# Carlo Vercellis

Carlo Vercellis is full professor of Machine Learning at Politecnico di Milano. He is director of **door**,
the Machine Learning and Big Data Analytics research group, founder and scientific director of the Observatory on Big Data & Business Analytics, director of the **International Master in Business Analytics and Big Data** at MIP-Politecnico di Milano,
founder and director of **Aiblooms**, a spin-off of Politecnico di Milano, focused on artificial intelligence and machine learning applications.

His research interests include machine learning, in particular deep learning, support vector machines, nonlinear dimensionality reduction, sentiment analysis; their application to marketing, social networks, internet of things, finance, biolife science; optimization models, with applications to supply chain and revenue management. His past research dealt also with design and analysis of algorithms for combinatorial optimization, project management, transportation models.

He is author of many scientific writings, among which 6 books and dozens of papers in high-ranked international journals. He has been associate editor of several journals, and coordinated several research programs funded by EEC, CNR, MIUR and private companies. He organized several international conferences, and has been invited to discuss his research work in leading research institutions. He developed projects with several companies on machine learning, predictive analytics, big data, sentiment analysis, marketing, risk analysis, supply chain optimization, quality control.

Previously, after his graduation in Mathematics at Università degli Studi di Milano, he has been with National Research Council (CNR), Bocconi University and Università degli Studi di Milano.

## Contact

School of Management - Politecnico di Milano

Room: 2.03 - Phone: (+39)02-23992784

Homepage
at Politecnico di Milano

## Publications

### Books

- C. Vercellis. Business intelligence. Data mining and optimization for decision making. Wiley, 2009.
- C. Vercellis. Ottimizzazione. Teoria, metodi, applicazioni. McGraw-Hill, 2008.
- G. Felici, C. Vercellis. Mathematical methods for knowledge discovery and data mining. Idea Group, 2007.
- C. Vercellis. Business intelligence. Modelli matematici e sistemi per le decisioni. McGraw-Hill, 2006.
- C. Vercellis. Modelli e decisioni. McGraw-Hill, 2006.
- C.Vercellis. Modelli e decisioni. Strumenti e metodi per le
decisioni aziendali. Esculapio, 1997.

