Santosh Paidi and Saumya Tiwari Receive SAS Barbara Stull Graduate Student Awards at SciX
The Society for Applied Spectroscopy’s (SAS) Barbara Stull Graduate Student Award was presented to two students this year: Santosh Paidi of Johns Hopkins University and Saumya Tiwari of the University of Illinois at Urbana Champaign.
The Society for Applied Spectroscopy’s (SAS) Barbara Stull Graduate Student Award was presented to two students this year: Santosh Paidi of Johns Hopkins University and Saumya Tiwari of the University of Illinois at Urbana Champaign. The award, presented on October 15 at SciX 2019 in Palm Springs, California, is given to graduate students in honor of longtime SAS employee Barbara Stull, in recognition of outstanding research in the area of spectroscopy.
Paidi is a doctoral student in the Department of Mechanical Engineering at Johns Hopkins, where his current research is in the application of Raman spectroscopy and multivariate data analysis to develop novel quantitative approaches for addressing unmet needs in the molecular study of cancers. Additionally, a major focus of Santosh’s graduate study is the development of a detection framework based on label-free plasmon-enhanced Raman spectroscopy for rapid identification of closely related human and murine antibody drugs during their manufacturing, with the ultimate goal of translation to fill-finish sites. His work has resulted in 13 peer-reviewed publications in various scientific journals.
Tiwari’s PhD in Bioengineering focused on applied spectroscopic imaging and computational analysis under Prof. Rohit Bhargava at the University of Illinois at Urbana-Champaign. She focused her thesis on the development and application of spectroscopic imaging to determine patient outcomes in colon cancer, adding independently to the current clinical information provided by stage and grade. She has also worked on integrating genomic information with spectroscopic data to improve outcomes in surgical resections and on developing applied computational models to analyze spectroscopic imaging data. As the first author of three publications, and an author in several secondary publications, she continues her work on applying spectroscopic data to improve patient health and disease outcomes.
AI, Deep Learning, and Machine Learning in the Dynamic World of Spectroscopy
December 2nd 2024Over the past two years Spectroscopy Magazine has increased our coverage of artificial intelligence (AI), deep learning (DL), and machine learning (ML) and the mathematical approaches relevant to the AI topic. In this article we summarize AI coverage and provide the reference links for a series of selected articles specifically examining these subjects. The resources highlighted in this overview article include those from the Analytically Speaking podcasts, the Chemometrics in Spectroscopy column, and various feature articles and news stories published in Spectroscopy. Here, we provide active links to each of the full articles or podcasts resident on the Spectroscopy website.
Diffuse Reflectance Spectroscopy to Advance Tree-Level NSC Analysis
November 28th 2024Researchers have developed a novel method combining near-infrared (NIR) and mid-infrared (MIR) diffuse reflectance spectroscopy with advanced data fusion techniques to improve the accuracy of non-structural carbohydrate estimation in diverse tree tissues, advancing carbon cycle research.
Mass Spectrometry for Forensic Analysis: An Interview with Glen Jackson
November 27th 2024As part of “The Future of Forensic Analysis” content series, Spectroscopy sat down with Glen P. Jackson of West Virginia University to talk about the historical development of mass spectrometry in forensic analysis.
