MPBA - Talk &Thesis

Talks & Posters

2019

  1. M. Chierici. Artificial intelligence and life sciences: challenges and cutting-edge applications in computational biology. New Frontiers in Research, Diagnostics and Therapies, Trieste, December 2019. (talk)
  2. M. Chierici. Machine learning for computational biology. Università degli studi di Milano, October 2019. (talk)
  3. M. Chierici, M. Giulini, N. Bussola, G. Jurman, C. Furlanello. ML4Tox – A Machine Learning Framework for Predictive Toxicology. MAQC 2019, Riva del Garda (TN). (poster)
  4. N. Bussola, A. Bizzego, M. Chierici, V. Maggio, M. Francescatto, L. Cima, M. Cristoforetti, G. Jurman, C. Furlanello. Evaluating reproducibility of Deep Learning models on Digital Pathology images. MAQC 2019, Riva del Garda (TN). (poster)
  5. I. Basadonne, A. Zandonà, SL. Mortera, P. Vernocchi, M. Chierici, A. Quagliariello, G. Jurman, C. Furlanello, L. Putignani, P. Venuti. Metaproteomics in ASD Families: A New Approach for Gut Microbiota Profiling in Autism Spectrum Disorders. MAQC 2019, Riva del Garda (TN). (poster)
  6. M.Chierici. Predictive models: principles and case studies. Machine learning: applications to clinical and psychological research, Rovereto (TN), 2019. (talk)
  7. L. Coviello, A. Alikadic. Il fenomeno delle HeatWaves. Trentino Clima 2019, October 2019, Trento (IT).  Presentation
  8. L. Coviello, A. Zanin, S. Fioravanzo. WebValley 2019: Foocus on agricolture, in cooperation with CO.DI.PR.A. Artificial Intelligence within Farmers’ Reach . June 2019, Trento (IT) Presentation
  9. L. Coviello, G. Franch. Microsoft AI4Earth Summit. Modeling Crop-Specific Impact of Heat Waves by Deep Learning.
    May 2019, Seattle (WA) Presentation
  10. L. Coviello. TNC19 – Forging Digital Societies. Democratizing Smart Farming with AI on LoRa Sensor Networks. June 2019, Tallin (EE) Presentation

2018

  1. M. Chierici. Deep learning for predictive toxicology. OpenTox USA 2018, Durham (NC), 2018. (talk)
  2. M. Chierici, V. Maggio, G. Jurman, C. Furlanello. Improved prognostic profiling in high-risk neuroblastoma by multi-task deep learning with distillation of the clinical diagnostic algorithm. MAQC 2018, Shanghai, China

2017

  1. C. Furlanello, M. De Domenico, G. Jurman, N. Bussola Towards a scientific blockchain framework for reproducible data analysis CAMDA 2017 22-23 July 2017 Prague (CZ) Presentation
  2. G. Jurman, Y. Giarratano, C. Agostinelli, V. Maggio, D. Fioravanti, C. Zarbo, C. Furlanello Phylogenetic Convolutional Neural Networks BMTL 2017 7-9 June 2017 Naples (I) Presentation
  3. G. Jurman. Basic principles of scientific visualization. Pycon Otto 6-9 April 2017 Florence (I). Presentation
  4. G. Jurman, R. Visintainer, M. Filosi, S. Riccadonna, C. Furlanello. Differential network analysis and graph classification: a glocal approach. Pycon Otto 6-9 April 2017 Florence (I). Presentation
  5. G. Franch, A. Nardelli, C. Zarbo, V. Maggio, C. Furlanello. Deep Learning for Precipitation and Lightning Nowcasting Pycon Otto 6-9 April 2017 Florence (I). Presentation
  6. V. Maggio. The unconventional introduction to Deep Learning. Pydata, 7 April 2017, Florence (I). Presentation
  7. C. Furlanello, G. Jurman, M. Cristoforetti, V. Maggio, C. Zarbo, M. Chierici. Deep Learning for Integrated Omics and Phenotype. Scientific summit Italy-Japan: Environment and Health, 24 March 2017 Rovereto (I). Presentation
  8. C. Furlanello, G. Jurman, M. Cristoforetti, V. Maggio, C. Zarbo, M. Chierici. Deep Learning for Precision Medicine (with some generalization). MLDAS 14 March 2017, Doha (QA). Presentation

