CV - Cornell University

Theo Damoulas
Research Associate
damoulas@cs.cornell.edu Department of Computer Science
Cornell University, 5160A Upson Hall
Ithaca, NY, 14853
Research Interests
I investigate fundamental problems in statistical machine learning and artificial intelligence that are
motivated by, and impact, real world applications in biology, sustainability and engineering. My
recent work is on algorithms for spatiotemporal inference, supervised learning and their application
on Big Data problems. My Ph.D thesis introduced a formal probabilistic framework for multinomial
classification in the presence of multiple sources of information.
Education
Doctor of Philosophy (Ph.D), Computer Science Feb 2006 - Oct 2009
University of Glasgow, Scotland, UK
Thesis: Probabilistic Multiple Kernel Learning
Classification Society Distinguished Dissertation Award (2012)
• Area: Statistical machine learning, Bayesian inference
• Advisor: Prof. Mark A. Girolami
Master of Science (M.Sc.), Computer Science Sep 2003 - Dec 2004
University of Edinburgh, Scotland, UK
Thesis: Evolving a Sense of Valency
Distinction
• Area: Machine learning, reinforcement learning
• Advisor: Dr. Gillian Hayes
Master of Engineering (M.Eng.), Mechanical Engineering Sep 1999 - Sep 2003
University of Manchester, England, UK
Thesis: Computational Fluid Dynamics Models of Nuclear Reactors
1st Class
• Area: computational fluid dynamics, engineering mathematics
• Advisor: Dr. Mark Cotton
Research Experience
Research Associate, Computer Science Jan 2011 - Present
Cornell University, Ithaca, NY, USA
• Area: Machine learning for Computational Sustainability
• Mentor: Carla P. Gomes
• Application areas: Biology, climate change, human computation
Postdoctoral Research Associate, Computer Science Oct 2009 - Jan 2011
Cornell University, Ithaca, NY, USA
• Area: Machine learning for Computational Sustainability
• Mentor: Carla P. Gomes
• Application areas: Biology, engineering, species distribution models
Ph.D Student, Computer Science Feb 2006 - Oct 2009
University of Glasgow, Scotland, UK
• Area: Statistical machine learning
• Advisor: Mark A. Girolami
• Application areas: Bioinformatics, automatic currency validation
Theo Damoulas Curriculum Vitae 1 of 6

Grants, Honors and Awards
TeraGrid (XSEDE) Grant, $150,000 (Estimated)
Statistical Modeling of Avian Distributional Dynamics on the TeraGrid: Support for the Phenological
Atlas of North American Birds. 3,000,000 Service Units (SUs).
• Co-PI and co-author of the proposal
• Enabled continent-scale predictive modeling on eBird data that contributed to the 2011 State
of the Birds report, Department of the Interior, US.
NSF II-EN Computing Research Infrastructure, $378,016
Computing Research Infrastructure for Constraint Optimization, Machine Learning, and Dynamical
Models for Computational Sustainability.
• Co-authored proposal (PI: Carla P. Gomes)
• Lead the design and purchase of the atlas.cac.cornell.edu HPC cluster.
Best Paper Award, Bayesian classification of flight calls with a novel dynamic time warping kernel,
9th International Conference on Machine Learning and Applications, IEEE ICMLA 2010.
Deployed Application Award, eBird: a human-computer learning network for biodiversity conservation
and research, IAAI 2012.
PhD Thesis Award, The Classification Society Distinguished Dissertation Award, The Classification
Society, CMU, June 2012.
PhD Scholarship Award, Machine Learning Techniques for Automatic Currency Validation, full
funding for PhD research by NCR Financial Solutions Group Ltd.
M.Sc. Scholarship Award Student Awards Agency for Scotland (SAAS), Scholarship for M.Sc. in
informatics, University of Edinburgh, SAAS Ref. no. P/13185160
Royal Academy of Engineering Post-Doctoral Fellowship (UK), Finalist for this prestigious
fellowship based on a full proposal that I authored during the third year of my PhD.
Publications
Book Chapters
[1] Kelling, S., Fink, D., Hochachka, W., Rosenberg, K., Cook, R., Damoulas, T., Silva, C., and Michener,
W. (2012a). Estimating species distributions across time through space and with features of the
environment. In Data Intensive Research. In Press
[2] Damoulas, T. and Girolami, M. A. (2009b). Combining information with a Bayesian multiclass
multikernel pattern recognition machine. In De, R. K., Mandal, D. P., and Ghosh, A., editors, Machine
Interpretation of Patterns: Image Analysis, Data Mining and Bioinformatics. World Scientific Press
Refereed Journal Papers
[3] Polajnar, T., Damoulas, T., and Girolami, M. A. (2011). Protein interaction sentence detection
using multiple semantic kernels. Journal of Biomedical Semantics, 2(1)
[4] Psorakis, I., Damoulas, T., and Girolami, M. A. (2010). Multiclass relevance vector machines:
sparsity and accuracy. IEEE Transactions on Neural Networks, 21(10)
Theo Damoulas Curriculum Vitae 2 of 6

