Gulf Coast Conference: Kevin Schug Discusses Predicting Gas Phase Vacuum Ultraviolet Spectra
At the 2023 Gulf Coast Conference, Spectroscopy spoke with Kevin Schug of the University of Texas at Arlington, about predicting gas phase vacuum ultraviolet spectra using machine learning. This interview was one of four conducted live at GCC 2023.
Schug spoke during the 2023 Gulf Coast Conference (GCC) in Galveston, Texas, with one of his lectures being titled, "Prediction of Gas Phase Vacuum Ultraviolet Spectra using Machine Learning."
Kevin A. Schug is a Professor and Shimadzu Distinguished Professor of Analytical Chemistry at the University of Texas at Arlington. He received his Ph.D. from Virginia Tech working with the late Professor Harold McNair. He earned a B.S. Chemistry from the College of William and Mary. He has been at the University of Texas at Arlington since 2005.
Spectroscopy sat down with Hagemann to discuss the following questions:
- Can you give us a brief overview of the work you'll be presenting today (00:16–01:24)?
- Why do you believe machine learning to be useful in predicting gas phase vacuum ultraviolet spectra (01:25–03:20)?
- What more research can be done in this space (03:21–04:57)?
- What is the most exciting or interesting part of this research for you (04:58–05:52)?
- Is there anything we're not asking you that you think would be interesting for viewers to know (05:53–06:49)?
- Are there other presentations you are/were excited to see here at GCC (06:50–07:59)?
- What makes GCC significant for the next generation of separation scientists (08:00–09:04)?
Our interview with Schug was one of four conducted live at GCC 2023. For the other published GCC interviews, click on the links below:
Gulf Coast Conference: Elena Hagemann Discusses Using Raman and NIR to Analyze Petrochemicals
Gulf Coast Conference: John Wasson Discusses Data Retrieval From Chemical Processing Plant Streams
Gulf Coast Conference: Jean-Francois Borny Discusses Evolutions in PFAS Analysis
How Satellite-Based Spectroscopy is Transforming Inland Water Quality Monitoring
Published: April 29th 2025 | Updated: April 29th 2025New research highlights how remote satellite sensing technologies are changing the way scientists monitor inland water quality, offering powerful tools for tracking pollutants, analyzing ecological health, and supporting environmental policies across the globe.
Introduction to Satellite and Aerial Spectral Imaging Systems
April 28th 2025Modern remote sensing technologies have evolved from coarse-resolution multispectral sensors like MODIS and MERIS to high-resolution, multi-band systems such as Sentinel-2 MSI, Landsat OLI, and UAV-mounted spectrometers. These advancements provide greater spectral and spatial detail, enabling precise monitoring of environmental, agricultural, and land-use dynamics.
Smarter Sensors, Cleaner Earth Using AI and IoT for Pollution Monitoring
April 22nd 2025A global research team has detailed how smart sensors, artificial intelligence (AI), machine learning, and Internet of Things (IoT) technologies are transforming the detection and management of environmental pollutants. Their comprehensive review highlights how spectroscopy and sensor networks are now key tools in real-time pollution tracking.
New Study Reveals Insights into Phenol’s Behavior in Ice
April 16th 2025A new study published in Spectrochimica Acta Part A by Dominik Heger and colleagues at Masaryk University reveals that phenol's photophysical properties change significantly when frozen, potentially enabling its breakdown by sunlight in icy environments.