2016

  1. V. Maggio. Deep Learning for Rain and Lightning Nowcasting. NIPS 2016 Workshop on ML for Spatiotemporal Forecasting, Barcelona (S). Presentation
  2. G. Franch, A. Nardelli, C. Zarbo, V. Maggio, C. Furlanello. Deep Learning for Precipitation and Lightning Nowcasting. NIPS 2016 Workshop on ML for Spatiotemporal Forecasting, Barcelona (S)
  3. A. Zandonà, L. Trastulla, G. Jurman, C. Agostinelli, C. Furlanello, M. Lavie-Richard, H. Sokol. Integrated meta-omics for models of gut inflammatory disease. NIPS 2016 MLCB Workshop, Barcelona (S). Poster
  4. C. Zarbo, V. Maggio, M. Chierici, G. Jurman, C. Furlanello. Integrating Deep Learning with the SEQC Data Analysis Plan for predictive biomarkers of Clinical Endpoints in Neuroblastoma. AIA 2016 MLDM Workshop, Genoa (I)
  5. V. Maggio. Data Formats for Data Science (Director’s Confidential). PyCon DE, 29 October 2016, Munich (D). Presentation
  6. V. Maggio. Data Formats for Data Science (Remastered). Budapest BI Forum, 26 October 2016, Budapest (H). Presentation
  7. C. Zarbo, V. Maggio, M. Chierici, G. Jurman, C. Furlanello. Integrating Deep Learning with the SEQC Data Analysis Plan for predictive biomarkers of Clinical Endpoints in Neuroblastoma. PKDD 2016 DLPM Workshop, Riva del Garda (I)
  8. C. Furlanello, A. Zandonà, M. Chierici, G. Jurman. Metagenomics data analytics. Maestra Summer School 2016 on Mining big and complex data, Ohrid (FYROM) Presentation
  9. N.M. Rad, S.M. Kia, C. Zarbo, G. Jurman, P. Venuti, C. Furlanello. Stereotypical Motor Movement Detection in Dynamic Feature Space. Maestra Summer School 2016 on Mining big and complex data, Ohrid (FYROM). Poster
  10. V. Maggio. %%async_run: an IPython notebook extension for asynchronous cell execution. EuroScipy 2016, 26 August 2016, Erlangen (D). Presentation
  11. V. Maggio. Data Formats for Data Science. EuroPython 2016, 21 July, Bilbao (S). Presentation
  12. C. Furlanello, M. Mina, G. Jurman. Disease networks and comorbidity analysis. EuroTox 2016, Seville (S) Presentation
  13. M. Cristoforetti, L. Coviello, C. Furlanello. Monitoring vaccine confidence (with deep learning): the VCM platform. DELVE 2016, Amsterdam (NL) Presentation
  14. V. Maggio. %%async_run: an IPython notebook extension for asynchronous cell execution. PyData Florence, 16 April 2016, Florence (I)
  15. N.M. Rad, C. Furlanello. Applying deep learning to stereotypical motor movement detection in autism spectrum disorders. International Conference on Data Mining 2016, PhD forum, Barcelona , Spain.
  16. N.M. Rad, S.M. Kia, C. Zarbo, G. Jurman, P. Venuti, C. Furlanello. Stereotypical Motor Movement Detection in Dynamic Feature Space. International Conference on Data Mining 2016, DMHAA workshop, Barcelona (S). Presentation