[5] Damoulas, T. and Girolami, M. A. (2009a). Combining feature spaces for classification. Pattern
Recognition, 42(11):2671–2683
[6] Damoulas, T. and Girolami, M. A. (2009c). Pattern recognition with a Bayesian kernel combination
machine. Pattern Recognition Letters, 30(1):46–54
[7] Damoulas, T. and Girolami, M. A. (2008). Probabilistic multiclass multikernel learning: On protein
fold recognition and remote homology detection. Bioinformatics, 24(10):1264–1270
Refereed Conference Papers
[8] Damoulas, T., Bruns, N., and Farnsworth, A. (2012). Machine learning techniques for automated
flight call detection. In 5th North American Ornithological Conference, (NAOC-V 2012)
[9] Kelling, S., Gerbracht, J., Fink, D., Lagoze, C., Wong, W.-K., Yu, J., Damoulas, T., and Gomes,
C. P. (2012b). eBird: a human-computer learning network for biodiversity conservation and research.
In 24th international conference on Innovative Applications of Artificial Intelligence (IAAI 2012).
Deployed Application Award
[10] Bras, R. L., Damoulas, T., Gregoire, J. M., Sabharwal, A., Gomes, C., and van Dover, R. B.
(2011). Constraint reasoning and kernel clustering for pattern decomposition with scaling. In 17th
international conference on Principles and Practice of Constraint Programming, (CP 2011)
[11] Phillips, S. J., Pearson, R. G., Beck, P. S., Loranty, M. M., Goetz, S. J., and Damoulas, T. (2011).
Estimating vegetation expansion in the arctic under climate change using machine learning. In society
of conservation biology, International Congress for Conservation Biology, (ICCB 2011)
[12] Damoulas, T., Henry, S., Farnsworth, A., Lanzone, M., and Gomes, C. P. (2010). Bayesian classification
of flight calls with a novel dynamic time warping kernel. In IEEE, 9th International Conference
on Machine Learning and Applications, (ICMLA 2010).
Best Paper Award
[13] Ying, Y., Campbel, C., Damoulas, T., and Girolami, M. A. (2009). Class prediction from disparate
biological data sources using a simple multi-class multi-kernel algorithm. In Pattern Recognition in
Bioinformatics (PRIB 2009)
[14] Damoulas, T., Ying, Y., Girolami, M. A., and Campbel, C. (2008). Inferring sparse kernel combinations
and relevance vectors: An application to subcellular localization of proteins. In IEEE, 7th
International Conference on Machine Learning and Applications (ICMLA 2008)
[15] Damoulas, T., Aguilera, I. C., Hayes, G., and Taylor, T. (2005b). Valency for adaptive homeostatic
agents: relating evolution and learning. In 8th European Conference on Artificial Life, (ECAL
2005)
[16] Damoulas, T., Aguilera, I. C., Hayes, G., and Taylor, T. (2005a). Valency as a mechanism for
agent adaptation. In 6th conference Towards Autonomous Robotic Systems, (TAROS 2005)
Accepted
[17] Pearson, R. G., Phillips, S. J., Loranty, M. M., Beck, P. S., Damoulas, T., Knight, S. J., and
Goetz, S. J. (2012). Arctic vegetation distribution shifts and associated feedbacks under future climate
change. Nature Climate Change. Accepted subject to minor revisions
Theo Damoulas Curriculum Vitae 3 of 6

