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SUMMARY:Consensus Clustering Paradigm for Brain Networks
DESCRIPTION:Speaker Biography\nProfessor Asoke Nandi received the degree of
  Ph.D. in Physics from the University of Cambridge (Trinity College)\, Cam
 bridge. He held academic positions in several universities\, including Oxf
 ord\, Imperial College London\, Strathclyde\, and Liverpool as well as Fin
 land Distinguished Professorship. In 2013 he moved to Brunel University Lo
 ndon\, to become the Chair and Head of Electronic and Computer Engineering
 .\nIn 1983 Professor Nandi co-discovered the three fundamental particles k
 nown as W+\, W− and Z0 (by the UA1 team at CERN)\, providing the evidenc
 e for the unification of the electromagnetic and weak forces\, for which t
 he Nobel Committee for Physics in 1984 awarded the prize to two of his tea
 m leaders for their decisive contributions. His current research interests
  lie in signal processing and machine learning\, with applications to func
 tional magnetic resonance data\, gene expression data\, communications\, a
 nd biomedical data. He has made fundamental theoretical and algorithmic co
 ntributions to many aspects of signal processing and machine learning. He 
 has much expertise in “Big Data”\, dealing with heterogeneous data\, a
 nd extracting information from multiple datasets. Professor Nandi has auth
 ored over 550 technical publications\, including 220 journal papers as wel
 l as four books\, entitled Automatic Modulation Classification: Principles
 \, Algorithms and Applications (Wiley\, 2015)\, Integrative Cluster Analys
 is in Bioinformatics (Wiley\, 2015)\, Blind Estimation Using Higher-Order 
 Statistics (Springer\, 1999)\, and Automatic Modulation Recognition of Com
 munications Signals (Springer\, 1996). The h-index of his publications is 
 67 (Google Scholar) and ERDOS number is\nProfessor Nandi is a Fellow of th
 e Royal Academy of Engineering and a Fellow of six other institutions incl
 uding the IEEE. He received many awards\, including the IEEE Heinrich Hert
 z Award in 2012\, the Glory of Bengal Award for his outstanding achievemen
 ts in scientific research in 2010\, the Water Arbitration Prize of the Ins
 titution of Mechanical Engineers in 1999\, and the Mountbatten Premium of 
 the Institution of Electrical Engineers in 1998. Professor Nandi is an IEE
 E Distinguished Lecturer (EMBS\, 2018-2019).\n \nTalk Abstract\nClusterin
 g algorithms can extract information from large datasets through model-fre
 e or data-driven approaches. However\, in applications with real data with
  little a priori knowledge\, it is often difficult to select an appropriat
 e clustering algorithm and evaluate the quality of clustering results due 
 to the unknown ground truth. It is also the case that conclusions based on
  only one specific algorithm might be biased\, since each algorithm has it
 s own assumptions of the structure of the data\, which might not correspon
 d to the real data.\nIn cases of multiple heterogeneous datasets from simi
 lar experiments\, which may have been generated either in the same laborat
 ory or different laboratories\, the challenge is how to reach consensus co
 nclusions. This presentation will address these issues and report
URL:https://www.imperial.ac.uk/events/98193/consensus-clustering-paradigm-f
 or-brain-networks/
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LOCATION:United Kingdom
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