Geoffrey Challen
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Updated 6/2/2026

Geoffrey Challen

né Werner-Allen

My professional goal is to teach computer science to as many people as possible, and to inspire them to use their skills to change the world for the better.

Department of Computer Science University of Illinois Thomas M. Siebel Center for Computer Science 201 North Goodwin Avenue, Urbana, IL, 61801-2302

Email:[email protected]
Phone:716.464.2749
Website:https://geoffreychallen.com
Public Course Materials:https://learncs.online
Primary Course Website:https://cs124.org
CV:https://geoffreychallen.com/CV
Statements:https://www.geoffreychallen.com/statements
Previous Research Group Website:https://bluegroup.systems
Google Scholar Profile:https://geoffreychallen.com/scholar

My online CV is always more up-to-date than any paper copy.

At this particular moment in computing history, AI has changed what it means to build with computers—and therefore what it means to teach computing. My current work responds along several connected threads.

I’ve redesigned CS 124’s larger programming project around AI coding agents: every student designs and builds their own Android app, and a new independent project teaches the skills that matter in the AI era—writing specifications, working with agents, and evaluating what they produce—while classical programming remains assessed through proctored quizzes.

Alongside that integration, I’m building new courses for students who arrive without a CS background. I piloted CS 199 UAI: Using and Understanding AI in Spring 2026 for non-technical students, and am preparing its permanent form, CS 108: Exploring Generative AI, which I’ll first teach in Spring 2027. I’m leading the design of Applied Computing, a proposed four-year undergraduate degree organized around studio-based design, domain integration, and AI-assisted building. I’m designing CS 199 ASK: Conversational Programming, a new course for anyone who wants to build—no prerequisites, no prior experience, no code—where students learn to work like architects: exploring problems, designing solutions, and partnering with AI to bring ideas to life.

Much of this depends on tools and infrastructure I continue to build: conversational assessment using a two-agent AI architecture, interactive demos that let students explore how AI systems work, and course platforms that are themselves built through conversation with AI. Applying my own skills as a computer scientist to create interactive and engaging learning environments remains central to how I work.

This work has begun to draw recognition beyond my own courses: in 2026 I was selected as a Replit Faculty Fellow—an invited fellowship from Replit, a widely used AI software-development platform—and as a Faculty AI Fellow in the University of Illinois Summer AI Studio, where I provide disciplinary guidance and peer mentorship to colleagues integrating AI into their teaching.

CS 124 remains the foundation for this work, and currently enrolls over 2000 students per year. Since I began teaching the course in Fall 2017, enrollment has doubled, drop rates have fallen, success rates have increased, student performance in later courses has improved, a gender performance gap has disappeared, students are practicing and learning more, the amount of content covered has increased, we have introduced Kotlin as a language option alongside Java, and hundreds of staff members have made contributions that help diversify the course’s voice.

Appointments and Preparation
Appointments and Preparation

I’m a Teaching Professor at the University of Illinois. My appointment is 60% teaching, 20% scholarship, and 20% service. My focus is teaching at scale.

Previous Position
Previous Position

From 2011–2017 I worked in mobile systems as a research professor at the University at Buffalo. My research group designed, built, and evaluated novel computer systems. We focused on smartphones, since they represent the most pervasive and powerful distributed system ever deployed. My previous group’s website is the best source of information about my prior research, and includes project descriptions, copies of all of our published papers and funded grant proposals, information about the courses that we created and taught, and details about former group members.

Academic Appointments
Academic Appointments

Professional Preparation
Professional Preparation

Honors and Awards
Honors and Awards

Teaching
Teaching

Over 21 terms at Illinois I have taught a total of 16,107 students(1). I have focused my efforts on expanding and improving our CS1 course for majors and students with deep interest in the material—previously numbered CS 125 and now CS 124. More recently I’ve been creating new courses on AI: CS 199 UAI: Using and Understanding AI (continuing as CS 108) and CS 199 ASK: Conversational Programming.

Additional information about each course is linked off its main website. Data about student success in each course and detailed student evaluation results available by request. For more details, please review my teaching statement.

Overview
Overview

Only primary teaching assignments are listed.

Course and Curricular Innovations and Improvements
Course and Curricular Innovations and Improvements

Links in the items below are usually to pages on learncs.online, which contains a publicly-accessible version of the materials and innovations I’ve developed to support my university CS1 course at Illinois, CS 124.

Semester-by-Semester Details
Semester-by-Semester Details

Below I provide a summary of the enrollment for each semester I’ve taught CS1 at Illinois, along with a detailed description of various changes and improvements made to the course each term. Note that we usually try to deploy substantial changes to course materials and infrastructure in the fall.

