IEEE UK & Ireland Signal Processing Society Seminar "Age of Data: A Personal Journey", Professor Asoke K. Nandi (Event SPS-2025-02)

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The IEEE UK&I Signal Processing Society Chapter is pleased to continue its invited speaker seminar series, as part of this year’s Signal Processing Day 2025. Established in 2023 and celebrated annually on 2 June, SPS Day commemorates the date that the IEEE Signal Processing Society (SPS) was established in 1948. For this special occasion, we are honoured to welcome Professor Asoke K. Nandi, from Brunel University London, who will reflect on the transformative impact of data, machine learning, and signal processing over the past two decades.

The IEEE UK&I SPS Chapter Seminar Series aims not only to explore cutting-edge technical topics, but also to showcase ongoing activities and opportunities across leading UK research groups, institutes, and centres of excellence. We also provide brief updates on upcoming IEEE UK&I SPS Chapter events.

We hope these events will contribute to refreshing and building a UK signal processing research map, and as part of SPS Day we will join other Signal Processing Society members and Chapters around the world by gathering at local events to connect and collaborate with our communities to advance the SPS mission and fields of interests.

Presentation Abstract:

In the last two decades we have become rich in data. With the availability of faster computers, cheaper data storage, cheaper computer memory, pervasive networks, signal processing, and machine learning, the world has possibly begun a new technological revolution. A new subject, Data Science, was born. This transition did not happen in a short time; it has been, and continues to be, a journey. This lecture will attempt to highlight a few of the topics that are part of this revolution from a personal perspective, identifying some of the developments and including the use of machine learning. 

Please register for the event using the following Registration Link


  Date and Time

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  • Date: 02 Jun 2025
  • Time: 12:30 PM UTC to 02:30 PM UTC
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  • Brunel University of London
  • London, England
  • United Kingdom UB8 3PH
  • Building: Bannerman Building
  • Room Number: BANN 019g
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  Speakers

Asoke K. Nandi

Topic:

Age of Data: A Personal Journey

In the last two decades we have become rich in data. With the availability of faster computers, cheaper data storage, cheaper computer memory, pervasive networks, signal processing, and machine learning, the world has possibly begun a new technological revolution. A new subject, Data Science, was born. This transition did not happen in a short time; it has been, and continues to be, a journey. This lecture will attempt to highlight a few of the topics that are part of this revolution from a personal perspective, identifying some of the developments and including the use of machine learning. 

Biography:

Professor Nandi received the PhD degree in Physics from the University of Cambridge (Trinity College). He held academic positions in several universities, including Oxford, Imperial College London, Strathclyde, and Liverpool as well as Finland Distinguished Professorship. In 2013 he moved to Brunel University of London.

In 1983 Professor Nandi co-discovered the three fundamental particles known as W+, W− and Z0, providing the evidence for the unification of the electromagnetic and weak forces, for which the Nobel Committee for Physics in 1984 awarded the prize to two of his team leaders for their decisive contributions. His current research interests lie in signal processing and machine learning, with applications to machine health monitoring, functional magnetic resonance data, gene expression data, communications, and biomedical data. He made fundamental theoretical and algorithmic contributions to many aspects of signal processing and machine learning. He has much expertise in “Big Data”. Professor Nandi has authored over 650 technical publications, including 300 journal papers as well as six books, entitled Image Segmentation: Principles, Techniques, and Applications (Wiley, 2022), Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines (Wiley, 2020), Automatic Modulation Classification: Principles, Algorithms and Applications (Wiley, 2015), Integrative Cluster Analysis in Bioinformatics (Wiley, 2015), Blind Estimation Using Higher-Order Statistics (Springer, 1999), and Automatic Modulation Recognition of Communications Signals (Springer, 1996). The H-index of his publications is 91 (Google Scholar) and ERDOS number is 2.

Professor Nandi is a Fellow of the Royal Academy of Engineering and a Fellow of six other institutions, including the IEEE. In 2023, he has been honoured by the Academia Europaea and the Academia Scientiarum et Artium Europaea. He has received many awards, including the IEEE Heinrich Hertz Award in 2012, the Glory of Bengal Award for his outstanding achievements in scientific research in 2010, the Water Arbitration Prize of the Institution of Mechanical Engineers in 1999, and the Mountbatten Premium of the Institution of Electrical Engineers in 1998. Professor Nandi was an IEEE Distinguished Lecturer (EMBS, 2018-2019).

Dr. Lu Gan

Biography:

Dr. Lu Gan is a Reader in the Department of Electronic and Electrical Engineering at Brunel University London. She received her B.Eng. and M.Eng. degrees from Southeast University, China, and her Ph.D. from Nanyang Technological University, Singapore. Before joining Brunel in 2008, she held academic positions at the University of Newcastle, Australia, and the University of Liverpool, UK. Dr. Gan’s research focuses on signal processing and machine learning, with applications in image/video coding, non-destructive imaging (terahertz and ultrasound), and wireless communications. Her work has been funded by the EPSRC, Innovate UK, BBSRC, UK Atomic Energy Authority etc. She is a Senior Member of IEEE, Vice Chair of the IEEE UK & Ireland Signal Processing Society, Associate Editor for IEEE Signal Processing Letters and IEEE Transactions on Circuits and Systems I. 





This will be a hybrid event, with both in-person and online attendance options. If you intend to participate in person, we kindly encourage you to register as soon as possible, as in-person capacity is limited. Light refreshments, including coffee and tea, will be available for in-person attendees.