In this interview clip, Katelynn Perrault Uptmor, an assistant professor of chemistry at the College of William & Mary, in Williamsburg, Virginia, discusses winning the Emerging Leader in Chromatography Award and her upcoming talk tomorrow.
On Tuesday March 4th, starting at 8:30 am, the LCGC International Awards Symposium will take place in Room 211 at Pittcon 2025. During the symposium, LCGC International associate editorial director, Caroline Hroncich, will present Katelynn Perrault Uptmor, an assistant professor of chemistry at the College of William & Mary, in Williamsburg, Virginia, with the Emerging Leader in Chromatography Award.
Perrault Uptmor’s recent work has focused on using multidimensional gas chromatography (GC) in forensic chemistry and odor analysis (1). Using multidimensional GC technology, Perrault Uptmor has shown how volatile organic compounds (VOCs) can be identified (1). Her 2022 paper presented an open-access approach that can handle complex GC×GC data processing without costly software, making this approach more accessible for resource-limited laboratories (1). She has also advanced forensic science by translating GC–mass spectrometry (GC–MS) systems into GC×GC setups for complex sample analysis (1). Additionally, her efforts to integrate GC×GC into undergraduate curricula have positioned her as a leader in chromatography education (1).
During this symposium, Perrault Uptmor will deliver a talk at 10:40 am titled, “Retroactive Curiosity Within Your Data: Asking Your Multidimensional Gas Chromatographic Samples Different Questions.” Her talk will highlight the power of comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC–TOF-MS) to extract deeper insights from complex samples (2).
GC×GC–TOFMS offers improved peak capacity and enhanced detectability, allowing researchers to obtain a full analyte profile and making it possible to address research questions more effectively than traditional one-dimensional GC–MS (2) techniques. Beyond initial analyses, the extensive data sets generated by this technique can be retroactively mined to uncover additional information. Perrault Uptmor’s talk will focus on data processing strategies for analyzing food and forensic samples, and demonstrate how statistical approaches can be applied to maximize data utility (2).
In this short interview clip, Perrault Uptmor answers the following questions: