Dr. Edoardo Pasolli

I am currently postdoctoral fellow at University of Trento, Centre for Integrative Biology, Italy. I am a Marie Sklodowska-Curie individual fellow with the project "Assembly-based discovery of uncharacterized human microbiome members and their tracking across individuals and time".

I was postdoctoral fellow at Purdue University, School of Civil Engineering, West Lafayette IN (November 2013-September 2014), NASA Goddard Space Flight Center, Computational and Information Sciences and Technology Office, Greenbelt MD (September 2012-October 2013) and University of Trento, Department of Information Engineering and Computer Science, Italy (December 2011-August 2012).

I received the Ph.D. in Information and Communication Technology (November 2011), Master's degree (March 2008, Grade: 110/110 cum laude) and Bachelor's degree (January 2006, Grade: 110/110 cum laude) both in Telecommunications Engineering at University of Trento, Italy.

My research interests include the development of
computational and statistically robust tools for analysis of metagenomic data. I have also worked on developing recognition techniques applied to remote sensing images and biomedical signals.

I received the recognitions of IEEE Senior Member (2017), IEEE Transactions on Geoscience and Remote Sensing Best Reviewer (2013), IEEE Geoscience and Remote Sensing Letters Best Reviewer (2012), and Elsevier Pattern Recognition Letters Best Reviewer (2012).

Email: edoardo.pasolli ( at ) unitn.it

http://twitter.com/epasolli


Updated: December 13th, 2017

Short CV

Current position

Postdoctoral fellow, Marie Sklodowska-Curie individual fellow, Centre for Integrative Biology, University of Trento, Italy.
Research activity: "
Assembly-based discovery of uncharacterized human microbiome members and their tracking across individuals and time".

Past positions

November 2013-September 2014
Postdoctoral fellow, School of Civil Engineering, Purdue University, IN.
Research activity: "Development of advanced algorithms for analysis of hyperspectral and unmanned aerial vehicle (UAV) remote sensing images".

September 2012-October 2013
Postdoctoral fellow
, Computational and Information Sciences and Technology Office, NASA Goddard Space Flight Center, MD.
Research activity: "Development of advanced algorithms for segmentation of hyperspectral and very high spatial resolution remote sensing images".

December 2011-August 2012
Postdoctoral fellow
, Department of Information Engineering and Computer Science, University of Trento, Italy.
Research activity: "Development of ICT solutions for environmental and biomedical applications".

Education

November 2011
Ph.D. in Information and Communication Technology
, Department of Information Engineering and Computer Science, University of Trento, Italy.
Thesis title: "Active learning methods for classification and regression problems" under the supervision of prof. F. Melgani. Thesis defence committee: prof. J. Chanussot (Grenoble Institute of Technology), prof. G. Moser (University of Genova), prof. F. Melgani (University of Trento).

March 2008
Master’s degree in Telecommunications Engineering, Faculty of Engineering, University of Trento, Italy, Grade 110/110 cum laude.
Thesis title: "Development of an innovative system for automatic analysis of GPR images" under the supervision of prof. F. Melgani and prof. M. Donelli.

January 2006
Bachelor’s degree in Telecommunications Engineering, Faculty of Engineering, University of Trento, Italy, Grade 110/110 cum laude.
Thesis title: "Multispectral remote sensing image watermarking with PCA and DCT transforms" under the supervision of prof. F. Melgani.

Awards
2017-2023 Qualification as Associate Professor (ASN, sector 09/F2)
2017 IEEE Senior Member
2013 IEEE Transactions on Geoscience and Remote Sensing Best Reviewer
2012 IEEE Geoscience and Remote Sensing Letters Best Reviewer
2012 Elsevier Pattern Recognition Letters Best Reviewer

Research visits
June 2010-July 2010
University of Colorado at Boulder, Department of Aerospace Engineering Sciences.
Research topic: "Improving active learning methods using spatial information" under the supervision of prof. W. J. Emery.