2015

  1. N.M. Rad, A. Bizzego, S.M. Kia, G. Jurman, P. Venuti, C. Furlanello. Convolutional Neural Networks for Stereotypical Motor Movements Detection in Autism. NIPS Workshop – Machine Learning and Interpretation in Neuroimaging, 2015 Montreal (CAN)
  2. C. Furlanello, G. Jurman, M. Filosi, S. Riccadonna, R. Visintainer. The HIM glocal metric and kernel for network comparison and classification. IEEE Data Science and Advanced Analytics (DSAA) 2015, Paris (F) (presentation)
  3. G. Jurman, M. Filosi, S. Riccadonna, R. Visintainer, C. Furlanello. Differential network analysis and graph classification: a glocal approach. Bringing Maths to Life (BMTL) 2015, Naples (I) (presentation)
  4. A. Zandonà, M. Chierici, G. Jurman, C. Furlanello, S. Cucchiara, F. Del Chierico, L. Putignani. Complex networks for the analysis of microbiome structures. Bringing Maths to Life (BMTL) 2015, Naples (I) (presentation)
  5. G. Jurman, A. Zandonà, M. Chierici, C. Furlanello, S. Cucchiara, F. Del Chierico, L. Putignani. Microbial Communities and Individual Health Trajectories. Microbiota: salute terme e alimentazione 2015, Comano Terme (I) (presentation)
  6. A. Zandonà, M. Chierici, G. Jurman, C. Furlanello. Choice of Training-Validation partitions impacts predictive performances. 4th Italian Workshop on Machine Learning and Data Mining (#AI4-MLDM) 2015, Ferrara (I) (presentation)
  7. E. Arbitrio, M. Filosi, A. Gobbi, C. Furlanello. Actionable Data Analytics in retail marketing analysis. Europython’15, Bilbao (E) (poster)
  8. Y. Ozturk, A. Bizzego, C. Furlanello, P. Venuti. Perceived stress, emotional response and physiological reactivity to cry of infant with autism and typically developing infants. European Congress of Psychology 2015, Milan (I)
  9. A. Bizzego, A. Battisti, B. Milosevic, R. De Filippi, E. Farella, C. Furlanello. Identification of fatigue patterns in skiing from inertial and GPS data. International Society for Skiing Safety 2015, San Vito di Cadore (I) (pdf, presentations)
  10. L. Coviello, M. Mina, C. Furlanello. Rhadius: a cloud-based framework interfacing with OMERO server for bioimaging analysis of large scale dataset. 10 Annual OME User Meeting, 2015 Paris (F) (poster)
  11. I. Basadonne, A. Zandonà. Assessment of nutrition and gastrointestinal conditions in children with autism spectrum disorders: an interview to parents. Mediterranean Journal of Clinical Psychology MJCP, Suppl. N.1B, vol.3, No.2, 2015, Milazzo (I) (poster)
  12. I. Basadonne, A. Zandonà, C. Furlanello, P. Venuti. Nutrition and gastrointestinal conditions in Autism Spectrum Disorders: is there a link between gut microbiota and ASD? In Proceedings of the 14th European Congress of Psychology – Linking technology and psychology: feeding the mind, energy for life, 2015, Milan (I) (presentation)

