Three Days Workshop on
Signal and Image Processing with Machine Learning Applications in Astronomy & Astrophysics
Organized by Department of Information Technology, Kannur University &
IUCAA Centre for Astronomy Research and Development (ICARD),
in collaboration with IUCAA (Pune)
Date: 16–18 November 2025
Venue: Department of Information Technology, Kannur University, Kerala – 670567
About Workshop
The workshop “Signal and Image Processing with Machine Learning Applications in Astronomy and Astrophysics”, to be held at the Department of Information Technology, Kannur University in November 2025, aims to train postgraduate students, researchers, and faculty in advanced computational techniques for astronomical data analysis. Over three days, the program will include expert lectures and hands-on sessions on signal and image analysis, noise filtering, object classification, and AI/ML applications in astrophysics. Participants will work with tools like AstroML, Astropy, and Python libraries, while also exploring cross-disciplinary applications in geospatial, medical, and acoustic signal processing. The workshop seeks to foster collaboration with IUCAA experts, strengthen regional capacity in computational astronomy, and build a research network.
Workshop features hands-on sessions focused on signal processing and machine learning applications in astronomy.
Signal Processing:
Participants will explore time-series analysis (1D & 2D) using Fourier transforms, filtering, and Lomb–Scargle periodograms to detect periodic signals like pulsars, exoplanet transits, or gravitational wave–like data. Image processing tasks will include star/galaxy detection, background subtraction, noise reduction, and basic PSF deconvolution using Python tools such as Astropy, scikit-image, and scipy.signal.
Machine Learning:
Building on this, sessions will introduce feature extraction and classification with scikit-learn (e.g., distinguishing stars, quasars, or galaxy morphologies), basic CNNs for image classification with curated datasets, and astronomy-specific ML examples from astroML.
All sessions will be fully hands-on, using Python notebooks and real astronomical datasets (e.g., SDSS images, time series data), providing practical experience in data pre-processing, analysis, and interpretation.
Eligibility
The eligibility for attending the workshop is as follows:
Postgraduate students from Information Technology, Physics, Data Science, Astronomy, and related fields.
Ph.D. scholars whose research aligns with the workshop themes.
Faculty members and teachers from Engineering and Science disciplines with an interest in computational astronomy.
Early-career researchers and college teachers interested in learning astronomical data analysis methods.
Selection will be based on academic performance (PG students), relevance of research (for Ph.D. scholars), and interest/registration order (for faculty and teachers).
Speakers / Resource Person
Prof. Kanak Saha (IUCAA)
IUCAA Coordinator
Prof. Ajit Kembhavi
Professor Emeritus (IUCAA)
Visiting Professor at IUCAA,
Artificial Intelligence Research and Intelligent Systems (airis4D)
Assistant Professor, Post-doctoral Fellow, IUCAA, Assistant Professor, Marthoma College, Chungathara, Nilambur
Assistant Professor, Department of Computer Science, Cochin University of Science and Technology
Dr. R K Sunil Kumar
Local Coordinator, Assistant Professor
Department of Information Technology, Kannur University
Director Centre for Quantum Computing
Selection will be based on academic background and a short statement of interest. There is no registration fee.
Limited seats (~50) are available.
In your application, briefly describe your programming experience and motivation to attend.
Application Opens - September 25, 2025
Application Deadline - October 30, 2025
Notification of Selection - November 1, 2025
Workshop - November 16 -18, 2025
About Dept. of IT
Established in 2000, the Department offers quality education and research in IT with advanced facilities. It began with a 2-year Open Source–based Master’s program and now offers MCA, M.Sc. Computer Science, M.Phil, Ph.D. in Computational Science, PG Diplomas in Data Science & Cyber Security, and a Five-Year Integrated Master’s program. Research areas include Speech & Signal Processing, Image Processing (Medical & Astronomical), Data Mining, NLP, Algorithm Design, Big Data, Active Noise Cancellation, and AI. The Department emphasizes multidisciplinary research and industry-relevant education, producing IT professionals who excel globally.
Contact
For queries, please reach out:
· Dr. R. K. Sunil Kumar (Kannur University) - sunilkumarrk@kannuruniv.ac.in - +91 9447217092
· Prof. Kanak Saha (IUCAA) - kanak@iucaa.in - +91 020 2560 4124
How to Reach Dept. of IT, Kannur University
By Air: Kannur International Airport (35 km away) is well connected to major cities in India and abroad. Taxis and buses are available to reach the campus.
By Train: Kannur Railway Station (15 km away) lies on the Mangalore–Palakkad line with connections across India. Local transport options include taxis, auto-rickshaws, and buses.
By Road: The campus is accessible via NH 66 and is well connected to major towns in Kerala and neighboring states. Regular KSRTC and private buses, taxis, and auto-rickshaws are available from Kannur town.
Explore the Best of Kannur
Paithalmala
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