The New York Section (New Jersey) of the Society for Applied Spectroscopy (SAS) is the first and oldest spectroscopy networking organization in the United States.  We were formed during World War II, before the parent organization of SAS. Our first Gold Medal Award symposium was awarded to Dr. William F. Meggers in 1952.  The local section provides a forum for practicing spectroscopists to interact, lead, and share insights that can benefit their respective organizations.  Monthly meetings feature research presentations from academia, government, and industry, and provide members with opportunities to expand their knowledge and application of vibration, electronic, and atomic spectroscopy. For more information, click on the "About NYSAS" page.

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SAS Virtual Webinar

SAS Virtual Seminar – Thursday, September 17, 2026, 12:00 – 1:00 PM EDT

Advances in Photothermal Mid-infrared Spectroscopic Imaging for Biomedical Diagnostics and Translational Applications

Speaker: Professor Rohith Reddy│ University of Houston

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Members: Free | Non-Members: $20

The registration page is: 

https://sas.memberclicks.net/2026septemberdistinguishedspectroscopistlecture?servId=20214#

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ABSTRACT

Advances in vibrational spectroscopy enable molecularly specific analysis of biological tissues without exogenous labels, creating new opportunities for objective disease detection and grading. Mid-infrared spectroscopic imaging (MIRSI) is particularly powerful because it combines the chemical specificity of infrared absorption with spatially resolved microscopy. When integrated with machine learning, MIRSI can provide quantitative tissue classification and reveal biochemical and structural changes that may be difficult to recognize with conventional histopathology alone.

This lecture will highlight our recent advances in photothermal MIRSI, which offer improved spatial resolution, sensitivity, and experimental flexibility. We demonstrate the utility of these approaches in several challenging biomedical applications. In lupus nephritis, spectroscopic imaging reveals subtle molecular alterations associated with early-stage renal involvement. In ovarian cancer, high-resolution photothermal MIRSI enables tissue segmentation and discrimination of malignant regions, with potential relevance to tumor-margin assessment. In bone marrow disease, spectroscopic signatures serve as markers of osteosclerotic changes, while polarization-sensitive photothermal MIRSI maps collagen organization and fiber orientation, providing complementary structural information for assessing and grading fibrosis.

A major challenge in translating spectroscopic imaging to the clinic is achieving sufficiently high acquisition speed without sacrificing chemical information. To address this limitation, we are developing high-speed mid-infrared frequency-comb approaches, including photothermal dual-comb microscopy, that increase spectral throughput by more than an order of magnitude. We are also pursuing miniaturized photothermal MIRSI platforms to improve portability and facilitate translation beyond specialized laboratory environments.

Together, these developments demonstrate how advances in spectroscopy, microscopy, polarization-resolved measurements, frequency-comb technology, and machine learning can converge to enable rapid, label-free, and chemically specific tissue characterization. Such integrated approaches could advance early disease detection, quantitative pathology, and more precise assessment of disease progression.

BRIEF BIOGRAPHY

About the Distinguished Spectroscopist Invited Lecture

The Society for Applied Spectroscopy (SAS) Distinguished Spectroscopist Invited Lecture Series is a quarterly program where the Society selects distinguished experts to present their research to members of the Society and affiliated students and scientists. Speakers are chosen for their significant contributions to the field of spectroscopy and their ability to engage both students and professionals. The series bridges the gap between industry and academia, providing industrial scientists and students with exposure to real-world spectroscopic applications and fundamental contributions. Speakers may be invited from the pool of SAS Fellows, recipients of prestigious spectroscopy awards, or authors of significant work published in Applied Spectroscopy or Applied Spectroscopy Practica. The lectures shall be delivered virtually and will be available for on-line streaming, post presentation.

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NY/NJ Monthly Meetings are FREE Zoom Meetings open to all International SAS Members and interested Scientists

Invited Seminar – Thursday, August 20, 2026, 12:00 – 1:00 PM EDT

KNNR in the Wild: Nonlinear Neighborhoods that Outperform PLS (Sometimes)

Speaker: Dr. David Honigs │ PerkinElmer, Perten Division

Join Zoom Meeting (See Meeting Details Below)

https://us02web.zoom.us/j/89243994684?pwd=YJzX44JdegRJHYPyIvtxJ9xMEHqsF8.1

ABSTRACT

K-Nearest Neighbor Regression (KNNR) isn’t new—but applying it to high-dimensional NIR spectral data in real-world conditions reveals surprising strengths. In this work, we examine cases where KNNR outperforms Partial Least Squares (PLS), not by modeling global latent structure, but by embracing local, resilient patterns that align more closely with how samples vary in practice.

Unlike PLS, which attempts to project the entire dataset into a compressed, linear latent space, KNNR responds to structure in immediate spectral neighborhoods. This approach proves effective when the sample space is irregular, noisy, or distorted by calibration transfer, ingredient variability, or instrument drift. In such cases, global structure may be misleading—while local relationships retain predictive power.

We explore examples across typical applied environments—ranging from food production to agricultural materials—where KNNR holds its own or surpasses PLS in predictive accuracy, stability, or adaptability. Rather than proposing KNNR as a universal replacement, we highlight it as a practical and complementary alternative that thrives under specific conditions where PLS begins to stretch or overgeneralize.

What emerges is a model selection story grounded in behavioral observation rather than theoretical purity. When KNNR and PLS disagree, it often points to something deeper: nonlinear variation, clustered domains, or edge cases where local modeling sees what global methods blur. The differences aren’t noise—they are signals worth examining.

This presentation offers a technical overview of KNNR behavior in spectral applications, key comparative performance results, and guidance on when to include KNNR in the calibration stack. Our findings suggest that KNNR, often overlooked in chemometric circles, deserves renewed attention—not as a throwback, but as a tool perfectly suited for spectral data that doesn't play by linear rules.

BRIEF BIOGRAPHY

Zoom Meeting Details

Topic: Dr. David Honigs - KNNR in the Wild: Nonlinear Neighborhoods that Outperform PLS (Sometimes)

Time: Aug 20, 2026 12:00 PM Eastern Time (US and Canada)

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