2014

  1. G. Lami, M. Cristoforetti, G. Jurman, C. Furlanello, T. Furlanello. Entropy Dynamics of of Community Alignment of the Italian Parliament Time-Dependent Network, NIPS Workshop – Networks: From Graph to Rich Data, 2014 Montreal (CAN) (poster & spotlight)
  2. A. Zandonà, M. Chierici, G. Jurman, C. Furlanello, S. Cucchiara, F. Del Chierico, L. Putignani. A metagenomic pipeline integrating predictive profiling methods and complex networks for the analysis of NGS microbiome data. NIPS Workshop – Machine Learning in Computational Biology, 2014 Montreal (CAN) (poster & spotloght)
  3. C. Furlanello. Reproducibility and stabilty of predictive biomarkers. Machine Learning and Data Analytics Symposium 2014, Doha (Q) (presentation)
  4. G. Jurman. Applications of streaming data environments for health and safety SAAT 2014, Bournemouth (UK) (presentation)
  5. R Gallesio, M De Mariano, M Chierici, S Stigliani, P Scaruffi, S Coco, C Furlanello, L Longo, GP Tonini. Exome sequencing suggests candidate genes associated with aggressiveness of
    stage 4 neuroblastoma patients. Advances in Neuroblastoma Research, Colonia, Germania, 13-16 Maggio 2014
  6. R. Gallesio, M. De Mariano, M. Chierici, S. Stigliani, P. Scaruffi, S. Coco, C. Furlanello, L. Longo, G.P. Tonini. Exome sequencing suggests candidate genes associated with aggressiveness of stage 4 neuroblastoma patients. Advances in Neuroblastoma Research 2014, Köln (D)
  7. M. De Mariano, R. Gallesio, M. Chierici, C. Furlanello, M. Conte, A. Garaventa, G.P. Tonini, L Longo. GALNT14 as a novel candidate gene for neuroblastoma predisposition. Advances in Neuroblastoma Research 2014, Köln (D)
  8. A. Zandonà, M. Chierici, G. Jurman, L. Putignani, C. Furlanello. A metagenomic pipeline integrating predictive profiling methods and complex networks for the analysis of NGS microbiome data. 3S Biology Summer School 2014, Trento (I) (presentation)
  9. A. Gobbi, F. Iorio, K.J. Dawson, D.C. Wedge, D. Tamborero, L.B. Alexandrov, N. Lopez-Bigas, M.J. Garnett, G. Jurman, J. Saez-Rodriguez. Fast randomization of large genomics datasets while preserving alteration counts. ECCB14, 2014, Strasbourg (F) (presentation)
  10. C. Zarbo, A. Bizzego, M. Mina, G. Esposito, C. Furlanello. A Galaxy-based framework for online streaming data analytics in Heart Rate Variability Analysis. Galaxy Community Conference 2014, Baltimore (US) (pdf, presentazione)
  11. A. Bizzego, M. Mina, C. Zarbo, G. Esposito, C. Furlanello. Physiolyze: a Galaxy-based web service for Heart Rate Variability analysis with online processing. IEEE European Study Group on Cardiovascular Oscillations 2014, Trento (I) (pdf, presentazione)

Tutorials

2019

  • M. Chierici. An introduction to machine learning. Bayer AG, July 2019, Berlin (D)
  • M. Chierici. Machine learning from scratch. EMBO practical course “Population genomics: Background, tools and programming”. April 2019, Procida, NA (I).

2017

  • V. Maggio. Ten Steps to Keras. PyData London, 5 May 2017, London (UK)
  • V. Maggio. Deep Learning: the Keras way. PyData Florence, 8 April 2017, Florence (I)
  • M.Chierici. The data analysis plan: intro to unbiased pipelines for binary classification. ELIXIR-IIB Training course on Machine Learning for Biologists. 2017,  San Michele all’Adige (I)

2016

  • V. Maggio. Deep Learning with Keras and Tensorflow. Budapest BI Forum, 25 October 2016, Budapest (H)
  • V. Maggio. An introduction to Deep Learning with Keras. EuriScipy 2016, 25 August 2016, Erlangen (D)
  • V. Maggio. Introduction to Machine Learning using scikit-learn. BigDive 2016, 24 June 2016, Turin (I)

Theses

Ph.D.