CS 199 UAI: Spring 2026 (In Progress)
CS 199 UAI: Spring 2026 (In Progress)

Website

Enrollment: 11
Format: In-person with AI-facilitated activities and conversational assessments

  1. Inaugural semester of Using and Understanding AI, a course for non-technical students
  2. Students use AI to create websites, music, and data analyses while exploring how AI works and what it means for society
  3. Deployed conversational assessments using a two-agent architecture as a novel scalable alternative to traditional exams
  4. Created interactive AI demos including Digit Recognition Network, Neuron Explorer, and Markov Babbler
  5. Entire course platform built through Claude Code (167 sessions over 47 days)

CS 124: Spring 2026 (In Progress)
CS 124: Spring 2026 (In Progress)

Syllabus // Staff

Enrollment: 400
Format: Tutorial format with both online and in-person support, frequent small assessment
Languages: Kotlin, Java

  1. Launched a new independent project, replacing the traditional shared machine project with individual student-driven Android applications built using AI coding agents
  2. Curriculum now teaches prompt writing, AI code validation, and test-driven development with AI
  3. Classical programming assessment maintained through weekly proctored quizzes

CS 124: Fall 2025 (In Progress)
CS 124: Fall 2025 (In Progress)

Syllabus // Staff

Enrollment: 1100
Format: Tutorial format with both online and in-person support, frequent small assessment
Languages: Kotlin, Java

  1. Integrated effective use of AI coding agents into the larger Android programming project to ensure students are prepared for the future of software development
  2. Began work on several AI integrations into course materials and systems, including retrieval-augment generation, code variable name analysis, and automatically generated quiz retake study guides

CS 124: Spring 2025
CS 124: Spring 2025

Syllabus // Staff

Enrollment: 700
Format: Tutorial format with both online and in-person support, frequent small assessment
Languages: Kotlin, Java

  1. Enhanced online proctoring interface to support remote students.
  2. Added quiz retake opportunities, allowing students additional chances to demonstrate mastery.
  3. Completed major database reorganization for improved system performance and scalability.

CS 124: Fall 2024
CS 124: Fall 2024

Syllabus // Staff

Enrollment: 1294
Format: Tutorial format with both online and in-person support, frequent small assessment
Languages: Kotlin, Java

  1. Deployed autogenerated testing exercises, providing students with practice writing test suites.
  2. Integrated code quality instruction and automated feedback into daily lesson content.
  3. Began coaching program to proactively contact students in need of support and offer individual course strategy sessions.
  4. Deployed Redis-based caching system for improved platform performance at scale.

CS 124: Spring 2024
CS 124: Spring 2024

Syllabus // Staff

Enrollment: 782
Format: Tutorial format with both online and in-person support, frequent small assessment
Languages: Kotlin, Java

  1. Enhanced compilation infrastructure to support mixed Java/Kotlin projects.
  2. Modernized platform architecture for improved performance and scalability.

CS 124: Fall 2023
CS 124: Fall 2023

Syllabus // Staff

Enrollment: 1281
Format: Tutorial format with both online and in-person support, frequent small assessment
Languages: Kotlin, Java

  1. Deployed enhanced mutation testing framework for automated debugging challenge generation.
  2. Continued stability improvements to website frontend and backend systems.
  3. Enhanced assessment platform with improved question delivery and evaluation.

CS 124: Spring 2023
CS 124: Spring 2023

Syllabus // Staff // Lessons

Enrollment: 879
Format: Tutorial format with both online and in-person support, frequent small assessment
Languages: Kotlin, Java

  1. Added profiles of diverse computer scientists to our daily lessons and weekly quizzes as part of a CS People series.
  2. Began work on adding support for autograding test suites for all of the 700 questions in our problem library.
  3. Transitioned the course website to a new static site framework to improve login integration and avoid library deprecation.
  4. Deployed several new code quality analysis features.
  5. Completed work on Kotlin syntactic feature analysis, achieving parity with Java in preparation for a new feature-based code quality analysis pipeline.
  6. Began work with Leon Li and Katie Cunningham to analyze data on student usage of online tutoring resources.

CS 124: Fall 2022
CS 124: Fall 2022

Syllabus // Staff // Lessons

Enrollment: 1399
Format: Tutorial format with both online and in-person support, frequent small assessment
Languages: Kotlin, Java

  1. Fully incorporated debugging challenges throughout the daily lessons, alongside an updated set of homework problems.
  2. Completed work on several new quiz security features, in particular a focus-tracking system that automatically closes a student’s assessment when it loses focus more than a configurable number of times.
  3. Began work with Rachel Zhou and Luc Paquette on processing data from our daily lessons to analyze how students develop preferences for different instructors.

