IMAGING DAYS 2026

2026 im days

Imaging Days once again will bring together researchers, students, and industry professionals to share ideas, discover the latest findings in imaging, and strengthen collaborations across academia and industry. Register and join us!

Register HERE. Note registration is binding. To use effectively resources, please, cancel your registration beforehand if you cannot attend by sending an email to imaging@tuni.fi

Technical programme, TB104, Hervanta, Tietotalo

12:00 — 12:05 Opening, Prof. Alessandro Foi, Director of the Imaging Platform, Signal Processing Research Centre, Tampere University.

12:05 – 12:50 IEEE SPS Distinguished Industry Speaker: Audio Signal Processing in the Era of AI, Dr. Ivan Tashev, Partner Software Architect at Microsoft Research, Washington, USA.

đź“„Abstract

In this talk, we will discuss the general architecture of speech enhancement pipelines for hands-free telecommunications and distant speech recognition. We will then explore audio signal processing applications for audio rendering and analytics. The talk will cover both classical statistical signal processing techniques and modern discriminative and generative AI approaches. We will examine the role of audio experts in the era of AI and look ahead to emerging technologies and applications of AI in audio signal processing. The concepts will be illustrated with real-world examples from the speech enhancement pipelines used in Kinect, HoloLens, and Teams.

12:50 — 13:05 Dr. Brendt Wohlberg, Los Alamos National Laboratory, USA. Further details to appear later.

13:05 — 13:20 Prof. Giacomo Boracchi, Politecnico di Milano, Italy. Further details to appear later.

13:20 — 13:45 Coffee break

13:45 — 14:30 IEEE Photonics Society Distinguished Lecturer: From Photons to Information: Co-designed Imaging Systems for Seeing More, Prof. Rajesh Menon, University of Utah, USA.

đź“„Abstract

Conventional cameras capture only a small fraction of the information carried by light. Rich properties such as spectrum, polarization, depth, coherence, and fast temporal dynamics are typically discarded, or require bulky instruments and sequential measurements to recover. In this talk, I will describe a different approach to imaging in which photonics, sensors, and computational algorithms are designed together to capture much more of the information available from a scene. Inverse-designed and unconventional optical elements can encode otherwise inaccessible physical information directly into sensor measurements, while computational methods, including machine learning, decode these measurements into high-dimensional images. When combined with emerging sensor technologies such as event-based cameras, this approach can also capture dynamics at timescales far beyond those accessible to conventional frame-based imaging. I will present examples spanning spectral and polarization imaging, ultrafast sensing, computational microscopy, and compact flat-optics systems, with applications ranging from biomedical imaging and industrial inspection to remote sensing and astronomy. More broadly, these results point toward a transition from cameras designed primarily to form images to information-aware imaging systems that jointly optimize the physics and computation for the information (or task) that ultimately matters. Such systems offer new opportunities to dramatically reduce size, weight, power, data volume, and latency while expanding what cameras can measure.

14:30 — 14:45 Image Denoising in Multiplicative Noise, Prof. Chandra Sekhar Seelamantula, Indian Institute of Science, India.

14:45 — 15:00 Machine Learning and Visual Texture Analysis, Prof. Thrasyvoulos N. Pappas, Northwestern University, USA.

15:00 — 15:15 Closing

Social programme

15:30 — 17:30 Suolijärven sauna

18:00 — 20:00 Get together and snack in TC428, working-cafe