Vinay K. Ingle

Vinay K. Ingle is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University, where he has held a faculty position since 1981. His research focuses on multidimensional signal processing and hyperspectral imaging with applications in defense and security systems.

Education:

• PhD in Electrical and Computer Engineering, Rensselaer Polytechnic Institute, 1981
• MSEE, Illinois Institute of Technology, 1977
• Bachelor of Technology in Electrical Engineering, Indian Institute of Technology

Professor Ingle maintains broad expertise in signal and image processing, stochastic processes, and estimation theory. His current research emphasizes hyperspectral imaging techniques, particularly in long-wave infrared (LWIR) spectrum analysis for threat detection and anomaly identification in sequential imagery. Collaborations with MIT Lincoln Laboratory drive his applied research in temperature-emissivity separation and atmospheric error modeling.

Recent publications (2017-2019) reveal concentrated research in hyperspectral data analysis, specifically addressing calibration challenges, atmospheric interference, and time-series modeling for defense applications. These works demonstrate innovative approaches to temperature-emissivity separation and wavelength calibration in LWIR systems while advancing statistical signal processing methodologies.

Professor Ingle serves as Principal Investigator for multiple MIT Lincoln Laboratory-funded projects including Algorithms for Threat Detection, Anomaly Detection using Low-Rank Modeling, and Hyperspectral Target Detection research. His extensive graduate teaching portfolio indicates significant student mentorship in signal processing disciplines despite no specific advisees being listed in available records.

Research operations are conducted within Northeastern's Electrical and Computer Engineering Department through sustained collaboration with MIT Lincoln Laboratory, focusing on developing next-generation signal processing algorithms for hyperspectral imaging systems in defense contexts.