Seminars



The Department has regular research seminars given by internal and prominent external speakers. They are open to all members of the University and other interested parties. The individual research groups also run seminars and group meetings. Details of these can be found on research-group web pages.


TITLE

From Random Projections to Learning Theory and Back

SPEAKERDr Ata Kaban - University of Birmingham
PROFILEAta Kaban is a senior lecturer in Computer Science at the University of Birmingham UK, and EPSRC Early Career Fellow. Her research interests include statistical machine learning and data mining in high dimensional data spaces, algorithmic learning theory, probabilistic modelling of data, and black-box optimisation. She authored / co-authored 80 per-reviewed papers, including best paper awards at GECCO'13, ACML'13, ICPR'10, and a runner-up at CEC'15. She was recipient of an MRC Discipline Hopping award in 2008/09. She holds a PhD in Computer Science (2001) and a PhD in Musicology (1999). She is member of the IEEE CIS Technical Committee on Data Mining and Big Data Analytics, and vice-chair of the IEEE CIS Task Force on High Dimensional Data Mining.
ABSTRACTWe consider two problems in statistical machine learning -- an old and a new:
  • Given a machine learning task, what kinds of data distributions make it easier or harder? For instance, it is known that large margin makes classification tasks easier.
  • Given a high dimensional learning task, when can we solve it from a few random projections of the data with good-enough approximation? This is the compressed learning problem.
This talk will present results and work in progress that highlight parallels between these two problems. The implication is that random projection -- a simple and effective dimensionality reduction method with origins in theoretical computer science -- is not just a timely subject for efficient learning from large high dimensional data sets, but it can also help us make a previously elusive fundamental problem more approachable. On the flip side, the parallel allows us to broaden the guarantees that hold for compressed learning beyond of those initially inherited from compressed sensing.
DATE2017-06-05
TIME14:10:00
PLACEHugh Owen - Lecture Theatre D5


TITLE

Computational Biology in Potato Pathology: From Chips to Chips

SPEAKERDr. Leighton Pritchard - The James Hutton Institute
PROFILEI graduated in 1996 from the University of Strathclyde with a first degree in Forensic and Analytical Chemistry, and remained there to complete my PhD with Mark Dufton in bioinformatics on snake venom toxin sequence-structure-function relationships (which spun out a drug design algorithm that is still in use). From there I moved to Aberystwyth in 1999 to work with Doug Kell, modelling yeast glycolysis and directed evolution. In 2003 I left to take up a bioinformatics position at the Scottish Crop Research Institute, working on microbial plant pathogens and major genomics projects for the first enterobacterial plant pathogen to be sequenced, and the globally-significant pathogen Phytophthora infestans. At SCRI and the James Hutton Institute (formed from a merger of SCRI and the Macaulay Land Use Research Institute) my computational biology research has covered bacterial, oomycete and nematode plant pathogens, and potato genomics. I currently have active projects focusing on plant-pathogen interactions, and the persistence and spread of human and animal pathogens in agricultural and natural environments. I co-supervise PhD students at the Universities of Dundee (Phytophthora diagnostics and monitoring), St Andrews/IBioIC (synthetic and structural biology of virulence enzymes, for industrial biotechnology) and Galway (environmental E. coli), and am co-investigator on a major national collaboration with Forest Research, the Centres for Ecology and Hydrology, and the Universities of Edinburgh and Worcester to identify and evaluate threats to trees from Phytophthora spp., and make recommendations on nursery practice. My work for the Scottish Government focuses on environmental phylogenomics and diagnostics, with input to policy. I am a badged Software and Data Carpentry instructor, and have taught at the Universities of Dundee and Strathclyde, and EMBL-EBI.
ABSTRACTIf it weren’t for destruction of crops by plant pathogens, we could feed two billion extra mouths each year. In this presentation, I’ll describe how at the James Hutton Institute we are using computational biology to try to make a dent into the societal impact of potato diseases: building classifiers to identify the components of plants and their pathogens that control whether disease develops; using brute-force computational methods to mine public genome databases and develop accurate diagnostic tools for identifying pathogens; developing algorithms to improve genome assembly through difficult-to-resolve regions and get extra value from large public sequence databases; and using graph theory to redefine, and perhaps even overturn, long-standing taxonomic classifications of potato pathogens and other bacteria.
DATE2017-06-19
TIME14:10:00
PLACEHugh Owen - Lecture Theatre D5


TITLE

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SPEAKERProfessor Yong Wang : De Montfort University
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DATE2017-07-03
TIME14:10:00
PLACEHugh Owen - Lecture Theatre D5


TITLE

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SPEAKERDima Damen - University of Bristol
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DATE2017-07-10
TIME14:10:00
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