About Me
Hi, Iām Logan Cadman, a graduate student in Computer Science at Colorado State University. My journey has been anything but traditional. I started out as an automotive technician, where I learned to solve real world problems with my hands. Over time, I discovered how technology can make a lasting impact on peopleās lives.
At CSU, Iāve worn many hats, from leading student orientation programs during COVID, an experience that sharpened my leadership skills, to managing Linux systems and networks as a Systems Administrator in the Computer Science department. Those varied roles have given me a unique blend of hands on know how and a big picture approach to problem solving.
An internship at VMware deepened my fascination with cybersecurity and networking, especially how virtualization can address big challenges like reducing environmental impact. Ultimately, I believe technology isnāt just about writing code or deploying systems, itās about helping people. Iām excited to keep learning, building, and finding new ways to make a positive difference.
Highlights
Graduate Research
Investigating internet transmission errors through the HIPFT project, focusing on error detection and data analysis. Made custom Linux kernel modifications and automated log connection pipelines. Maintained server infrastructure for data collection and analysis.
Systems Administration
Managing over 600 Linux servers and workstations, implementing OpenLDAP migration, GPU monitoring for efficient resource management, system updates, and user support.
Leadership & Collaboration
Supervised orientation programs at CSU, managing a team of 26 orientation leaders, facilitating large-scale events, and training on communication, diversity, and team building.
Education
M.S. Computer Science @ Colorado State University
2023 - 2025, Fort Collins, CO.
Focused on systems, networking, machine learning, and software engineering.
B.S. Computer Science @ Colorado State University
2019 - 2023, Fort Collins, CO.
Officer in the Computer Information Systems Club, member of the Augmented Reality/Virtual Reality Club, Orientation Leader, Undergraduate Systems Administrator.
Experience
+ Graduate Research Assistant @ Colorado State University (2023āPresent)
- Investigated internet transmission errors through HIPFT, simulating real-world issues with custom Linux kernel modifications.
- Developed automated pipelines to collect and analyze over 10,000 logs for error detection and benchmarking.
- Applied time series analysis and machine learning to detect patterns and mitigate DDoS attacks.
+ Systems Administrator @ Colorado State University (2020āPresent)
- Managed and maintained 600+ Linux systems, ensuring smooth operations for students, faculty, and researchers.
- Designed and implemented the migration from NIS to OpenLDAP, enhancing system security and user management.
- Automated GPU monitoring and enforced resource limits for efficient lab usage.
+ Technical Support Engineer Intern @ VMware (2022)
- Collaborated with systems administrators to resolve complex VMware vCenter Server networking issues.
- Completed training toward VMware Certified Professional Certification.
- Supported enterprise-level clients in troubleshooting cloud and virtualization solutions.
+ Orientation Team Leader @ Colorado State University (2020ā2021)
- Supervised 26 orientation leaders to welcome 5,296 students, fostering community through large-scale events.
- Conducted interviews for over 200 candidates and led training on communication and teamwork.
- Redesigned orientation programs during COVID-19 to adapt to virtual and in-person formats.
Projects & Papers
Adaptive Honeypots: Optimizing Dwell Time with Reinforcement Learning
This project explores how we can make honeypots smarter by using reinforcement learning to adapt their lifespan based on real-time network activity. Inspired by DSCOPE, a system that used fixed 10-minute honeypot sessions, I built a dynamic alternative that learns when to keep honeypots running longer to catch delayed or low-frequency attacks. The system runs on Google Cloud, spinning up honeypots, capturing TCP SYN traffic with tcpdump, and feeding contextual data (like connection rate, unique IPs, and traffic trends) into a tabular Q-learning agent. The agent learns to balance the value of captured data against resource usage, gradually favoring longer dwell times (like 45 minutes) in richer threat environments. Key takeaway: fixed honeypot durations can miss out on valuable attack data. By adapting in real time, this system captures more meaningful behavior from slow or stealthy adversaries.
Learn MoreLooking for Errors TCP Misses
Inspired by prior work suggesting undetected errors were becoming a problem on the Internet, we set out to create a measurement system to detect errors that the TCP checksum missed. We designed a client-server framework in which the servers sent known files to clients. We then compared the received data with the original file to identify undetected errors introduced by the network. We deployed this measurement framework on various public testbeds. Over the course of 9 months, we transferred a total of 26 petabytes of data. Scaling the measurement framework to capture a large number of errors proved to be a challenge. This paper focuses on the challenges encountered during the deployment of the measurement system. We also present the interim results, which suggest that the error problems seen in prior works may be caused by two distinct processes: (1) errors that slip past TCP and (2) file system failures. The interim results also suggest that the measurement system needs to be adjusted to collect exabytes of measurement data, rather than the petabytes that prior studies predicted.
Learn MoreLearning 2048 with Reinforcement Learning
Project for CS545 at Colorado State University Fall 2023, by Chad Schwenke and Logan Cadman. This project utilizes AI to play the 2048 game.
