User:Leo Lahti

General
I am computational scientist focusing on the development and application of novel computational techniques and modeling principles in data-intensive science, in particular functional genomics associated with human health and well-being. See the occasional opencomp blog on computational science and a brief biography of my research career.

Computational analysis of human microbial communities forms the current main focus of my research activity at Centre of Excellence in Microbial Food Safety Research, Department of Veterinary BioScience, University of Helsinki, Finland. Before that, I was working at Adaptive Informatics Research Centre of Excellence, Aalto University, Laboratory of Cytomolecular Genetics, University of Helsinki and as a visiting researcher at European Bioinformatics Institute EBI, Hinxton, UK, developing machine learning approaches for genome- and organism-wide analysis of the human transcriptome, cancer genomics, and cross-species studies.

Keywords: computational science, machine learning, functional genomics, data analysis, data science, social science, open access, reproducible research, oncogenomics, transcriptomics, metagenomics, microbiomics..

Contact Info

 * Leo Lahti D.Sc. (Tech.) / B.Sc. (Pol. Sci.)
 * Mailing address: Faculty of Veterinary Medicine, PO Box 66, FI-00014 University of Helsinki, Finland


 * Location: Viikki Campus, Helsinki
 * email: Leo.Lahti'at'iki.fi
 * www: http://www.iki.fi/Leo.Lahti


 * Mobile: +358-40-565 5872


 * ResearcherID: G-3170-2010
 * Curriculum Vitae

Education

 * D.Sc. (Tech.) Machine learning, functional genomics, probabilistic data integration, bioinformatics, exploratory data analysis. Aalto University School of Science and Technology, Faculty of Information and Natural Sciences, Espoo, Finland, 2010. PhD thesis: Probabilistic analysis of the human transcriptome with side information (v&auml;it&ouml;stiedote, summary, electronic version, LaTeX sources, pdf). Thesis introduction released with CC-BY license.


 * M.Sc. (Tech.) Mathematics, information technology, materials physics. TKK Helsinki University of Technology, Dpt. Engineering Physics and Mathematics, 2003. Thesis: Comparative functional genome analysis using associative clustering (in Finnish; pdf)


 * B.Sc. (Pol.Sci.) Practical philosophy, economics, communication, political history. University of Helsinki, Faculty of political sciences, 2009. Thesis: Simon Blackburnin kvasi-realismi ja moraalisen keskustelun turvaaminen (Concerning Blackburn's quasi-realism in securing moral discussion; in Finnish; LaTex; pdf). CC-BY license.

Publications
Complete list of publications.

Investigation, development, and application of novel computational techniques for data integration and analysis. In particular, adaptive learning algorithms that can be used to discover relevant structure in the observed data with minimal human intervention. The main application fields are functional genomics and open data initiatives. Open source implementations are provided to enhance transparency, reproducibility, and accelerated adoption of the new methods.

Scientific Open Source Software
Computational scientists can advance the development and wide-spread adoption of reproducible research standards by making computational code available to others through convenient implementations and working to ensure that the research data is released in the public domain. The lack of free and transparent access to research material, including data, computational experiments, and results has been a major bottleneck in computational studies.

To promote reproducibility in computational science, I am actively releasing general-purpose implementations of probabilistic algorithms. Some of the key tools include models for dependency modeling, genomic data integration, functional network analysis, and microarray analysis; see the list of publications for a comprehensive list.

Let us continue and remove artificial barriers from reusing research material to make the newest computational techniques easily available to spark new applications and further development. To start releasing your scientific code, a variety of open licenses are available; I have collected a brief memo on open licensing of scientific material to help with choosing a suitable open license for academic purposes.

Teaching
Machine learning and functional genomics; supervised theses and assignments and participated in organizing seminar and lecture courses in data integration and functional genomics, with the topics varying from state-of-the-art machine learning models to meta-analysis and classical statistics and from human genomics to high-throughput sequencing, cell-biological networks and integration of background information from biomedical community databases to improve statistical inferences based on noisy and high-dimensional genomic observations. For details, see the comprehensive list.

Other activities

 * European leukemia research network; bioinformatics work group member (2009-2011): EuGESMA COST Action BM0801: Translating Genomic and Epigenetic Studies of MDS and AML. European network for leukemia research for collaboration and half-annual workshop meetings.
 * Consortium coordinator (2008-2011): Computational data fusion of multiple biological information sources and background data (MULTIBIO). Three-year research consortium for data integration in functional genomics, funded by the Finnish Funding Agency for Technology and Innovation (TEKES) (total budget 989ke), involving three research groups from University of Helsinki and Aalto University.
 * Board member: public relations (2007-2009); vice president (2009-2010) Bioinformatiikan seura (Finnish Society for Bioinformatics)
 * Memberships in scientific societies: Public Library of Science (PLoS); International Society for Computational Biology (ISCB); Society for Bioinformatics in Northern Europe (SocBIN); IEEE, IEEE Society on Social Implications of Technology
 * NGO support: Electronic Frontier Finland; Amnesty International (founding member and president 2001-2004 for student group at Helsinki University of Technology); Friends of the Earth; Service Civil International (SCI)
 * Refereed papers for BMC Bioinformatics; Neural Processing Letters; Wiley interdisciplinary reviews: Data Mining and Knowledge Discovery; Journal of Machine Learning Research (JMLR/MLOSS track); Machine learning in integrative genomics (MLIG'09); ISCB student council Symposium (ISMB09); Int. Workshop on Self-Organizing Maps (WSOM09); Int. Conf. on Pattern Recognition (ICPR08); Eur. Conf. on Artif. Intelligence (ECAI08); Asia Pac. Bioinf. Conf. (APBC'08); Int. Conf. Natural Computation (ICNC'07); Machine Learning for Signal Processing Workshop (MLSP'07); Int. Symp. Neural Networks (ISNN'06); Comp. Syst. Biol. (WCSB'06).