Kloub, Lina

Assistant Professor in Residence, School of Computing

Email lina.kloub@uconn.edu
Phone (860) 486-0543
Mailing Address University of Connecticut 371 Fairfield Way, Unit 4155 Storrs, CT 06269-4155
Office Information Technology Engineering building (ITE) room 302

Lina Kloub is an Assistant Professor in Residence in the School of Computing at the University of Connecticut and a Neuroinclusive Engineering Teaching Fellow. She earned her Ph.D. in Computer Science and Engineering from UConn in 2021. Dr. Kloub is a Faculty Affiliate in AI at the Center for Excellence in Teaching and Learning (CETL), where she supports faculty across disciplines in integrating AI responsibly into their courses.

Dr. Kloub is deeply committed to inclusive teaching practices that foster belonging, accessibility, and student success. Her teaching and mentoring philosophy centers on creating collaborative and supportive environments where students can develop both technical expertise and essential career readiness skills. She has been recognized with

Her teaching and mentoring philosophy centers on creating inclusive, collaborative, and supportive learning environments where students can thrive both academically and professionally. She has been recognized with the 2025 AAUP Teaching Excellence: Early Career Award and the Belonging and Advocacy Educator Award from the Vergnano Institute for Impact, reflecting her dedication to innovation in engineering education.

 

AI Integration in Education: Developing frameworks to help faculty adopt AI responsibly in their teaching, including interactive assignments, group projects, and curriculum design.

Career Readiness in Engineering: Incorporating NACE career competencies into computing courses through group projects, reflective surveys, and hands-on activities.

Neuroinclusive Teaching Practices: Redesigning courses such as Algorithms and Complexity to apply I-standards for inclusivity, accessibility, and wellness.

Honor thesis supervisor: 2025-2026: work closely with the honor students and serve as a scholarly guide throughout the development, implementation, and conclusion of their honor thesis project.

  • Alejandro Reilly – Fall 2025: Technical Debt Amplified by AI: Real-World Case Studies and Strategies for Mitigation - 2026 ASEE-NE Conference Under review
  • Samuel Chichester – Spring 2026: Evaluating the Effects of AI-Driven Interfaces on User Experience

Research advisor: Supervised undergraduate research projects, fostering publication and career development opportunities.

  • Aayush Gupta - 2023-2024: "ChatGPT in Computer Science Education: Exploring Benefits, Challenges, and Ethical Considerations" ASEE-NE 2024.
  • Vraj Patel – 2024-2025: Best paper award "AI tools in the Spotlight: Addressing Educators' Concerns and Building Trust" ASEE-NE 2025
  • Christina Smith and Faiyhaa-Sydra Saulat: Spring 2025: "Enhancing Career Readiness Skills for Engineering Students with Artificial Intelligence" ASEE-NE 2025.
  • Karina Jadia, Priya Jeyaprakash, Faiyhaa-Sydra Saulat, Xinyi Li, and Neev Vachhani: fall 2025 on project “Husky Lecture Log: The cutting-edge AI tool that can analyze a video and provide transcripts with specifically curated content, answer questions about confusing topics, and provide questions to help build a strong understanding of materials.

 

  • Spring 2026:
    • Sophia Gomez Reynoso
    • Troy Murphy
  • Fall 2025:
    • Alejandro Reilly
    • Karina Jadia
    • Priya Jeyaprakash
    • Faiyhaa-Sydra Saulat
    • Xinyi Li
    • Neev Vachhani
  • Spring 2025:
    • Vraj Patel
    • Christina Smith
    • Faiyhaa-Sydra Saulat
  • Fall 2024:
    • Vraj Patel
  • Fall 2023 - Spring 2024:
    • Aayush Gupta

 

  • AI Integration in Education: Developing frameworks to help faculty adopt AI responsibly in their teaching, including interactive assignments, group projects, and curriculum design.

  • Career Readiness in Engineering: Incorporating NACE career competencies into computing courses through group projects, reflective surveys, and hands-on activities.

  • Neuroinclusive Teaching Practices: Redesigning courses such as Algorithms and Complexity to apply I-standards for inclusivity, accessibility, and wellness.

  • Faculty Development Workshops: Leading initiatives to train faculty across disciplines on using AI for course design, assessment, and engagement.

Algorithms and Complexity (CSE 3500): Redesigned using inclusive teaching standards and project-based learning. The course emphasizes understanding algorithm design paradigms (divide-and-conquer, greedy, dynamic programming, randomized algorithms), and computational complexity. Students work in teams on research-driven projects to practice communication, teamwork, and career readiness competencies.

Data Structures and Object-Oriented Design (CSE 2050): Focuses on core data structures and object-oriented programming principles in Python. Students engage in collaborative coding labs and weekly assignments that reinforce concepts in both algorithmic efficiency and software design. The course emphasizes problem-solving, debugging, and peer collaboration.

Software Engineering (CSE 2102): Covers the fundamentals of software engineering, including requirements analysis, design patterns, testing, and documentation. Students learn modern development practices such as Agile methodology, Git/GitHub, and CI/CD concepts. A semester-long team project simulates real-world development, giving students hands-on experience with collaboration, project management, and stakeholder communication.

Kloub, V. Patel, T. Heuy – Best paper award "AI tools in the Spotlight: Addressing Educators' Concerns and Building Trust" 2025 ASEE-NE Conference

Kloub – "Empowering Students with AI: A Universal Design Framework for Learning and Growth" 2025 ASEE-NE Conference

Kloub, C. Smith, F. Saulat "Enhancing Career Readiness Skills for Engineering Students with Artificial Intelligence" 2025 ASEE-NE Conference

Alshugran, L. Kloub "Preserving Student Privacy While Leveraging Generative AI in Higher Education" 2025 ASEE-NE Conference

Kloub, A. Gupta – "ChatGPT in Computer Science Education: Exploring Benefits, Challenges, and Ethical Considerations" ASEE 2024.

Kloub – "Engaging Minds, Elevating Performance: The Transformative Power of Interactive Review Sessions in Computer Science Courses," ASEE 2024.

Kloub, S. Gosselin, J. Graf, J. P. Gogarten, M. S. Bansal – "Investigating Additive and Replacing Horizontal Gene Transfers Using Phylogenies and Whole Genomes," Genome Biology and Evolution, 16(9), evae180, 2024.

Kloub, S. Gosselin, M. Fullmer, J. Graf, J. P. Gogarten, M. S. Bansal  – "Systematic Detection of Large-Scale Multigene Horizontal Transfer in Prokaryotes," Molecular Biology and Evolution, 38(6): 2639–2659, 2021.

S. Yoo, L. Kloub – "Mobile Web Application with Shortest Path Finder: Traveler’s Sidekick," IEEE SAI Computing Conference, 2016.

  • Neuroinclusive Engineering Teaching Fellow, UConn School of Engineering

  • Faculty Affiliate for AI, UConn Center for Excellence in Teaching and Learning (CETL)

  • Faculty Mentor, NSF S-STEM Scholarship Program

  • Career Champion, Center for Career Readiness and Life Skills