Teaching
2016: Teaching assistant for the course "Digital transmission", Bachelor's degree in Electronics and Telecommunications Engineering, Department of Information Engineering and Computer Science, University of Trento, Italy.
2015-2016: Teaching assistant for the course "Recognition systems", Master's degree in Telecommunications Engineering, Department of Information Engineering and Computer Science, University of Trento, Italy.
2010-2012: Teaching assistant for the course "Remote sensing technologies for archaeology", Master’s degree in Cultural Heritage, Faculty of Letters and Philosophy, University of Trento, Italy.
2009: Teaching assistant for the course "Advanced pattern recognition", Master’s degree in Telecommunications Engineering, Faculty of Engineering, University of Trento, Italy.

Selected talks
August 2017: Metagenomic meta-analysis of large datasets: tools and biological insights. Invited talk at the Joint statistical meeting, Baltimore, United States.
July 2017: Microbiome data analysis. Selected workshop at the Bioc 2017: where software and biology connect, Boston, United States.
February 2017: Tools and challenges for large-scale and accessible metagenomic meta-analysis. Invited talk at the Second workshop in statistical and algorithmic challenges in microbiome data analysis, Boston, United States.
June 2015: MetaPhlAn v2 and tracking microbes at the strain level. Invited talk at the MetaSUB workshop, New York, United States.
June 2015: Meta analysis of disease-association metagenomic datasets for disease classification. Selected talk at the EMBL-The human microbiome conference, Heidelberg, Germany.
April 2014: Investigating pseudo-waveforms for mapping urban infrastructure. Invited talk at the Advancing continuous wave LADAR workshop, West Lafayette, United States.

Reviewer activity (289 papers)
IEEE: Transactions on Geoscience and Remote Sensing; Geoscience and Remote Sensing Letters; Journal of Selected Topics in Applied Earth Observations and Remote Sensing; Geoscience and Remote Sensing Magazine; Transactions on Image Processing; Transactions on Industrial Electronics; Transactions on Medical Imaging; Transactions on Biomedical Engineering; Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics; Transactions on Systems, Man and Cybernetics: Systems; Transactions on Cybernetics; Electronic Letters.
Elsevier: Remote Sensing of Environment; ISPRS Journal of Photogrammetry and Remote Sensing; International Journal of Applied Earth Observation and Geoinformation; Computer & Geosciences; Journal of Applied Geophysics; Journal of the Franklin Institute; Pattern Recognition Letters; Computers in Biology and Medicine; Journal of Chemometrics; Neurocomputing; Chemometrics and Intelligent Laboratory Systems; Biomedical Signal Processing and Control; Informatics in Medicine Unlocked.
Nature: Scientific Reports.
Springer: Journal of Heuristics; Acta Geophysica; Soft Computing.
Taylor & Francis: International Journal of Remote Sensing.
SPIE: Journal of Applied Remote Sensing.
Hindawi: Applied Computational Intelligence and Soft Computing; The Scientific World Journal.
MDPI: Remote Sensing; ISPRS International Journal of Geo-Information; Sensors.
BMC: Microbiome; Bioinformatics.
Others: Photogrammetric Engineering and Remote Sensing; Progress in Electromagnetics Research; Biomedical Engineering; PLOS ONE; International Journal of Remote Sensing Applications; International Journal on Artificial Intelligence Tools; Journal of Zhejiang University Science C; The Open Civil Engineering Journal.

