SearchAPI

SearchAPI is used as a programmatic data acquisition layer for extracting structured information from Google Scholar, enabling automated access to academic search results that would otherwise require manual effort.

In this portfolio, it is applied within research-oriented AI systems, where large-scale collection of paper metadata and references is required.

Key Capabilities

• Programmatic Scholar Search
  Enables automated querying of Google Scholar for papers, authors, and citations.

• Structured Result Extraction
  Returns parsed metadata such as titles, authors, publication venues, and citation counts.

• Scalable Data Collection
  Supports repeated and parameterized queries suitable for pipeline-based ingestion.

• Automation-Friendly Interface
  Designed for integration into data pipelines, agents, and research workflows.

• Downstream Integration Ready
  Outputs can be directly consumed by storage, indexing, or RAG systems.

Experience & Platform Contribution

Used SearchAPI as part of a project focused on automated research discovery and analysis.

Key contributions included:

• Integrating SearchAPI to scrape and collect Google Scholar results programmatically
• Building pipelines to extract paper metadata and citation information
• Feeding retrieved data into downstream systems for indexing and analysis
• Supporting AI-driven workflows that require up-to-date academic references
• Evaluating data quality and consistency for research-focused use cases

SearchAPI served as a practical ingestion tool, enabling scalable access to scholarly data and supporting higher-level systems focused on research synthesis and citation-aware outputs.