CyberAI at Michigan Tech

CyberAI SFS scholars receive financial and professional support consistent with the NSF/OPM CyberAI program rules and grant funding availability. Benefits are expected to include:

• Full-time tuition and education-related fees.
• An annual stipend: $27,000 per year for undergraduate students and $37,000 per year for graduate students.
• A professional development allowance for activities such as travel, conferences, and professional certifications, up to $6,000 per academic year.
• Personalized academic advising and mentoring.
• Career development support for internships and post-graduation government placement.
• Participation in a supportive CyberAI learning community, including faculty mentoring, peer mentoring, external mentoring, research engagement, professional development, and outreach activities.

CyberAI SFS scholars must agree to:

• Work after graduation for the federal government or for a state, local, or tribal government organization in a position related to cybersecurity, AI, or both, for a period equal to the length of scholarship support.
• Participate in government internship opportunities during the summers of scholarship study, as required by the SFS program.
• Maintain good academic standing and make satisfactory progress toward the approved B.S. + M.S. degree plan.
• Complete required CyberAI coursework and participate in program activities, including advising meetings, mentoring activities, professional development, cyber competitions, conferences, research, and outreach.
• Complete all required SFS documentation, including service agreements, entry and exit counseling, and related materials required by NSF, OPM, and Michigan Tech.

CyberAI SFS scholars are responsible for applying for and obtaining qualifying internship and employment positions. Michigan Tech will provide support by helping scholars identify opportunities, prepare application materials, and connect with government agencies, national laboratories, and other eligible public-sector organizations.

The CyberAI SFS program is designed primarily for students pursuing an accelerated B.S. + M.S. pathway. Scholars may choose a combination of the B.S. and M.S. degree programs, subject to prerequisite requirements, course sequencing, and approval by the project director. Participating undergraduate programs include:

• B.S. in Cybersecurity
• B.S. in Computer Science
• B.S. in Software Engineering
• B.S. in Information Technology
• B.S. in Data Science
• B.S. in Artificial intelligence

At the graduate level, CyberAI scholars may pursue:

• M.S. in Cybersecurity
• M.S. in Computer Science
• M.S. in Data Science

Exceptional students from other undergraduate majors may also be considered if they demonstrate strong preparation, clear interest in CyberAI, and commitment to public service.

• Students with junior standing are encouraged to apply for the CyberAI program, as the scholarship covers the cost of the senior year and one additional year for the M.S. degree.
• Students with senior standing may also apply and plan to pursue a two-year M.S. degree, especially if additional bridge courses are needed.
• High school students, as well as students in their freshman or sophomore year, are encouraged to actively participate in cybersecurity and AI related activities and apply for the scholarship in a future year.

The CyberAI SFS program prepares students through an integrated curriculum that combines cybersecurity, AI, data science, experiential learning, research, and professional development. Scholars are expected to complete at least four approved cybersecurity courses and at least two approved AI-related courses within the combined B.S. + M.S. curriculum.

This “4 + 2” curriculum model supports five core competencies:

• Foundational cybersecurity knowledge and skills.
• Foundational AI knowledge and skills.
• Application of AI techniques to cybersecurity challenges.
• Security of AI-enabled systems.
• Ability to operate effectively in government and mission-driven environments.

Each scholar will work with a faculty mentor and academic advisor to develop an individualized degree plan that aligns coursework, research, professional development, internship preparation, and career goals. Scholars are encouraged to broaden their preparation by combining cybersecurity and AI/data science experiences across the B.S. and M.S. degrees.

Choose at least four approved cybersecurity courses

• CS4471/5471 Computer Security
• CS4723 Network Security
• CS4001/5001 National Cybersecurity Policy & Law
• CS4711 Software Processes and Management
• CS4710 Model Driven Software Development
• CS5751 Dependable and Secure CPS-IoT
• CS4740/5740 Development of Trusted Software
• CS5472 Advanced Topics in Computer Security
• CS5350 Modern Cryptography
• CS5751 Systems Performance Analysis
• SAT3812 Cybersecurity I
• SAT4812 Cybersecurity II
• SAT4283/5283 Information Governance and Risk Management
• SAT4816/5816 Digital Forensics
• SAT4520/5520 Machine Learning in Security
• SAT4817/5817 Penetration Test
• SAT5111 Security and Privacy
• SAT5317 Internet of Things
• SAT5555 Blockchain Fundamentals
• EE5315 Security of Automotive Systems
• EE5455 Security for Industrial Control Systems
• MA3203 Cryptography
• MIS4200 Management of Cybersecurity

Choose at least two approved AI courses

• DATA2201 Foundations of Data Science
• CS2800 Introduction to AI Applications
• CS4801 Foundations of Machine Learning
• CS4811 Artificial Intelligence
• CS4821 Data Mining
• CS4611 Computer Graphics
• CS4841/5841 Deep Learning
• CS5851 Advanced Natural Language Processing
• CS4861/5861 AI Theory and Applications
• CS5831 Advanced Data Mining
• CS5631 Data Visualization
• CS5761 Human-Robot Interaction
• SAT3903 AI Tools and Applications
• SAT4411 Data Center Operations
• SAT5165 Introduction to Big Data Analysis
• SAT5114 AI in Healthcare
• SAT5646 Machine Learning for Drug Discovery
• SAT4520/5520 Machine Learning in Security
• EE5615 AI Engineering Applications
• HU3704 AI Ethics
• MIS4000 AI & Emerging Technologies for Business
• MIS4400 Business Intelligence and Analytics
• EET4501 Applied Machine Learning

Additional courses may be added with the approval of the project team.

CyberAI SFS scholars will participate in a structured learning community supported by faculty mentors, peer mentors, external mentors, the Pavlis Honors College, Career Services, alumni, and government partners.

Each scholar will develop an Individual Development Plan that outlines coursework, research, experiential learning, outreach, professional development, internship preparation, and career goals. Scholars will meet regularly with faculty mentors and advisors to review progress and receive guidance.

Professional development activities will help scholars strengthen communication, teamwork, leadership, ethics, professional identity, and career readiness for government service. Scholars will also be encouraged to participate in cybersecurity competitions, professional conferences, research projects, certifications, and outreach activities.

1. SFS eligibility and ability to meet government employment requirements.
2. Academic performance and potential.
3. Relevant experience in cybersecurity, AI, data science, computing, research, internships, projects, competitions, certifications, or outreach.
4. Motivation for CyberAI and commitment to public service.
5. Communication, leadership, teamwork, professionalism, and career readiness.
6. Potential to complete the CyberAI SFS program successfully and obtain qualifying internship and employment placements.

1. Join RedTeam or other student organizations. Take a leadership role if possible.
2. Participate in National Cyber League, Capture-the-Flag events, Programming Contests, or other competitions and professional development activities.
3. Take cybersecurity, AI, and data science courses that support CyberAI preparation.
4. Build projects that connect cybersecurity and AI, such as AI-enabled threat detection, secure machine learning, LLM security, IoT security, privacy-preserving systems, or secure data analytics.
5. Seek summer internships, undergraduate research, enterprise projects, or senior design projects.
6. Develop communication, leadership, and teamwork skills through student organizations, outreach, mentoring, and community service.