Publications

International journal papers (*: equal contribution)
  1. E. Pasolli*, L. Schiffer*, P. Manghi*, A. Renson, V. Obenchain,  D. T. Truong, F. Beghini, F. Malik, M. Ramos, J. B. Dowd, C. Huttenhower, M. Morgan, N. Segata, L. Waldron. Accessible, curated metagenomic data through ExperimentHub. Nature Methods, 14(11):1023-1024, Nov. 2017 [IF 2016: 25.062] [ website ].
  2. F. Pinto, A. Tett, F. Armanini, F. Asnicar, A. Boscaini, E. Pasolli, M. Zolfo, C. Donati, N. Salmaso, N. Segata. Draft genome sequence of the planktic cyanobacterium Tychonema bourrellyi, isolated from alpine lentic freshwater. Genome Announcements, 5(47):e01294-17, Nov. 2017 [IF 2016: 1.18].
  3. F. Beghini*, E. Pasolli*, D. T. Truong, L. Putignani, S. Cacciò, N. Segata. Large-scale comparative metagenomics of Blastocystis, a common member of the human gut microbiome. ISME Journal, 11:2848-2863, Aug. 2017 [IF 2016: 9.664].
  4. S. Wuyts, S. Wittouck, I. De Boeck, C. Allonsius, E. Pasolli, N. Segata, S. Lebeer. Large-scale phylogenomics of the Lactobacillus casei group highlights taxonomic inconsistencies and reveals novel clade-associated features. mSystems, 2(4):e00061-17, Aug. 2017.
  5. A. Tett, E. Pasolli*, S. Farina*, D. T. Truong*, F. Asnicar, M. Zolfo, F. Beghini, F. Armanini, O. Jousson, V. De Sanctis, R. Bertorelli, G. Girolomoni, M. Cristofolini, N. Segata. Unexplored diversity and strain-level structure of the skin microbiome associated with psoriasis. npj Biofilms and Microbiomes, Jun. 2017.
  6. S. Duranti, G. A. Lugli, L. Mancabelli, F. Armanini, F. Turroni, K. James, P. Ferretti, V. Gorfer, C. Ferrario, C. Milani, M. Mangifesta, R. Anzalone, M. Zolfo, A. Viappiani, E. Pasolli, I. Bariletti, R. Canto, R. Clementi, M. Cologna, T. Crifò, G. Cusumano, S. Fedi, S. Gottardi, C. Innamorati, C. Masè, D. Postai, D. Savoi, M. Soffiati, S. Tateo, A. Pedrotti, N. Segata, D. van Sinderen, M. Ventura. Maternal inheritance of bifidobacterial communities and bifidophages in infants through vertical transmission. Microbiome, 5:66, Jun. 2017 [IF 2016: 8.496].
  7. D. T. Truong, A. Tett, E. Pasolli, C. Huttenhower, N. Segata. Microbial strain-level population structure and genetic diversity from metagenomes. Genome Research, Feb. 2017 [IF 2016: 11.922] [ code ].
  8. E. Pasolli, D. T. Truong, F. Malik, L. Waldron, N. Segata. Machine learning meta-analysis of large metagenomic datasets: tools and biological insights. PLOS Computational Biology, 12(7):e1004977, Jul. 2016 [IF 2016: 4.542] [ code | Gut check article by Casey S. Greene ].
  9. Z. Zhang, E. Pasolli, H. L. Yang, and M. M. Crawford. Multimetric active learning for classification of remote sensing data. IEEE Geoscience and Remote Sensing Letters, 13(7):1007-1011, Jul. 2016 [IF 2016: 2.761].
  10. The MetaSUB International Consortium. The metagenomics and metadesign of the subways and urban biomes (MetaSUB) international consortium inaugural meeting report. Microbiome, 4(1):1-14, Jun. 2016 [IF 2016: 8.496].
  11. M. Scholz*, D. W. Ward*, E. Pasolli*, T. Tolio, M. Zolfo, F. Asnicar, D. T. Truong, A. Tett, A. L. Morrow, and N. Segata. Strain-level microbial epidemiology and population genomics from shotgun metagenomics. Nature Methods, 13(5):435-438, May 2016 [IF 2016: 25.062] [ code | Strain-level article by Vivien Marx ].
  12. E. Pasolli, H. L. Yang, and M. M. Crawford. Active-metric learning for classification of remotely sensed hyperspectral images. IEEE Transactions on Geoscience and Remote Sensing, 54(4):1925-1939, Apr. 2016 [IF 2016: 4.942].
  13. Z. Zhang, E. Pasolli, M. M. Crawford, and J. C. Tilton. An active learning framework for hyperspectral image classification using hierarchical segmentation. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 9(2):640-654, Feb. 2016 [IF 2016: 2.913].
