Virginia Tech Researcher Explores Innovation Trends with Machine Learning
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Virginia Tech graduate student Shehryar Khan is applying machine learning to a growing challenge in research and innovation: the sheer volume of patent data. The number of granted patents annually has more than doubled in the last 15 years, making it increasingly difficult for experts to assess the novelty of new ideas, prompting Khan to explore automated solutions. Working with the University Libraries’ research impact and intelligence team, Khan’s research focuses on optimizing systems to make research information more organized and accessible, ultimately deriving meaningful insights from complex data. “My work focuses on optimizing and building systems that make research information more organized, accessible, and accurate,” Khan said, and added, “I like to say I do ‘research in research.’” This emerging work, intended for publication with Khan as first author, seeks to leverage models like ChatGPT to generate novel patent ideas while avoiding existing concepts.
Machine Learning Applied to Patent Data & Innovation Trends A surge in patent applications, more than doubling over the past 15 years, is driving demand for new methods to assess the true novelty of inventions, and researchers are increasingly turning to machine learning for solutions. “We are researching how to push models like ChatGPT to produce new ideas. To attempt this, we aim to ask these models to generate patents for us but avoid ideas that already exist,” Khan said, highlighting the challenge of moving beyond simple predictive algorithms. This approach addresses a critical gap in current AI research, as models are often perceived as merely extrapolating from existing knowledge. Sarah Over, Assistant Director for Research Intelligence, emphasizes the broader significance of this work for Virginia Tech. “Virginia Tech needs to keep advancing within fields like machine learning and AI,” she stated, noting that analyses of patents complement other research initiatives within the University Libraries. A forthcoming publication, with Khan as first author, will detail his findings on evaluating novelty in patent submissions, building on a conference paper currently undergoing peer review. Khan’s Research at Virginia Tech’s Institute for Advanced Computing Shehryar Khan’s work at Virginia Tech’s Institute for Advanced Computing is focused on extracting order from the rapidly expanding volume of patent data, a challenge increasingly critical as the pace of innovation accelerates. The project aims to move beyond simple predictive text generation, a common criticism of large language models. This approach addresses a critical need to determine if a proposed invention truly represents a novel contribution, a task complicated by the sheer scale of existing intellectual property. Khan’s work isn’t merely academic; it’s intended to bridge the gap between theoretical machine learning and practical application. Virginia Tech needs to keep advancing within fields like machine learning and AI [artificial intelligence]. Evaluating Novelty in Patents via Machine Learning Models Assistant Director for Research Intelligence, Sarah Over, notes that “granted patents per year have more than doubled over the past 15 years,” creating a significant challenge for experts attempting to stay abreast of innovation. Khan believes this represents a combination of intellectual property, research evaluation, and advanced computing. Ultimately, the goal is to create systems that can not only organize and access research information but also derive “meaningful insights from very messy data sources,” as Khan puts it, furthering understanding of innovation trends and research impact. Virginia Tech was an obvious choice for my interests, especially applied machine learning. Source: https://news.vt.edu/articles/2026/02/univlib-shehryar-khan-profile.html Tags: Quantum News There is so much happening right now in the field of technology, whether AI or the march of robots. Adrian is an expert on how technology can be transformative, especially frontier technologies. But Quantum occupies a special space. Quite literally a special space. A Hilbert space infact, haha! Here I try to provide some of the news that is considered breaking news in the Quantum Computing and Quantum tech space. Latest Posts by Quantum News: IonQ Collaborates with Qollab to Expand Quantum Literacy and Innovation March 18, 2026 Xanadu Demonstrates Quantum Computing Approach for High-Capacity Battery Analysis March 18, 2026 Linköping University Researchers Enable Qubit Functionality in Perovskites March 18, 2026