{"slug": "research-highlighter-matchmaker-project", "title": "Research Highlighter-MatchMaker Project", "summary": "The University at Albany (SUNY) developed the Research Highlighter-MatchMaker Project, an NLP-driven software platform that matches researchers with funding opportunities and collaborators through a searchable portal and automated email recommendations. The system offers three search functions — \"Search By Name,\" \"Search By Topic,\" and \"Search By Text\" — and integrates publication data from the Scopus API and funding opportunity data from the SPIN API. The platform aims to address fragmented, manual funding searches that disproportionately affect early-career researchers and graduate students.", "body_md": "This technology uses AI and natural language processing to analyze research data, helping researchers find funding, identify collaborators, and group by research topics through a searchable portal and automated email recommendations.\n\nIn academic and research institutions, the ability to efficiently connect researchers with relevant funding opportunities and potential collaborators is crucial for fostering innovation and advancing scientific discovery. The field of research administration has seen a growing emphasis on leveraging digital tools and data-driven approaches to streamline these processes. As the volume of research output and the diversity of funding sources continue to expand, researchers and administrators face increasing challenges in navigating complex databases, identifying suitable grants, and building interdisciplinary teams. The need for intelligent systems that can analyze vast amounts of research data and provide personalized recommendations has become more pronounced, especially as competition for funding intensifies and collaborative, cross-disciplinary research becomes more essential. Current approaches to matching researchers with funding and collaboration opportunities are often fragmented and inefficient. Traditional methods typically rely on manual searches through funding databases, institutional newsletters, or word-of-mouth, which can be time-consuming and may overlook relevant opportunities. Many existing systems lack the ability to process unstructured data, such as research abstracts or proposals, and do not integrate seamlessly with publication records or external funding databases. As a result, researchers may miss out on critical funding or collaboration prospects, and institutions may struggle to form effective research clusters. Furthermore, these limitations disproportionately affect early-career researchers and graduate students, who may not yet be fully integrated into institutional databases or networks, thereby hindering their access to vital resources and connections.\nThe Research Highlighter-MatchMaker Project is a software platform developed at the University at Albany (SUNY) that leverages advanced Natural Language Processing (NLP) to streamline research collaboration and funding discovery. Through a user-friendly front-end portal, the system offers three main search functionalities: \"Search By Name\" provides tailored funding recommendations based on a researcher’s profile; \"Search By Topic\" groups researchers by specific research areas to facilitate collaboration; and \"Search By Text\" allows users to receive funding suggestions based on arbitrary input, such as research proposals or abstracts. The platform integrates publication data from the Scopus API and funding opportunity data from the SPIN API, ensuring up-to-date and comprehensive information. Additionally, an automated email listserv regularly delivers personalized funding recommendations to researchers, further enhancing engagement and opportunity awareness. What differentiates this technology is its holistic and flexible approach to research support, combining robust data integration with intelligent, NLP-driven analysis. Unlike traditional systems that may rely solely on keyword matching or manual curation, this solution dynamically analyzes the full context of research activities, enabling more accurate and relevant recommendations. Its multi-modal search capabilities cater to a wide range of users, from established faculty to graduate students and external collaborators, making it highly inclusive. The system’s extensible architecture also allows for future integration of additional research-related data, such as technology transfer agreements and compliance documents, positioning it as a comprehensive tool for fostering interdisciplinary collaboration and maximizing funding opportunities within academic environments.\n\n*Photo for reference only, not a depiction of the invention.*\n \n•    Efficiently matches researchers with relevant funding opportunities based on their research history and interests.\n\n•    Identifies research clusters and suggests potential collaborations to foster interdisciplinary partnerships.\n\n•    Offers flexible search options including by researcher name, research topic, and arbitrary text input for broad usability.\n\n•    Integrates comprehensive data from Scopus (publications) and SPIN (funding opportunities) APIs for up-to-date recommendations.\n\n•    Automates personalized funding recommendations via an email listserv, saving researchers time and effort.\n\n•    Supports a wide range of users including faculty, researchers, graduate students, and external collaborators.\n\n•    Designed for extensibility to incorporate additional research-related data sources in the future.\n•    Automated funding opportunity matching\n\n•    Researcher collaboration identification\n\n•    Topic-based researcher discovery\n\n•    Personalized research funding alerts\nPatent Pending\nTRL = 3\nThis technology is available for licensing.", "url": "https://wpnews.pro/news/research-highlighter-matchmaker-project", "canonical_source": "https://suny.technologypublisher.com/tech/Research_Highlighter-MatchMaker_Project", "published_at": "2026-09-11 12:51:15+00:00", "updated_at": "2026-09-19 13:53:38.859830+00:00", "lang": "en", "topics": ["natural-language-processing", "artificial-intelligence", "ai-tools"], "entities": ["University at Albany (SUNY)", "Research Highlighter-MatchMaker Project", "Scopus API", "SPIN API"], "alternates": {"html": "https://wpnews.pro/news/research-highlighter-matchmaker-project", "markdown": "https://wpnews.pro/news/research-highlighter-matchmaker-project.md", "text": "https://wpnews.pro/news/research-highlighter-matchmaker-project.txt", "jsonld": "https://wpnews.pro/news/research-highlighter-matchmaker-project.jsonld"}}