CS 124: Spring 2022
CS 124: Spring 2022

Syllabus // Staff

Enrollment: 666
Format: Tutorial format, frequent small assessment
Languages: Kotlin, Java

  1. Began work on debugging challenges generated from our growing library of student solutions to our homework problems.
  2. Released our CS1 materials publicly at learncs.online.
  3. Improved the staff mentoring program to connect junior and senior course staff members, including involving mentors in staff scheduling to help reduce absenteeism.
  4. Began work on improved quiz security features to better secure our online assessments.

CS 124: Fall 2021
CS 124: Fall 2021

Syllabus // Staff

Enrollment: 1441
Co-Instructor: Colleen Lewis
Format: Tutorial format, frequent small assessment
Languages: Kotlin, Java

  1. Introduced Kotlin as a language option alongside Java, requiring the development of a parallel set of lessons, homework, and assessments, and project.
  2. Colleen Lewis joined as a co-instructor and provided a complete set of alternate explanations for Java-language content.
  3. Worked with Colleen Lewis to update several course policies, including enabling students to collaborate on homework problems and on the machine project.
  4. Prepared data collection from the daily lessons to examine how students develop preferences when explanations from multiple instructors are available.

CS 125: Spring 2021
CS 125: Spring 2021

(Course website no longer online.)

Enrollment: 613
Format: Asynchronous online, frequent small assessment
Language: Java

  1. Continued improving and stabilizing the systems supporting the new course format launched in Fall 2020.

CS 125: Fall 2020
CS 125: Fall 2020

(Course website no longer online.)

Enrollment: 1103
Format: Asynchronous online lessons, frequent small assessment
Language: Java

  1. Relaunched the course in a new asynchronous online daily lesson format to support student success during the pandemic, comprising daily interactive lessons integrating text, code playgrounds, interactive walkthroughs, homework problems, and video explanations.
  2. Deployed a novel homework autograder enabling rapid authoring and accurate evaluation of programming exercises.
  3. Transitioned to a new quizzing and proctoring tool integrating the homework autograder and multiple-choice questions designed to support efficient and secure online assessment.
  4. Integrated the online tutoring tool directly into the new course website, further lowering the bar for students to ask questions and receive one-on-one assistance.
  5. Completed and deployed a new service enabling continuous saving of student work in online code editors, to support student coding on the homework problems and during quizzes.

CS 125: Spring 2020
CS 125: Spring 2020

Syllabus // Staff

Enrollment: 380
Format: Synchronous online lectures, frequent small assessment
Language: Java

  1. Transitioned the course online mid-semester due to onset of the COVID-19 pandemic.
  2. Over spring break, completed the first version of our online tutoring site to allow staff to efficiently provide remote support.
  3. Began preparing for fully-online instruction the next semester.

CS 125: Fall 2019
CS 125: Fall 2019

Syllabus // Staff

Enrollment: 696
Format: Synchronous lectures, frequent small assessment
Language: Java

  1. Deployed the first iteration of the Android machine project, a multi-part assignment where students build a complete Android app through multiple weekly checkpoints, in a process that more accurately reflects real-world software development.
  2. Created and deployed our first distributed cloud-native continuous autograder, which we have continued to use to perform on-demand containerized grading of student Android programming assignments.
  3. Migrated all course backend systems to new server infrastructure running in our own private cloud managed using Kubernetes.

CS 125: Spring 2019
CS 125: Spring 2019

Website // Syllabus // Staff

Enrollment: 459
Format: Synchronous lectures, frequent small assessment
Language: Java

  1. Began work on an initial version of Jeed as an improved backend for the in-class programming examples embedded in the lecture slides.
  2. Improved the test suites for the Android programming assignments.

CS 125: Fall 2018
CS 125: Fall 2018

Website // Syllabus // Staff

Enrollment: 742
Format: Synchronous lectures, frequent small assessment
Language: Java

  1. Created and deployed an initial set of ~60 daily programming exercises to accompany and support the CS 125 course content.
  2. Wrote an additional ~45 small programming exercises to accompany each weekly assessment, marking the first time that every CS 125 quiz included programming questions.
  3. Eliminated the high-stakes final exam, completing a transition to frequent small assessment.
  4. Established a course tutoring center in a dedicated 40-seat room in the basement of the Siebel Center, replacing a woefully undersized office used for the purpose in previous semesters.
  5. Created several new assignments, including an adaptation of a previous photo manipulation assignment to Android, and a molecule-naming assignment using graph traversal, developed with course staff member Ben Nordick.

