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GenAI Productivity: Ideas to project proposal ideas from Google Scholar

From Google Scholar to Project Ideas or Using AI to Map the Future of Your Research



Generated as well by Google Gemini






Have you ever looked at a researcher’s Google Scholar profile and felt overwhelmed? Between the long lists of citations and dense technical titles, "connecting the dots" of a decade-long career is a massive cognitive lift.
Whether you are a student hunting for a dissertation topic or a professional scouting for a collaborator, understanding the trajectory of research is harder than reading the papers themselves.
In my latest experiment, I used Google Gemini to see if it could bridge this gap. I gave it a specific challenge: Analyze my own research profile and design 10 compelling project ideas for a final-year Computer Science student.

The Prompt: Turning Data into Direction

The secret to a good AI output is giving it a clear "anchor." By providing a URL to a live dataset (my Scholar profile), I bypassed the need to copy-paste thousands of words.

Prompt used:  "Using this as a starting point https://scholar.google.com/citations?user=ghQedZAAAAAJ&hl=en from the research here provide 10 project ideas suitable for a final year Computer Science student project with this supervisor. For each provide title, 100 word summary, possible outcomes"


The Results: Beyond Simple Lists
I’ll admit, there was a bit of vanity in using my own profile—but the results were a revelation. Gemini didn't just summarize; it performed a Deep Research analysis. It:
Audited my most cited papers.
Identified my core intellectual "pillars."
Mapped my historical work against 2024–2025 technology trends.
It even "promoted" me to Professor—a hallucination I’m quite happy to live with!
Spotlighting a Project: Robotics & "Physical AI"

One standout suggestion was a project titled: "Robotics Simulation Platform for Experiential Learning." What impressed me wasn't just the idea, but the reasoning. The AI linked my previous work in "Problem Solving and Creativity" with the modern trend of Physical AI—where robots train in virtual environments (like Unity or Gazebo) before entering the real world.
It recognised that real-world robotics is expensive and prone to failure, suggesting a simulator as a way to "democratise" access to advanced AI experimentation for students.

I’ll admit, there was a bit of vanity in using my own profile—but the results were a revelation. Gemini didn't just summarize; it performed a Deep Research analysis. It:
Audited my most cited papers.
Identified my core intellectual "pillars."
Mapped my historical work against 2024–2025 technology trends.
It even "promoted" me to Professor—a hallucination I’m quite happy to live with!
Spotlighting a Project: Robotics & "Physical AI"
One standout suggestion was a project titled: "Robotics Simulation Platform for Experiential Learning." What impressed me wasn't just the idea, but the reasoning. The AI linked my previous work in "Problem Solving and Creativity" with the modern trend of Physical AI—where robots train in virtual environments (like Unity or Gazebo) before entering the real world.
It recognized that real-world robotics is expensive and prone to failure, suggesting a simulator as a way to "democratize" access to advanced AI experimentation for students.

The Power of "Joining the Dots"

The AI identified four key pillars of my career and suggested how they could evolve into the next era of tech:
Research PillarHistorical Focus2025 TrendFuture Direction
AI & RoboticsGenetic AlgorithmsPhysical AIMulti-agent simulations
NetworkingSDN & WebRTCAI-Driven IoTIntelligent network management
Health TechGlucose DetectorsPredictive AnalyticsAI-powered diagnostics
PedagogyTeaching Problem-SolvingIntelligent AutomationAI-driven educational tools

Why This Matters (Beyond the Classroom)

What started as a tool for students turned into a powerful strategic audit for myself. This experiment highlights three massive benefits of Prompt Engineering in academia:
Interdisciplinary Links: The AI saw how my work in robotics could actually inform my research in healthcare—connections I hadn't explicitly made.
Trend Alignment: It identified "Physical AI" as the natural bridge between my teaching and my technical research.
Instant Portability: The entire analysis can be exported to Google Docs in one click, turning a 5-minute prompt into a 10-page strategic roadmap.
The Lesson: Don't just use AI to write; use it to synthesize. The next time you're stuck on "what's next," let the AI look at where you've been to show you where you're going.
A Question for You
If you fed your own LinkedIn or Scholar profile into an LLM and asked it to find your "blind spots," what do you think it would find?
Try the prompt above and let me know the results!

All opinions in this blog are the Author's and should not in any way be seen as reflecting the views of any organisation the Author has any association with. Twitter @scottturneruon
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