Learn MoreAnalyzing the Communication Patterns of Different Teammate Types in a Software Engineering Course Project
Effective communication is vital for the success of professional software engineering (SE) teams. As SE courses teach essential industry skills like teamwork and collaboration, ensuring effective communication becomes important in student projects. However, poor engagement from team members can lead to conflicts, uneven workloads, and diminished learning experiences. Teammate types such as Couch Potatoes, who contribute minimally, and āHitchhikersā, who rely on others while taking credit, exacerbate these issues. In contrast, āLone Wolvesā work independently, potentially isolating themselves, while āGood Teammatesā actively collaborate and contribute somewhat, driving team success. In this study, we aimed to investigate the communication patterns of teammate types such as Couch Potato, Hitchhiker, Lone Wolf, or Good Teammate during a SE testing course. We applied Ordered Network Analysis (ONA) to the conversational data of the teams to examine the distinct communication patterns of students whose contributions were either perceived positively (e.g., Good Teammates) or negatively (e.g., Couch Potato, Hitchhiker, Lone Wolf) by their peers. The findings reveal distinct communication behaviors across teammate types. While Good Teammates and Couch Potatoes discussed similar content, Good Teammates communicated more frequently and consistently throughout the project. Lone Wolves seldom engaged in pleasantries, reflecting a task-focused approach, whereas Hitchhikers rarely contributed substantively to technical discussions, such as pull requests, but often interacted through pleasantries. These patterns emphasize the need for early interventions and communication planning to promote accountability balance and effective student collaboration during class projects.
Learn MoreCourses
CS-540
Artificial Intelligence
Level: Graduate
About the Course
Covers topics from various subareas of AI, including learning, planning, and reasoning.
CS-542
Natural Language Processing
Level: Graduate
About the Course
Covers advanced NLP techniques such as parsing, language models, and applying machine learning to text analysis.
CS-580B2
Human/Social Factors in Software Engineering
Level: Graduate
About the Course
Examines the impact of social and human dynamics on software teams, focusing on communication and collaboration.
CS-501
Introduction to Research in Computer Science
Level: Graduate
About the Course
Introduces research methods, literature reviews, and effective academic communication in computer science.
CS-510
Image Computation
Level: Graduate
About the Course
Explores computational techniques for image processing, focusing on algorithms and real-world applications.
CS-535
Big Data
Level: Graduate
About the Course
Focuses on large-scale data processing, including Hadoop, Spark, and distributed systems for analytics.
CS-514
Software Product and Process Evaluation
Level: Graduate
About the Course
Teaches evaluation techniques for software products, processes, and methodologies for quality assurance.
CS-545
Machine Learning
Level: Graduate
About the Course
Covers machine learning fundamentals, focusing on algorithms, classification, regression, and neural networks.
CS-415
Software Testing
Level: Undergraduate
About the Course
Introduces methods for software testing, including test design, debugging, and quality assurance practices.
CS-458
Blockchain Principles and Applications
Level: Undergraduate
About the Course
Explores blockchain concepts, including cryptocurrency, consensus mechanisms, and decentralized applications.
CS-464
Principles of Human-Computer Interaction
Level: Undergraduate
About the Course
Examines the design, implementation, and evaluation of user interfaces for improved user experiences.
CS-456
Modern CyberSecurity
Level: Undergraduate
About the Course
Covers principles and practices of cybersecurity, including cryptography, network security, and threat mitigation.
CS-457
Computer Networks and the Internet
Level: Undergraduate
About the Course
Introduces networking principles, including protocols, architecture, and the Internet's technical foundations.
CS-462
Engaging in Virtual Worlds
Level: Undergraduate
About the Course
Focuses on virtual and augmented reality concepts, including interface design and immersive experiences.
CS-320
Algorithms - Theory and Practice
Level: Undergraduate
About the Course
Covers algorithm design, analysis, and implementation, focusing on efficiency and computational complexity.
CS-356
Systems Security
Level: Undergraduate
About the Course
Focuses on system vulnerabilities, security threats, cryptography, and secure software development practices.
CS-370
Operating Systems
Level: Undergraduate
About the Course
Covers operating system concepts such as process management, memory management, file systems, and concurrency.
CS-314
Software Engineering
Level: Undergraduate
About the Course
Introduces software development lifecycle, project management, and team-based software design methodologies.
CS-270
Computer Organization
Level: Undergraduate
About the Course
Explores computer architecture, digital logic, assembly language, and the relationship between hardware and software.
CS-253
Software Development with C++
Level: Undergraduate
About the Course
Teaches object-oriented programming, memory management, and software design principles using C++.
CS-220
Discrete Structures and their Applications
Level: Undergraduate
About the Course
Covers mathematical concepts such as logic, set theory, combinatorics, and graph theory for computer science.
CS-165
CS2--Data Structures
Level: Undergraduate
About the Course
Focuses on fundamental data structures such as linked lists, trees, stacks, and queues, along with algorithms.
CS-163
CS1---No Prior Programming Experience
Level: Undergraduate
About the Course
Introduces programming fundamentals, including variables, loops, functions, and basic problem-solving techniques.
CS-150
Introduction to Programming (CS0)
Level: Undergraduate
About the Course
Provides an overview of programming concepts and problem-solving, designed for students with no programming background.
CIS-355
Business Database Systems
Level: Undergraduate
About the Course
Explores database design, normalization, SQL, and data management systems for business applications.
CIS-320
Project Management for Information Systems
Level: Undergraduate
About the Course
Teaches project management methodologies, risk analysis, and resource planning for IT projects.
CIS-240
Application Design and Development
Level: Undergraduate
About the Course
Focuses on designing, developing, and deploying applications with an emphasis on user experience and functionality.
Resume
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