AI-Powered Academic Research Professor Discovery & Tailored Cold Email Generator
ResearchMatch Lite bridges the gap between ambitious students seeking research internships and leading faculty members across India's premier technical institutes (IITs, IIITs, NITs, and IISc).
By analyzing your resume, skills, and project portfolio, ResearchMatch Lite identifies professors whose active research agendas closely align with your background, and automatically crafts individualized, high-converting cold email drafts.
- Skill & Domain Extraction: Ingests your resume to identify technical competencies, past internships, academic projects, and primary research domains (NLP, Computer Vision, Speech Processing, Biomedical AI, Systems, etc.).
- Instant Preload Option: Includes a realistic reference student profile to test and explore the recommendation engine immediately.
- Tier-Categorized Selection: Targets faculty across Top Old IITs (Bombay, Delhi, Madras, Kanpur, Kharagpur, Roorkee, Guwahati), Newer IITs (Ropar, Hyderabad, Gandhinagar, Indore, Bhilai, Palakkad, Tirupati, Mandi, Patna), Top IIITs (Hyderabad, Bangalore, Delhi, Allahabad, Sri City, Gwalior), and Top NITs (Trichy, Surathkal, Calicut, Warangal, Rourkela, SVNIT Surat).
- Exact Boundary Isolation: Employs normalized boundary matching to eliminate false-positive collisions (strictly distinguishing IIT vs. IIIT, and SVNIT Surat vs. NIT Surathkal).
- Interactive Multi-View Tabs: Switch seamlessly between all selected institutions or drill down into per-institute recommendations with live match counts.
- Comprehensive Seed Faculty Database: Pre-indexed profiles of professors with lab affiliations, designations, official websites, and research keywords.
- Dynamic Web Directory Aggregator: Queries live faculty portals to surface active lab heads and newly recruited tenure-track faculty.
- Gemini-Powered Semantic Scoring: Leverages Google Gemini AI to analyze overlap between candidate research publications and student technical experience, scoring each match with explicit rationale.
- Personalized Professor Intro: Addresses each professor by title, department, institution, and their exact research focus.
- Proven Model Mail Body: Seamlessly incorporates core student highlights:
- Summer research internship at IIT Ropar with annam.ai ("Krishi Darshan" speech-to-text pipeline processing 74 Hindi agricultural videos).
- FLN Assessment & Personalized Worksheet Platform for Classes 2–4.
- Research poster presentation on Multispectral Wound Diagnostics at Innovación 2026 (IEM Kolkata).
- Dynamic Alignment Connector: Adapts Paragraph 2 based on the professor's exact domain:
- NLP & Speech: Connects Indic speech datasets, ASR automation, and model formatting.
- Biomedical AI & Health: Highlights spectral tissue diagnostics and clinical imaging data.
- Computer Vision: Highlights multi-modal pipelines and large-scale video processing.
- IIT Ropar Faculty: Leverages on-campus familiarity with IIT Ropar computing clusters and lab ecosystem.
- Distributed Systems & Cloud: Emphasizes pipeline throughput, data ingestion, and scalable workflows.
- One-Click Actions: Copy subject line, copy full body, or open directly in your desktop/web mail client with prefilled
mailto:headers.
- Export matched faculty lists with research keywords, match scores, and contact emails to CSV.
- Filter results dynamically by minimum match score, institute tier, and target university.
researchmatch-lite/
├── src/
│ ├── components/
│ │ ├── ProfessorCard.tsx # Faculty card with match rationale & email generator modal
│ │ ├── ProfileViewer.tsx # Student resume profile overview and editable fields
│ │ ├── ResumeUploader.tsx # Resume text/file ingest and parsing trigger
│ │ ├── SearchProgress.tsx # Live status indicators during discovery & ranking
│ │ └── TargetInstitutesStep.tsx # Interactive multi-select institute selection grid
│ ├── data/
│ │ └── seed-professors.ts # Curated faculty directory across premier institutes
│ ├── utils/
│ │ ├── coldEmailGenerator.ts # Faculty-tailored cold email synthesis logic
│ │ └── instituteMatcher.ts # Type-aware institution string matching & normalization
│ ├── App.tsx # Main single-page application workflow & filters
│ ├── main.tsx # React root entry point
│ ├── types.ts # TypeScript data contracts & schemas
│ └── index.css # Tailwind CSS v4 entry point
├── server.ts # Express backend proxy for Gemini AI & web directory discovery
├── metadata.json # Application metadata and runtime permissions
├── vite.config.ts # Vite build configuration
└── package.json # Scripts & dependencies
- Frontend: React 19, TypeScript, Tailwind CSS v4, Lucide React, Motion
- Backend: Express 4, Cheerio, tsx, esbuild
- AI Intelligence: Google Gen AI SDK (
@google/genai) powered by Gemini models
- Node.js: v18.0.0 or later (v20+ recommended)
- npm: v9.0.0 or later
- Gemini API Key: From Google AI Studio
-
Clone or Download the Repository:
git clone https://github.com/your-username/researchmatch-lite.git cd researchmatch-lite -
Install Dependencies:
npm install
-
Configure Environment Variables: Create a
.envfile in the root directory (based on.env.example):GEMINI_API_KEY="your_actual_gemini_api_key_here" APP_URL="http://localhost:3000"
-
Start Development Server:
npm run dev
Open your browser and navigate to
http://localhost:3000.
To compile the React frontend and bundle the Express backend into a standalone distribution:
# Build client and server bundle
npm run build
# Start production server
npm startIf you are running this project inside Google AI Studio:
- Click the Export or Settings menu at the top right of the workspace.
- Select Export to GitHub (or Download ZIP).
- Authenticate with your GitHub account and choose your target repository.
- AI Studio will automatically commit this complete codebase together with this
README.md.
This project is licensed under the MIT License.