Michiel Stock
15 SlideShares 26 Followers 11 Folgens
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Gent Area, Belgium Belgium
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Postdoctoral Researcher (FWO) at Ghent University
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Education
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I am an FWO funded postdoctoral researcher at the KERMIT (knowledge-based systems) group at Ghent University. Machine intelligence and living systems fascinate me. In my research, I develop intelligent techniques to understand, predict and control biological networks. My main toolbox involves a mix of machine learning, optimization, bioinformatics and graph theory. I use these methods to predict how plants, animals, microorganisms and molecules interact with each other. Much of my work involves working together with others, translating biological problems as mathematical or computational ones. Every year, I try to engage students students in projects and theses, doing cool things such ...
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machine learning ecology mathematics big data synthetic biology proteins kernel methods collaborative filtering pollination community ecology food webs species interactions graphs networks recommender systems phd pairwise learning algorithms computational biology enzymes bioinformatics ai copula cfd water science communication personalised medicine food netflix data science image processing optimal transport optimization beer molecular biology books biotechnology stem multi-target prediction bioinformatcs drug design extreme classification zero shot learning chemoinfomatics ranking
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(14)
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Bioinformatics kernels relations

Vor 11 Jahren • 508 Aufrufe

A Kernel Based Framework for Predicting Interactions Between Methanotrophs and Heterotrophs

Vor 11 Jahren • 488 Aufrufe

Enzyme Annotation using Conditional Ranking Algorithms

Vor 9 Jahren • 715 Aufrufe

Kernel Methods and Relational Learning in Computational Biology

Vor 9 Jahren • 1317 Aufrufe

A two-step method to incorporate task features for large output spaces

Vor 8 Jahren • 960 Aufrufe

Exact and efficient top-K inference for multi-target prediction by querying separable linear relational models

Vor 7 Jahren • 203 Aufrufe

Bioscience engineering together: participating at iGEM

Vor 7 Jahren • 135 Aufrufe

PhD defence pairwise learning

Vor 7 Jahren • 545 Aufrufe

Pairwise Learning for Synthetic Biology

Vor 6 Jahren • 392 Aufrufe

A tour in optimal transport

Vor 6 Jahren • 1825 Aufrufe

2018 presentation montréal_handouts

Vor 6 Jahren • 103 Aufrufe

Disentangling ecological networks using graph embedding methods

Vor 6 Jahren • 472 Aufrufe

How the mathematics behind Netflix will save the world

Vor 5 Jahren • 210 Aufrufe

Wiskunde voor Waterbeheer

Vor 5 Jahren • 307 Aufrufe

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Poster genome engineering & Synthetic Biology 2016

Vor 8 Jahren • 411 Aufrufe

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Cheminformatics in R

Rajarshi Guha • Vor 13 Jahren
Personal Information
Unternehmen/Arbeitsplatz
Gent Area, Belgium Belgium
Beruf
Postdoctoral Researcher (FWO) at Ghent University
Branche
Education
Info
I am an FWO funded postdoctoral researcher at the KERMIT (knowledge-based systems) group at Ghent University. Machine intelligence and living systems fascinate me. In my research, I develop intelligent techniques to understand, predict and control biological networks. My main toolbox involves a mix of machine learning, optimization, bioinformatics and graph theory. I use these methods to predict how plants, animals, microorganisms and molecules interact with each other. Much of my work involves working together with others, translating biological problems as mathematical or computational ones. Every year, I try to engage students students in projects and theses, doing cool things such ...
Tags
machine learning ecology mathematics big data synthetic biology proteins kernel methods collaborative filtering pollination community ecology food webs species interactions graphs networks recommender systems phd pairwise learning algorithms computational biology enzymes bioinformatics ai copula cfd water science communication personalised medicine food netflix data science image processing optimal transport optimization beer molecular biology books biotechnology stem multi-target prediction bioinformatcs drug design extreme classification zero shot learning chemoinfomatics ranking
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