Other Published Works
[18] Fink, D., Hochachka, W., Damoulas, T., Dave, J., and Kelling, S. (2012). Exploratory analysis
and inference with broad-scale citizen science data. In Ecological Society of America, (ESA 2012)
[19] Dilkina, B., Damoulas, T., Gomes, C., and Fink, D. (2011). AL 2 : Learning for active learning.
In NIPS workshop on Maching Learning for Sustainability, (NIPS 2011)
[20] Pearson, R. G., Phillips, S. J., Beck, P. S., Loranty, M. M., Damoulas, T., and Goetz, S. J.
(2011). Arctic greening under future climate change predicted using machine learning. In American
Geophysical Union, (AGU 2011)
[21] Bras, R. L., Damoulas, T., Gregoire, J. M., Sabharwal, A., Gomes, C., and van Dover, R. B.
(2010). Computational thinking for material discovery: bridging constraint reasoning and learning. In
2nd international workshop on Constraint Reasoning and Optimization for Computational Sustainability
(CROCS, CP 2010)
[22] Damoulas, T. (2009). Probabilistic Multiple Kernel Learning. PhD thesis, University of Glasgow
[23] Damoulas, T., Girolami, M. A., and Rogers, S. (2009). Preliminary analysis of multiple kernel
learning: flat maxima, diversity and Fisher information. In NIPS workshop on Understanding Multiple
Kernel Learning Methods, (NIPS 2009)
Patent
[24] He, C., Damoulas, T., and Girolami, M. A. (2011). Self-service terminals. US Patent 7,942,315
Selected Talks
Carnegie Mellon University, Classification Society Dissertation Award 2012
Probabilistic Multiple Kernel Learning
Ohio State University, Invited Talk 2012
Probabilistic Machine Learning in Biology and Computational Sustainability
Cornell University, AI Seminar 2010
Probabilistic Multiple Kernel Learning
University of Glasgow, Cakes Talk 2009
Computational Sustainability
University of Edinburgh, Invited Talk 2008
Probabilistic Multiple Kernel Learning
Cambridge University, Cavendish Laboratory, Invited Talk 2008
Probabilistic Multiple Kernel Learning
Teaching Experience
Guest Lecturer, Cornell University 2012
CS 6702, Topics in Computational Sustainability, taught by Prof. Carla Gomes.
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I will deliver a series of lectures on machine learning techniques for computational sustainability.
Guest Lecturer, Cornell University 2010
CS 6784, Advanced Topics in Machine Learning, taught by Prof. Thorsten Joachims.
Delivered one lecture on Markov Random Fields and covariate shift techniques.
Graduate Teaching Assistant (GTA), University of Glasgow 2007 - 2008
CS1Q, Intro to Computer Systems, taught by Prof. Chris Johnson.
I was the GTA for a group of 1st year undergraduate students for two semesters.
Private Tutor, Thessaloniki, Greece 2004 - 2005
Taught university entry-level physics, computer science and mathematics to high-school students
preparing for the Greek national exams.
Mentoring and Advising
I have successfully supervised 7 graduate (Master’s degree) students to date as a Research Associate
at Cornell University and as a PhD student at the University of Glasgow.
Ioannis Psorakis, M.Sc. IT, University of Glasgow 2009
Thesis: Multiclass Relevance Vector Machines
• Area: Empirical evaluation of algorithms developed during my PhD thesis
• Joint publication [4] at IEEE Transactions journal
Samuel Henry, M.Eng, Cornell University 2010
Thesis: Bayesian Flight Call Classification
• Area: Dynamic Time Warping kernels for bioacoustics
• Joint publication [12] at IEEE conference and Best Paper Award
Jason Marcell, M.Eng, Cornell University 2011
Thesis: mRVMs in C++ and Social Network Discovery
• Area: Sparse multiclass classifiers, LDA and network inference
• Joint winner of the BOOM 2011, EMC Big Data Award
Karan Kurani, M.Eng, Cornell University 2011
Thesis: Multiview ensemble learning for poverty mapping and Social Network Discovery
• Area: Ensemble classification, multiview clustering, LDA and network inference
• Joint winner of the BOOM 2011, EMC Big Data Award
• Winner of the 2011 Academic Excellence award
Nikhil Kejriwal, M.Eng, Cornell University 2011
Thesis: Inverse Reinforcement Learning for Pastoral Systems
• Area: Inverse Reinforcement Learning
• Winner of the 2011 Outstanding Project award for M.Eng thesis
Jaimin Dave, M.Eng, Cornell University 2011 - 2012
Thesis: Data-driven spatiotemporal segmentations and sampling bias
• Area: spatiotemporal inference, data structures
• Work presented [18] at the Ecological Society of America (ESA 2012)
• Active collaboration towards a AAAI 2013 conference paper
Nicholas Bruns, M.Eng, Cornell University 2012 - 2013
Thesis: Spectral clustering techniques for flight call detection
• Area: spectral clustering, image segmentation
• Joint publication [8] at ecological conference
• Active collaboration towards an Ecoinformatics journal paper
Theo Damoulas Curriculum Vitae 5 of 6

Professional Service
Reviewer: IEEE Transactions on Neural Networks, IEEE Transactions on Computers, Bioinformatics,
BMC Bioinformatics, Pattern Recognition, Pattern Recognition Letters, IEEE Signal Processing
Letters, IEEE Transactions on Systems, Man and Cybernetics (Part B), Artificial Intelligence.
Senior PC member: IJCAI (2013)
PC member: AAAI (2011-2012), ICPR (2011-2012), CompSust (2010-2012), ICANN 2010, PRIB
(2009-2010)
Organizer: NIPS 2012 workshop on Human Computation for Science and Computational Sustainability
together with Thomas G. Dietterich, Edith Law and Serge J. Belongie.
Details at www.cs.cornell.edu/∼damoulas/Site/HCSCS.hmtl
References
Available upon request
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