Artificial Intelligence in Spectroscopy: A SciX Interview with Ishan Barman
As a preview to SciX 2023, Spectroscopy magazine sat down with Ishan Barman of Johns Hopkins University to ask him about his thoughts on how artificial intelligence may impact spectroscopic research going forward.
Barman spoke with us before the SciX Conference in Sparks, Nevada, where he is set to give a talk titled, “From Spectroscopy to Solutions: Transformative Biophotonics in Disease Detection and Monitoring,” and accept The Coblentz Society Clara Craver Award as the 2023 recipient on Monday October 9, 2023, at 11:30 am in Sierra 5 at the Golden Nugget Casino in Sparks, Nevada.
Dr. Barman, an Associate Professor at Johns Hopkins University, specializes in Mechanical Engineering, Oncology, and Radiology. He earned his undergraduate degree from IIT Kharagpur and a Ph.D. from MIT, where he pioneered Raman spectroscopy for transcutaneous blood analysis. His work established key techniques for in vivo spectroscopy, addressing issues like tissue turbidity and non-linear chemometric analysis. As a postdoc at MIT, he extended Raman and reflectance spectroscopy to guide breast biopsies and diagnose lesions with microcalcifications. Barman joined Johns Hopkins University in 2014, rising to the position of Associate Professor with tenure in 2019.
In this interview clip, Barman answers the following question:
- In your view, how can artificial intelligence (AI) be used effectively in spectroscopy, and where do you see the application of AI heading in this field?
This interview segment is the first of several conducted in conjunction to the SciX 2023 conference. You can see our latest conference coverage, including our additional video interviews conducted at SciX, at the following link: https://www.spectroscopyonline.com/conferences/scix
Illuminating Robotics and the Role of Optical Sensors in Continuum Robots
March 19th 2025A recent review published in Sensors explores the dynamic field of continuum robotics, with a particular focus on the advances in optical sensing technologies. The study, led by researchers from the Technical University of Košice and the University of Texas at Austin, highlights the dominance of optical fiber sensors in tracking robotic shape perception and environmental interactions, demonstrating spectroscopic applications and future potential.
Smarter Food Processing with AI, Optical Sensors, and Robotics Enhance Quality Control
March 17th 2025Researchers at Oregon State University explore how machine learning, optical sensors, and robotics are transforming food quality assessment and processing, improving efficiency and reducing waste.