  • A. Zandonà. Predictive networks for multi meta-omics data integration. University of Trento, (CIBIO).
  • Andrea Bizzego. A Data Analytics Framework for Physiological Signals from Wearable Devices. University of Trento, 2017 (ICT)
  • Michele Filosi. A network medicine approach for microarray and Next Generation Sequencing data. University of Trento, 2014 (CIBIO)
  • Andrea Gobbi. Theoretical and algorithmic solutions for null models in network theory. University of Trento, 2013 (Maths) PDF
  • Roberto Visintainer. Distances and Stability in Biological Network Theory. University of Trento, 2013 (ICT) PDF
  • Giorgio Guzzetta. A new computational approach to the integrated modeling of infectious diseases. University of Trento, 2011 (ICT) PDF
  • Piero Poletti. Human behavior in epidemic modeling. University of Trento, 2010 (Maths) PDF
  • Silvano Paoli. A high performance computational environment for UHTS studies. University of Trento, 2010 (ICT) PDF
  • Marco Ajelli. New Generation Individual Based Models for Infectious Diseases Transmission. University of Trento, 2009 (ICT) PDF
  • Samantha Riccadonna. Predictive Data Mining for Integrative Functional Genomics. University of Trento, 2009 (ICT) PDF

 

M.Sc.

  • Ylenia Giarratano. Phylogenetic Convolutional Neural Networks in Metagenomics University of Trento, 2016 (Maths)
  • Lucia Trastulla. Techniques of integration for high-throughput omics data University of Trento, 2016 (Maths)
  • Isotta Landi. Assessing mother-child relationship: Topological Data Analysis of Physiological Measurements University of Trento, 2015 (Maths) PDF
  • Calogero Zarbo. A Deep Learning predictive framework for Metagenomics based on microbiome functional potential profiles University of Trento, 2015 (Eng) PDF
  • Valentina Marziano. Modelling the impact of demographic changes on Varicella and Herpes Zoster University of Trento, 2013 (Maths) PDF
  • Marco Ferrarini. Biological network inference via DTW & correlation measures from time-course data University of Trento, 2012 (Maths) PDF
  • Federico Pierucci. Kernel methods for promoterome analysis with UHTS data University of Trento, 2011 (Maths) PDF
  • Andrea Gobbi. Algebraic reconstruction of gene regulatory networks University of Trento, 2010 (Maths) PDF
  • Martina Calovi. Strumenti e metodi per una nuova geografia: analisi di un sistema sperimentale per l’accesso interattivo a dati territoriali e dati statistici socio-economici a supporto del governo della pianificazione urbanistica University of Pisa, 2009 (Geo) PDF
  • Roberto Visintainer. Feature ranking and classification of molecular data based on discriminant analysis methods University of Trento, 2008 (Eng) PDF
  • Francesca Maule University of Trento, 2006 (Eng)
  • Bettina Irler. Modelli predittivi per la proteomica clinica University of Trento, 2006 (Maths)
  • Francesca Gatti. Analisi discriminante penalizzata: applicazione a dati microarray University of Trento, 2005 (Maths)
  • Matteo De Angeli. Tecniche di regressione applicate al controllo della qualita’ delle acque marine University of Trento, 2005 (Eng)
  • Francesco Cricrì. Algoritmi per la geocodifica automatica di fotogrammetria storica University of Trento, 2005 (Eng)
  • Irene Oliani. Metodi algebrici per la bioinformatica: codici ECOC in problemi multiclasse con costi non uniformi University of Trento, 2005 (Maths)
  • Irene Andreatta. Un modello geostatistico di impatto del traffico con applicazione all’epidemiologia ambientale University of Trento, 2004 (Maths)
  • Ilenia Fronza. Metodi geostatistici per l’epidemiologia ambientale: lo studio SIDRIA2 per la Provincia di Trento University of Trento, 2004 (Maths)
  • Ivan Michelazzi. Geocodifica ed elaborazione di immagini oblique per visualizzazione 3D in ambiente GIS University of Trento, 2004 (Eng)
  • Samantha Riccadonna. Profili molecolari da serie temporali di espressioni geniche University of Trento, 2003 (Maths)
  • Enrico Trainotti. Modelli numerici per la valutazione della tipicità sensoriale University of Trento, 2003 (Maths)
  • Mauro Martinelli. Metodi di classificazione automatica basati su tecniche di ensemble per l’individuazione di pattern in immagini aerofotogrammetriche storiche University of Trento, 2003 (Eng)
  • Luca Miori. Tecniche automatiche per il raddrizzamento di immagini da remote sensing University of Trento, 2003 (Eng)
  • Fabio Morera. Applicazione di un modello per la dispersione dei flussi turistici in un’area protetta: la Val Genova University of Trento, 2002 (Eng)
  • Antonella Lunelli. Epidemiologia della rogna sarcoptica nelle popolazioni di camosci: studio della dinamica dell’infezione attraverso modelli matematici e analisi di dati georiferiti University of Trento, 2002 (Maths)
  • Maria Serafini. Support Vector Machines per la classificazione e la selezione di espressioni geniche da Microarray University of Trento, 2002 (Maths)
  • Marco Olivieri. Tecniche di pattern recognition e remote sensing applicate al monitoraggio di ghiacciai University of Trento, 2002 (Eng)
  • Alessio Cantone. Bagging per k nearest neighbour ed applicazione alla classificazione di ortofoto digitali University of Trento, 2002 (Eng)
  • Steno Fontanari. Sviluppo di metodologie GIS per la determinazione dell’accessibilità  territoriale come supporto alle decisioni nella gestione ambientale University of Trento, 2002 (Eng)
  • Michela Calza. Metodologie di classificazione automatica in ambiente GIS per un modello predittivo del rischio da incidente stradale con fauna selvatica University of Trento, 2002 (Eng)
  • Beatrice Aiardi. Algoritmi di bump hunting in basi dati multidimensionali University of Trento, 2000 (Maths)
  • Elena Vigolo. Metodi di correzione di dati georiferiti con applicazione all’epidemiologia University of Trento, 2000 (Maths)
  • Stefano Menegon. Metodologie GIS per la valutazione predittiva dei miglioramenti ambientali su piccola scala University of Trento, 1999 (Eng)
  • Angela Donini. Modelli predittivi per la gestione faunistica del capriolo in Trentino University of Trento, 1998 (Maths)
  • Sonia Teresi. Misture di Componenti Principali Locali per l’analisi di dati multivariati University of Trento, 1998 (Maths)

