b Monarch Hall, Norfolk, 23529, Email: pjiang@odu.edu
About
- $7,200 for stipends and food
- Free on-campus housing for 10 weeks and travel support
(Conditioned on that the REU program is hosted on-site at ODU)
- U.S. citizen or permanent resident
- Must be an undergraduate student during the program period
(Graduation date after the program period) - Preferred GPA 3.0+
- Students from all disciplines or majors will be considered
- Perform at least 30 hours/week research with the mentor for 10 weeks
(Starting from May 31, 2023) - Attend weekly research meeting and other events
- Write a research report and create a poster at the end of the program
- $7,200 for stipends and food
- Free on-campus housing for 10 weeks and travel support
(Conditioned on that the REU program is hosted on-site at ODU)
- U.S. citizen or permanent resident
- Must be an undergraduate student during the program period
(Graduation date after the program period) - Preferred GPA 3.0+
- Students from all disciplines or majors will be considered
- Perform at least 30 hours/week research with the mentor for 10 weeks
(Starting from May 31, 2023) - Attend weekly research meeting and other events
- Write a research report and create a poster at the end of the program
The REU project is selected together by the student and the mentor based on the student interests and background. The following is a list of selected past REU projects.
- Investigating User Photo Privacy on Social Network Services
- Developing an Automatic Approach for Identifying Directions That Lead to Foreground Background Image Separation Truth Masks for the Building Damage Dataset
- Comparing Telehealth Crimes to Regular Cybercrimes and Health Care Crimes
- Using Privacy-preserving Medical Image Analysis Framework to Predict Prognosis of Patients with Gliomas
- Using Semantic Segmentation and Adversarial Inpainting for Transient Object Removal
- AT-GAN and Co-occurrence Network to Improve Model Robustness to Adversarial Attacks
- Is Transfer Learning Safe? A Case Study in Object Detection Application
- Economics of the Helium Network: User Demand and Network Traffic
- Adversarial Attack Transfer for Edge-Adapted Object Detection Models
- Convolutional Neural Networks with the MNIST dataset module
- A Comparison of Scholarly Articles and Media Articles Focusing on XR in the Military
- Identifying Slow Read DDoS Attack using Deep Learning
Research Mentors