  14. D. T. Truong, E. A. Franzosa, T. T. Tickle, M. Scholz, G. Weingart, E. Pasolli, A. Tett, C. Huttenhower, and N. Segata. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nature Methods, 12(10):902-903, Oct. 2015 [IF 2015: 25.328] [ code ].
  15. E. Pasolli and F. Melgani. Genetic-algorithm based method for mitigating label noise issue in ECG signal classification. Biomedical Signal Processing and Control, 19:130-136, May 2015 [IF 2015: 1.521].
  16. Y. Zhang, H. L. Yang, S. Prasad, E. Pasolli, J. Jung, and M. M. Crawford. Ensemble multiple kernel active learning for classification of multi-source remote sensing data. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 8(2):845-858, Feb. 2015 [IF 2015: 2.145].
  17. E. Pasolli, F. Melgani, D. Tuia, F. Pacifici, and W. J. Emery. SVM active learning approach for image classification using spatial information. IEEE Transactions on Geoscience and Remote Sensing, 52(4):2217-2233, Apr. 2014 [IF 2014: 3.514].
  18. J. Jung, E. Pasolli, S. Prasad, J. C. Tilton, and M. M. Crawford. A framework for land cover classification using discrete return LiDAR data: Adopting pseudo-waveform and hierarchical segmentation. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 7(2):491-502, Feb. 2014 [IF 2014: 3.026].
  19. N. Alajlan, E. Pasolli, F. Melgani, and A. Franzoso. Large-scale image classification using active learning. IEEE Geoscience and Remote Sensing Letters, 11(1):259-263, Jan. 2014 [IF 2014: 2.095].
  20. E. Pasolli, F. Melgani, N. Alajlan, and N. Conci. Optical image classification: a ground-truth design framework. IEEE Transactions on Geoscience and Remote Sensing, 51(6):3580-3597, Jun. 2013 [IF 2013: 2.933].
  21. E. Pasolli, F. Melgani, N. Alajlan, and Y. Bazi. Active learning methods for biophysical parameter estimation. IEEE Transactions on Geoscience and Remote Sensing, 50(10):4071–4084, Oct. 2012 [IF 2012: 3.467].
  22. N. Segata*, E. Pasolli*, F. Melgani, and E. Blanzieri. Local SVM approaches for fast and accurate classification of remote sensing images. International Journal of Remote Sensing, 33(19):6186–6201, Oct. 2012 [IF 2012: 1.138].
  23. F. Douak, F. Melgani, N. Alajlan, E. Pasolli, Y. Bazi, and N. Benoudjit. Active learning for spectroscopic data regression. Journal of Chemometrics, 26(7):374–383, Jul. 2012 [IF 2012: 1.937].
  24. D. Tuia, E. Pasolli, and W. J. Emery. Using active learning to adapt remote sensing image classifiers. Remote Sensing of Environment, 115(9):2232–2242, Sep. 2011 [IF 2011: 4.574].
  25. E. Pasolli, F. Melgani, and Y. Bazi. Support vector machine active learning through significance space construction. IEEE Geoscience and Remote Sensing Letters, 8(3):431–435, May 2011 [IF 2011: 1.560].
  26. E. Pasolli and F. Melgani. Active learning methods for electrocardiographic signal classification. IEEE Transactions on Information Technology in Biomedicine, 14(6):1405–1416, Nov. 2010 [IF 2010: 1.707].
  27. E. Pasolli, F. Melgani, and M. Donelli. Gaussian process approach to buried object size estimation in GPR images. IEEE Geoscience and Remote Sensing Letters, 7(1):141–145, Jan. 2010 [IF 2010: 1.431].
  28. A. Paoli, F. Melgani, and E. Pasolli. Clustering of hyperspectral images based on multiobjective particle swarm optimization. IEEE Transactions on Geoscience and Remote Sensing, 47(12):4175–4187, Dec. 2009, [IF 2009: 2.234].
  29. E. Pasolli, F. Melgani, and M. Donelli. Automatic analysis of GPR images: a pattern-recognition approach. IEEE Transactions on Geoscience and Remote Sensing, 47(7):2206–2217, Jul. 2009, [IF 2009: 2.234].

