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Mihran Siddiqui

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Research AI

An AI-powered app that transforms dense academic papers into bite-sized, scrollable insights for students on the go

Overview

University students and researchers often struggle to access and understand academic papers efficiently. Existing tools are time-consuming, difficult to navigate on mobile, and lack personalization.

 

Research AI addresses this by transforming dense research papers into AI-generated microlearning summaries — concise, scrollable insights that make academic knowledge more accessible, engaging, and mobile-friendly.

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Designed as part of a master’s project, Research AI was nominated for the UX Design Awards 2025, recognizing its potential to simplify how students discover and learn from scholarly content.

UX Designer (Research, IA, Usability Testing)

Role

6 members

Team

12 Weeks (Jan 2025 - April 2025)

Timeline

UX Design Awards 2025

Context

Figma | Miro | Google Forms | Notion | Canva

Tools

I. Background & Motivation

University students and researchers often struggle to find relevant academic papers efficiently. Traditional research tools are time-consuming, inaccessible on mobile, and not adaptive to user needs.
Research AI solves this by offering AI-powered microlearning summaries of academic papers — transforming dense research into bite-sized, personalised insights.

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The Challenge

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  • Slow, fragmented academic search experience

  • Information overload and inaccessible formats

  • Limited mobile usability and personalisation

II. Research

We followed the Double Diamond process — Discover, Define, Develop, Deliver — to ensure decisions were grounded in user needs and validated with evidence.

Primary Research
 

  • Surveys (25 students) to identify pain points in reading and managing research papers.

  • Interviews (8 participants) including students and professors to understand how they search, read, and retain academic content.

  • Key Findings:

    • Researching is time-consuming and overwhelming.

    • Students struggle to filter relevant papers.

    • Academic language and dense layouts reduce motivation.

    • PDFs are difficult to read on mobile devices.

    • Users want faster ways to grasp key insights

Secondary Research
 

  • Accessibility: Only ~3% of scholarly PDFs meet accessibility standards.

  • Microlearning: Improves retention and engagement through short, focused content.

  • Colour Psychology: Warm and soft visuals support comfort and learning focus.

  • Social Media Patterns: Feed-style browsing increases engagement and familiarity.

Secondary Research
 

  • Accessibility: Only ~3% of scholarly PDFs meet accessibility standards.

  • Microlearning: Improves retention and engagement through short, focused content.

  • Colour Psychology: Warm and soft visuals support comfort and learning focus.

  • Social Media Patterns: Feed-style browsing increases engagement and familiarity.

III. Design

Wireframes

After defining the Information Architecture, we began with low-fidelity wireframes to explore layout, navigation, and key interactions. The goal was to make the app simple, efficient, and mobile-first, focusing on how users would move between discovering, reading, and saving research papers.

Early wireframes focused on core sections — Home Feed, Search, Paper Summary, and Library. Through feedback sessions, we realised that some screens felt overcrowded and visually heavy, which led us to simplify layouts, add more white space, and clarify content hierarchy.

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Functional Prototype
 
Once the core flow was validated, we developed a  prototype to test navigation and key interactions in more detail.
This version focused on:
 

  • Testing how users accessed AI summaries and citations.

  • Evaluating the ease of switching between Search, Feed, and Library.

  • Understanding how micro-snippets of text could be displayed effectively on smaller screens.
     

Feedback at this stage highlighted the need for better icon consistency and clearer interaction cues, such as buttons and states for saving or sharing content.

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IV. Usability Testing

To validate the high-fidelity prototype, we conducted usability testing with 10 participants (students and researchers).


Participants were asked to complete key tasks such as searching for a topic, reading an AI summary, asking the AI a question, and saving a paper.

Key Feedback & Findings

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  • The Home Feed felt cluttered, with too much information competing for attention.

  • The “More Insights” button looked like an ad, so users ignored it.

  • Citation management was confusing without visual guidance.

  • Users wanted AI transparency, showing which parts of the paper were summarised.

Design Iterations

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  • Simplified home layout with clearer hierarchy and more breathing room.

  • Redesigned buttons and icons for stronger recognition.

  • Added inline filters and topic tags for discoverability.

  • Introduced highlighted references within AI summaries for better transparency.

  • Streamlined onboarding to explain citation tools clearly.

V. Solution

The final design of Research AI brings together accessibility, microlearning, and AI-powered summarisation into one seamless mobile experience. It focuses on making academic research faster, easier to digest, and more engaging for students and academics with limited time.

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The interface is clean, intuitive, and built around the idea of learning in moments, not hours. Every feature supports focused, credible, and personalised academic exploration.

AI Summaries of Research Papers

The feature uses AI to break down long academic papers into section-by-section summaries — covering the Abstract, Methodology, Results, and Conclusion.


Each summary is short, structured, and visually separated, helping users quickly grasp the relevance of a paper before reading it in full.

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Design Goals:

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  • Reduce the time spent filtering through irrelevant research.

  • Present information in manageable micro-snippets for mobile reading.

  • Maintain transparency with a “View Source Section” link that shows exactly where the summary was derived from in the original paper.

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Chat with AI (Research Assistant)

This conversational feature allows users to ask specific questions about a paper or topic.


The AI responds with context-aware answers, highlighting relevant sentences from the original text.

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Design Goals:

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  • Support deeper understanding without leaving the app.

  • Provide transparency and trust through linked citations and highlighted source text.

  • Offer real-time help during reading or preparation (e.g., before a seminar or presentation).

Microlearning Feed

The Home Feed mimics the scrolling rhythm of social media, but instead of entertainment, it delivers bite-sized research insights and “Did you know?”-style summaries.


Each post presents one focused idea or question derived from real academic research, encouraging curiosity and exploration.

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Design Goals:

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  • Make academic learning feel light, familiar, and engaging.

  • Encourage quick daily learning habits with digestible research content.

  • Reduce cognitive overload by presenting one insight per scroll.

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Full Paper Access & Management

For users who wish to go deeper, every summary card links to the full research paper, viewable or downloadable directly in the app.


The Library section allows users to save, organise, and manage citations efficiently.

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Design Goals:

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  • Bridge microlearning and in-depth reading in one platform.

  • Simplify citation handling with one-click export options (APA, MLA, etc.).

  • Enable offline access for studying without network dependency.

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