Hi, I'm Misan.
Applied AI • Software Engineering • Learning Technology • Human-Centered AI
I build and evaluate AI-powered products, software systems, and learning experiences that help people solve problems, learn, and work more effectively.
My work sits at the intersection of applied AI, software engineering, learning technology, and user research. I've developed production applications, RAG systems, machine-learning pipelines, and educational technology—and worked with users to understand their needs, translate complex concepts into useful experiences, and measure what works.
I hold an M.S. in Computer Science from Northern Arizona University, where my research focused on designing, deploying, and evaluating AI and software systems in real-world learning and software-development environments.
Real World Impact
I developed a learning system deployed at Northern Arizona University
OSS-Doorway was deployed across undergraduate (CS 386) and graduate (CS 499/599) software engineering courses, supporting students through authentic GitHub-based open-source workflows.
How I Work
Understand → Design → Build → Deploy → Evaluate → Improve
Understand
Identify user needs through research, observation, interviews, feedback, and domain analysis.
Design
Translate complex problems into clear workflows, learning experiences, prototypes, and technical solutions.
Build
Develop software and AI systems using modern application, ML, and LLM technologies.
Deploy
Put solutions into real environments with learners, developers, and other users.
Evaluate
Combine product data, experiments, surveys, interviews, and human evaluation to understand effectiveness.
Improve
Turn evidence and user feedback into better products, experiences, and systems.
Systems built for real people
AI assistants, learning platforms, and ML systems designed, deployed, and evaluated with real users — in classrooms, open-source communities, and production products.
OSS-Doorway
OSS-Doorway is a learning environment designed to help students develop practical software-engineering skills through authentic GitHub and open-source workflows. Rather than completing isolated programming assignments, students work through structured quests involving repositories, issues, branches, commits, pull requests, and other real development activities. I contributed to the system's development, classroom deployment, evaluation, and continued improvement across university computing courses.
ML Task Recommendation for Open-Source Software
Developed a machine-learning system for identifying open-source software issues suitable for university student projects. The project analyzed 3,295 real-world GitHub issues using issue text and semantic representations to rank promising tasks for educator and maintainer review. In independent blind evaluation, a senior open-source maintainer confirmed approximately 60% of the top-ranked recommendations as suitable university projects, including previously uncatalogued opportunities.
JabRAG
How can newcomers get trustworthy answers about an unfamiliar software project without searching across documentation, issues, source repositories, and developer discussions? JabRAG is a retrieval-augmented generation system that retrieves information from project documentation, GitHub issues, repository resources, and developer discussions before generating answers grounded in project-specific knowledge. I worked on the retrieval architecture, knowledge sources, LLM integration, and evaluation against general-purpose LLM and human-generated answers across helpfulness, comprehensiveness, conciseness, and practical usefulness.
Learning & User Experience
Experience-design case studies from real deployments
Research → Practice
I don't just build AI systems. I study whether they actually work.
My work combines product development, user research, learning design, and empirical evaluation. I study how people interact with AI and software, where they struggle, what information or support they need, and whether the resulting systems actually improve their experience.
Depending on the problem, that has involved experiments, classroom deployments, surveys, interviews, observations, human evaluation, behavioral data, and iterative product improvement.
FSE Companion '26
Shh! Don't Tell Them I Use GenAI: Exploring How Participants Use Generative AI in Hackathons
P Acharya, T Conte, J Penney, P Oliveira, MP Etchie, et al.
BotSE @ ICSE 2025
Towards a Dataset to Assess Conversational Agent's Efficacy in Mentoring Newcomer Developers
MP Etchie, H Beach, K Felizardo, I Steinmacher
arXiv:2606.07544
AI-Integrated Learning Management System for Middle School: A Longitudinal Study of Learning Outcomes Through High School and Beyond
MP Etchie, T Olutosin
Technical Communication
Making complex technology understandable is a recurring part of my work.
I write for technical, academic, educational, and general audiences—from peer-reviewed research and software documentation to instructional material and technology articles. I enjoy turning complex systems and ideas into explanations that help people understand what matters and what to do next.
Experience
RESHAPE Lab
Wiseki Technologies
Lead City University
New Horizons
Skills
AI & Software
Learning & Experience Design
Research & Evaluation
Product & Communication
Additional Technologies
Education
Northern Arizona University
Lead City University
Research & publications
Consumer & product apps
iOS and cross-platform applications shipped to real users.
SekiApp
Contributed to the development and maintenance of a cryptocurrency-focused mobile application at Wiseki Technologies. Worked on product functionality, API integrations, application maintenance, and user-facing improvements.
PlugNG
Contributed to a mobile platform that brings multiple everyday digital services into one application, including airtime, mobile data, electricity payments, television subscriptions, educational services, event tickets, and virtual-card functionality. Worked on mobile development and integration of third-party services through APIs.
Boardly
Built a collaborative workspace where users can create shared boards containing notes, images, polls, tasks, events, links, and conversations. Designed around real-time collaboration so changes are synchronized across participants.
Selected community, conference, and service work.
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National Association of Computing Students — Director of Welfarism & Community — Lead City University
Lead City University
-Organized activities and initiatives for computing students.-Supported student engagement and community development.-Mentored fellow computing students.
What I'm Interested In
I'm interested in roles at the intersection of AI, technology, learning, research, and user experience.
That includes:
Applied AI • Learning Experience Design • Learning Technology • AI Enablement • Technical Instructional Design • Product & Customer Education • Human-Centered AI • AI Evaluation • Research Engineering • Learning Engineering • Developer Education
I'm especially drawn to work where I can understand a complex problem, translate technology into a useful experience, work with real users, and use evidence to improve the result.
Get in Touch
I'm always interested in conversations about applied AI, learning technology, software engineering, research, and building useful experiences.
Let's connect.
Send me an email