🎓 Research Like a Pro: Hands-on Workshop on Building Research Mindset and Skills through Reproducibility
📅 Date: Friday, October 24 from 11 AM until 2 PM
🏛 Hosted by: CIS Department & ACM Student Chapter
📍 Location: Kochoff Hall A, University Center, 4901 Evergreen Rd, Dearborn, MI 48128
💡 Overview
Curious how researchers design experiments, validate results, and tackle complex problems?
Join us for the CIS Reproducibility Workshop — a hands-on event where you’ll explore, experiment, and present your findings alongside peers and faculty.
This workshop helps you develop critical thinking, collaboration, and research resilience — the essential skills that define successful scholars and innovators.
🔹 What’s Inside
🎙 Faculty Panel (30 min)
Hear insights on research design, validation, and communication from:
- Dr. Khouloud Gaaloul
- Dr. Foyzul Hassan
- Dr. Anwar Ghammam
- Dr. Utkarshani Jaimini
- Dr. Niccolò Meneghetti
- Moderated by Dr. Probir Roy
🧠 Hands-on Workshop (90–120 min)
Work in small groups to reproduce and analyze selected results from faculty-nominated research papers.
Experience the challenges and creativity involved in validating scientific results.
🗣 Student Presentations (30–40 min)
Present your:
- Research problem of interest
- Reproduced results and observations
- Lessons learned during the process
⏱ Program Outline (Durations)
- Faculty Panel: ~30 min
- Hands-on Workshop Session 1: ~60 min
- Lunch Break: ~15 min
- Hands-on Workshop Session 2: ~40 min
- Student Presentations: ~25 min
- Closure: ~10 min
🧩 Workshop Proposals & Tracks
Participants will work in small groups to reproduce results from one of the following faculty-nominated research papers.
Each project provides hands-on experience with different aspects of reproducible research.
🔍 Proposal 1: ProRCA
Proposed by: Dr. Utkarshani Jaimini
Paper: ProRCA: A Causal Python Package for Actionable Root Cause Analysis in Real-world Business Scenarios
Skills You’ll Develop
- Apply causal inference techniques in practice
- Design reproducible pipelines and inject controlled anomalies
- Interpret and validate causal results
Student Tasks
- Investigate whether anomaly injection reveals true causal links
- Evaluate how reproduced results align with the paper’s claims
- Reflect on discrepancies and what they reveal about reproducibility
Resources
⚙️ Proposal 2: EvoSuite
Proposed by: Dr. Khouloud Gaaloul
Paper: EvoSuite: Automatic Test Suite Generation with Defects4J
Skills You’ll Develop
- Use automated test generation tools
- Measure coverage and mutation metrics
- Benchmark test effectiveness
Student Tasks
- Compare EvoSuite and Randoop test quality
- Evaluate coverage and mutation scores
- Reflect on tool differences and reproducibility
Resources
🤖 Proposal 3: Quality Assessment of ChatGPT-Generated Code
Proposed by: Dr. Anwar Ghammam
Paper: Quality Assessment of ChatGPT-Generated Code and their Use by Developers
Skills You’ll Develop
- Run static analysis tools (Pylint, Bandit, CodeQL)
- Interpret software quality metrics
- Conduct empirical software engineering
Student Tasks
- Investigate systematic issues in ChatGPT-generated code
- Evaluate static analysis findings across languages
- Reflect on differences from the paper’s conclusions
Resources
🧠 Proposal 4: SpecRover
Proposed by: Dr. Foyzul Hassan
Paper: SpecRover: Code Intent Extraction via LLMs
Skills You’ll Develop
- Orchestrate multi-agent LLM workflows
- Infer code intent using SWE-bench datasets
- Extend experimental pipelines
Student Tasks
- Investigate whether multi-agent systems infer developer intent
- Evaluate generated patch performance
- Reflect on challenges in scaling LLM-based repair
Resources
🧪 Proposal 5: InfiniFilter
Proposed by: Dr. Niccolò Meneghetti
Paper: InfiniFilter: Expanding Filters to Infinity and Beyond
Skills You’ll Develop
- Debug and configure research environments
- Reproduce algorithmic benchmarks
- Analyze reproducibility trade-offs in data systems
Student Tasks
- Investigate reproducibility of InfiniFilter results on modern hardware
- Evaluate reproduced plots vs. originals
- Reflect on environmental effects on reproducibility
Resources
🌍 Open to Everyone
This workshop welcomes all students, faculty, and research enthusiasts — regardless of background or experience.
If you’re curious about how research works, this is your chance to learn by doing and connect with the CIS research community.
RSVP REQUIRED
For questions, please reach out to the ACM Student Chapter
📧 acm@umdearborn.edu
⭐ Join Us
Don’t just read about research — do it!
Let’s build a culture of openness, rigor, and reproducibility in CIS research together.
🧭 What’s Next?
Already registered? Great!
Before the workshop:
- Review the five papers listed above.
- Pick one you’d like to work on.
- Try setting up its artifact or code on your laptop or cloud service.
- Make sure you have Python 3.8+, Git, and any required tools installed.
💼 At the Workshop — What to Bring
- Your Own Laptop (no devices provided)
- Power Cord / Charger
- Pre-installed dependencies (Python, IDE, required libraries)
- Curiosity and teamwork!