Master

  • Silvana Sibilia. WebRENDER: Sistema sperimentale di Rendering paesaggistico Master in Tecnologie e Applicazione di Informatica per la Gestione Territoriale, IIASS, 2003
  • Annita Dei Tos. Strumenti per la gestione del turismo sostenibile. Master Europeo in Ingegneria Ambientale, University of Turin, 1998
  • Paola Coraiola. Metodi software per il monitoraggio del rischio ambientale Master in Tecnologie Avanzate dell’informazione e della telecomunicazione, IIASS, 1997

B. Sc.

  • Marco Roncador. A pipeline for metagenomics with next generation sequencing data. University of Trento, 2011
  • Antonio Ganarini. Protocolli predittivi per l’identificazione di Biomarker in trascrittomica. University of Trento, 2011 PDF Slides
  • Andrea Gobbi. Algebraic and combinatorial techniques for stability algorithms on ranked data. University of Trento, 2008 (Maths) PDF
  • Martina Rossi. Studio di algoritmi algebrici per la stabilita’ predittiva di signature molecolari per dati genomici ad alta dimensione. University of Trento, 2008 (Maths) PDF
  • Stefano Maragnoli. Algoritmi permutazionali per la sintesi di profili molecolari. University of Trento, 2005 (Maths)
  • Alessia Peretti. Indicatori algebrici di stabilità per liste ordinate in diagnostica molecolare. University of Trento, 2005 (Maths)
  • Davide Albanese. BioDCV: a distributed computing system for the complete validation of gene profiles. University of Trento, 2005 (Eng) PDF
  • Roberto Visintainer. Tecniche di machine learning supervisionato per il controllo di qualità di cDNA microarray. University of Trento, 2004 (Eng)
  • Laura Zampa. Tecniche GIS di histogram matching e image blending per la mosaicatura di ortofoto digitali. University of Trento, 2004 (Eng)