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Analytical Chemistry|November 29, 2024
How Machine Learning and Gas Chromatography-Ion Mobility Spectrometry Form an Optimal Team for Benchtop VolatilomicsHadi Parastar, Philipp WellerAnalytica Chimica Acta|February 13, 2025
Feature selection and extraction strategies for non-targeted analysis using GC-MS and GC-IMS: A tutorialHadi Parastar, Philipp WellerTalanta|February 21, 2024
Benchtop volatilomics supercharged: How machine learning based design of experiment helps optimizing untargeted GC-IMS gas phase metabolomicsHadi Parastar, Philipp WellerFood Chemistry|November 21, 2024
Non-targeted volatilomics for the authentication of saffron by gas chromatography-ion mobility spectrometry and multivariate curve resolutionHadi Parastar, Hassan Yazdanpanah, Philipp WellerAnalytica Chimica Acta|January 20, 2024
Automated 2D peak detection in gas chromatography-ion mobility spectrometry through persistent homologyHadi Parastar, Joscha Christmann, Philipp WellerFood Research International (Ottawa, Ont.)|November 4, 2025
Solvent-based mid-infrared spectroscopy paired with modern machine learning approaches for saffron authenticationHadi Parastar, Linus Busse, Andreas Wolf, et al.Journal of the American Society for Mass Spectrometry|May 12, 2026
Separation of Ammonia Isotopologues by Benchtop Drift Tube Ion Mobility Spectrometry and Chemometric ModelingSeyedali Ghiasi, Thorsten Röder, Stephan Schunk, et al.Analytical and Bioanalytical Chemistry|March 10, 2026
Towards "greener" strategies in quality control: rapid volatilomics of cocoa based on HS-GC-IMS and machine learningLukas Bodenbender, Sascha Rohn, Hadi Parastar, et al.Food Chemistry|December 13, 2025
Benchtop volatilomics and advanced convolutional neural network workflows for accurate and explainable food authenticationFarbod Bayat-Afshary, Nima Naderi Tehrani, Lukas Bodenbender, et al.The Analyst|April 8, 2014
Mutual information concept for evaluation of separation quality in hyphenated chromatographic measurementsHadi ParastarPageof 9