CS 125: Spring 2018
CS 125: Spring 2018

Website // Syllabus // Staff

Enrollment: 439
Format: Synchronous lectures, high-stakes assessments
Language: Java

  1. Rewrote all lectures to use interactive online materials and integrate participation tracking and in-class programming examples into classroom presentations.
  2. Deployed the first version of what became Jeed to support web-based exploration of Java code snippets through safe and high-speed untrusted code execution.
  3. Completed and deployed continuous assignment autograding.
  4. Deployed the first CS 125 online gradebook.
  5. Developed Java autograding support for PrairieLearn to enable programming questions on weekly quizzes, which had previously been entirely multiple-choice questions.
  6. Introduced Android programming to the course with new labs and assignments.
  7. Held the first ever CS 125 Project Fair, featuring 165 Android projects developed by teams of students.
  8. Moved the final exam to the computer testing center (CBTF), enabling autograded programming questions and reducing staff grading burden.
  9. Updated course development tools, replacing Eclipse with IntelliJ and Subversion with Git and GitHub Classroom.
  10. Began a course developer program with 10 students working on projects including new assignments, a new project fair, plagiarism detection, and data analysis.
  11. Created several new assignments on imperative programming, functions, and Android programming using APIs.

CS 125: Fall 2017
CS 125: Fall 2017

Website // Syllabus // Staff

Enrollment: 698
Co-Instructors: Bill Chapman, Lawrence Angrave
Format: Synchronous lectures, high-stakes assessment
Language: Java

  1. Updated course assignments and infrastructure while Bill Chapman and Lawrence Angrave gave the lectures.
  2. Rewrote and updated all assignments to use a modern build system (Gradle), exhaustive test cases, linter (checkstyle), and modern Java idioms.
  3. Rewrote all lab activities to better match course content and use online (rather than printed) materials.
  4. Designed and deployed a new course website and forum.
  5. Began work on a continuous Git autograder and online grade return system integrated into the course website.
  6. Created several new assignments covering photo manipulation, object-oriented programming, and recursion.
  7. Began work on a fast and safe Java small code execution engine, originally based on the Janino high-speed Java compiler.

University at Buffalo (2011–2016)
University at Buffalo (2011–2016)

During my five years at UB I taught a total of 1150 students—an average of 104 per semester—and offered four different courses to beginning undergraduates, advanced undergraduates and graduate students. Despite being extremely challenging and required for undergraduate computer science majors, my course on computer operating systems was among the most popular in the department and a favorite of both graduate and undergraduate students. My graduate seminar on rotating topics in mobile systems attracted a small group of motivated students and recruited several new Ph.D. students into my group, while giving advanced undergraduates the chance to explore research topics. In Fall 2016 I introduced a new course on the internet to freshman undergraduates.

Courses taught at UB, in reverse chronological order:

My UB online teaching portfolio has information about these and other teaching-related activities at UB. I also have copies of a teaching statement and statements of course effectiveness and improvement that I prepared in 2016.

Curriculum Development
Curriculum Development

Projects
Projects

Please see my projects page or my statement on scholarly activities for more details.

Earlier instructional and research infrastructure from my time at the University at Buffalo:

Publications
Publications

My work spans computer science education and, earlier in my career, mobile systems and wireless sensor networks. Full-text copies of my earlier research publications are available on my previous group’s website, and citation counts are tracked on Google Scholar.

Computer Science Education
Computer Science Education

Mobile Systems (University at Buffalo, 2011–2017)
Mobile Systems (University at Buffalo, 2011–2017)

Wireless Sensor Networks (Harvard, 2004–2010)
Wireless Sensor Networks (Harvard, 2004–2010)

Published under the name Geoffrey Werner-Allen:

Edited Volumes and Book Chapters
Edited Volumes and Book Chapters

Presentations
Presentations

Funding
Funding

Across my career I have received almost $3M in competitive external funding, primarily from the National Science Foundation and Google, most as PI. Full copies of my funded grant proposals are available on my previous group’s website.

Computer Science Education (Illinois)
Computer Science Education (Illinois)

Mobile Systems Research (University at Buffalo)
Mobile Systems Research (University at Buffalo)

Advising
Advising

At the University at Buffalo I graduated one Ph.D. student and supervised 47 other students, including Ph.D. students, Masters students, undergraduates, a visiting Ph.D. student, and the PhoneLab system administrator.

Ph.D. Students
Ph.D. Students

Masters Students
Masters Students

Undergraduates
Undergraduates

Visiting Student and Research Staff
Visiting Student and Research Staff

Service
Service

For more details, please review my service statement.

Illinois
Illinois

University at Buffalo
University at Buffalo

Reviewing
Reviewing

Mentoring
Mentoring

References

  1. Nate Derbinsky, Teaching Professor, Khoury College of Computer Sciences, Northeastern University ([email protected])
  2. Margaret Fleck, Teaching Professor, University of Illinois ([email protected])
  3. Cinda Heeren, Professor of Teaching, University of British Columbia ([email protected])
  4. Margo Seltzer, Canada 150 Research Chair and Professor, University of British Columbia ([email protected])
  5. Tiffani Williams, Teaching Professor and Director of Onramp Programs, University of Illinois ([email protected])
  6. Craig Zilles, Professor, University of Illinois ([email protected])