Book chapters

  1. N. Meger, E. Pasolli, C. Rigotti, E. Trouve, F. Melgani. Satellite image time series: mathematical models for data mining and missing data restoration. In J. Zerubia and G. Moser, editors, Mathematical models for remote sensing image processing. Springer, 2018.
  2. F. Melgani, G. Mercier, L. Lorenzi, and E. Pasolli. Recent methods for reconstructing missing data in multispectral satellite imagery. In R. S. Anderssen et al., editors, Applications + practical conceptualization + mathematics = fruitul innovation, pages 221-234. Springer, 2016.
  3. F. Melgani and E. Pasolli. Multiobjective PSO for hyperspectral image clustering. In A. Chatterjee and P. Siarry, editors, Modern image processing algorithms employing computational intelligence techniques, pages 265-280. Springer, 2013.

International conference papers

  1. D. Dolce, N. Ravenni, S. Campana, E. Camera, S. Neri, C. Braggion, S. Manara, E. Pasolli, F. Armanini, N. Segata, G. Taccetti. Longitudinal study of methicillin-resistant Staphylococcus aureus genetic background isolated from cystic fibrosis patients. In Proceedings of the European Cystic Fibrosis Conference, Journal of Cystic Fibrosis, 16(S90), Jul. 2017.
  2. D. Dolce, N. Ravenni, S. Campana, E. Camera, T. Orioli, S. Neri, C. Braggion, S. Manara, E. Pasolli, F. Armanini, N. Segata, G. Taccetti. Genetic background of methicillin-resistant Staphylococcus aureus isolates from cystic fibrosis patients: a three-year longitudinal study. In Proceedings of the Annual North American Cystic Fibrosis Conference, Pediatric Pulmonology, 51(S45):318, Oct. 2016. 
  3. E. Pasolli, H. L. Yang, and M. M. Crawford. Combining active and metric learning for hyperspectral image classification. In Proceedings of the IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing 2014, Lausanne, Switzerland, 2014.
  4. J. C. Tilton and E. Pasolli. Incorporating edge information into best merge region-growing segmentation. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2014, pages 4891-4894, Quebec, Canada, 2014.
  5. E. Pasolli and F. Melgani. An approach for classifying large scale images. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2012, pages 5410-5413, Munich, Germany, 2012.
  6. F. Douak, F. Melgani, E. Pasolli, and N. Benoudjit. SVR active learning for product quality control. In Proceedings of the International Conference on Information Science, Signal Processing and their Applications 2012, pages 1113-1117, Montreal, Canada, 2012.
  7. E. Pasolli and F. Melgani. Ground-truth assisted design for remote sensing image classification. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2011, pages 609–612, Vancouver, Canada, 2011.
  8. E. Pasolli and F. Melgani. Gaussian process regression within an active learning scheme. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2011, pages 3574–3577, Vancouver, Canada, 2011.
  9. E. Pasolli, F. Melgani, D. Tuia, F. Pacifici, and W. J. Emery. Improving active learning methods using spatial information. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2011, pages 3923–3926, Vancouver, Canada, 2011.
  10. D. Tuia, E. Pasolli, and W. J. Emery. Dataset shift adaptation with active queries. In Proceedings of the Joint Urban Remote Sensing Event 2011, pages 121–124, Munich, German, 2011.
  11. F. Melgani, G. Mahlknecht, E. Pasolli, E. Gottardini, A. Cristofori, F. Cristofolini, and N. La Porta. Exploiting ozone concentration measurements from satellite remote sensors for forest monitoring: a feasibility study. In Proceedings of the IUFRO World Congress 2010, pages 336–336, Seoul, Republic of Korea, 2010.
  12. E. Pasolli and F. Melgani. Model-based active learning for SVM classification of remote sensing images. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2010, pages 820–823, Honolulu, Hawaii, 2010.
  13. A. Paoli, F. Melgani, and E. Pasolli. Swarm intelligence for unsupervised classification of hyperspectral images. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2009, pages V–96–V–99, Cape Town, South Africa, 2009.
  14. E. Pasolli, F. Melgani, and M. Donelli. A pattern recognition system for extracting buried object characteristics in GPR images. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2009, pages IV–430–IV–433, Cape Town, South Africa, 2009.
  15. E. Pasolli, F. Melgani, M. Donelli, R. Attoui, and M. de Vos. A pattern recognition system for archaeological exploration with GPR images. In Proceedings of the Colloque International sur l’Archeologie 2009, Tebessa, Algeria, 2009.
  16. E. Pasolli, F. Melgani, M. Donelli, R. Attoui, and M. de Vos. Automatic detection and classification of buried objects in GPR images using genetic algorithms and support vector machines. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium 2008, pages II–525–II–528, Boston, USA, 2008.