### Papers in ISI/SCOPUS journals

- K.A. Arano, P. Gloor, C. Orsenigo, C. Vercellis. "Emotions are the Great Captains of our Lives": Measuring Moods through the Power of Physiological and Environmental Sensing.
*IEEE Transactions on Affective Computing*, DOI: 10.1109/TAFFC.2020.3003736. - M. Jalayer, C. Orsenigo, C. Vercellis. Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms.
*Computers in Industry 125*(2021), pp. 103378. - F.Z. Xing, E. Cambria, L. Malandri, C. Vercellis. Discovering bayesian market views for intelligent asset allocation.
*Lecture Notes in Computer Science*11053 (2019), pp. 120–135. - L. Malandri, F.Z. Xing, C. Orsenigo, C. Vercellis, E. Cambria. Public Mood–Driven Asset Allocation: the Importance of Financial Sentiment in Portfolio Management.
*Cognitive Computation 10(6)*(2018), pp. 1167-1176. - C. Orsenigo, C. Vercellis. Anthropogenic influence on global warming for effective cost-benefit analysis: a machine learning perspective.
*Economia e Politica Industriale 45(3)*(2018), pp. 425-442. - C. Orsenigo, C. Vercellis, C. Volpetti. Concatenating or Averaging? Hybrid Sentences Representations for Sentiment Analysis.
*Lecture Notes in Computer Science*11314 (2018), pp. 567-575. - C. Orsenigo, C. Vercellis. Linear versus nonlinear
dimensionality reduction for banks' credit rating prediction.
*Knowledge-Based Systems 47*(2013), pp. 14-22. - C. Orsenigo, C. Vercellis. A comparative study of nonlinear
manifold learning methods for cancer microarray data
classification.
*Expert Systems with Applications 40*(2013), pp. 2189-2197. - C. Orsenigo, C. Vercellis. Landmark Selection for Isometric Feature
Mapping Based on Mixed-Integer Optimization. In: Modeling Decisions for
Artificial Intelligence.
*Lecture Notes in Computer Science*8234 (2013), pp. 260-271. - C. Orsenigo, C. Vercellis. Dimensionality Reduction via Isomap
with Lock-Step and Elastic Measures for Time Series Gene
Expression Classification. In: Evolutionary Computation, Machine
Learning and Data Mining in Bioinformatics.
*Lecture Notes in Computer Science*7833 (2013), pp. 92-103. - C. Orsenigo, C. Vercellis. Regularization through fuzzy discrete
SVM with applications to customer ranking.
*Journal of Intelligent & Fuzzy Systems 23*(2012), pp. 101-110. - C. Orsenigo, C. Vercellis. Kernel ridge regression for
out-of-sample mapping in supervised manifold learning.
*Expert Systems with Applications 39*(2012), pp. 7757-7762. - C. Orsenigo, C. Vercellis. An effective double-bounded
tree-connected Isomap algorithm for microarray data
classification.
*Pattern Recognition Letters 33*(2012), pp. 9-16. - C. Orsenigo, C. Vercellis. Combining discrete SVM and fixed
cardinality warping distances for multivariate time series
classification.
*Pattern Recognition*(2010), pp. 3787-3794. - C. Orsenigo, C. Vercellis. Time series gene expression data
classificationvia L1-norm temporal SVM. In: Pattern Recognition
in Bioinformatics.
*Lecture Notes in Computer Science*6282 (2010), pp. 264-274. - C. Orsenigo, C. Vercellis. Multicategory classification via
discrete support vector machines.
*Computational Management Science*6 (2009), 101-114. - C. Orsenigo, C. Vercellis. Accurately learning from few examples
with a polyhedral classifier.
*Computational Optimization and Applications*38 (2007), pp. 235-247. - C. Orsenigo, C. Vercellis. Evaluating membership functions for
fuzzy discrete SVM. In: Applications of fuzzy sets theory.
*Lecture Notes in Artificial Intelligence*4578 (2007), pp. 187-194. - C. Orsenigo, C. Vercellis. Softening the margin in discrete SVM.
In: Advances in Data Mining.
*Lecture Notes in Artificial Intelligence*4597 (2007), pp. 49-62. - C. Orsenigo, C. Vercellis. Predicting HIV protease-cleavable
peptides by discrete support vector machines. In: Evolutionary
Computation, Machine Learning and Data Mining in Bioinformatics.
*Lecture Notes in Computer Science*4447 (2007), pp.197-206. - C. Orsenigo, C. Vercellis. A Bayesian stopping rule for greedy
randomized procedures.
*Journal of Global Optimization*36 (2006), 365-377. - C. Orsenigo, C. Vercellis. Discrete support vector decision
trees via tabu-search.
*Computational Statistics and Data Analysis*47 (2004), 311-322. - C. Orsenigo, C. Vercellis. Multivariate classification trees
based on minimum features discrete support vector machines.
*IMA Journal of Management Mathematics*14 (2003), 221-234. - D. La Torre, C. Vercellis. C1,1 approximations of generalized
support vector machines.
*Journal of Concrete and Applicable Mathematics*1 (2003), 125-134. - C. Orsenigo, C. Vercellis. One-against-all multicategory
classification via discrete support vector machines.
*Management Information Systems*7, 2003, 255-264. - C. Vercellis. Combining Data Mining and Optimization for
Campaign Management.
*Management Information Systems*6, 2002, 61-71. - A. Dumoulin, C. Vercellis. Tactical models for hierarchical
capacitated lot-sizing problems with setups and changeovers.
*International Journal of Production Research*38 (2000), 51-67. - F. Fumero, C. Vercellis. Synchronized development of production,
inventory and distribution schedules.
*Transportation Science*33 (1999), 330-340. - C. Vercellis. Multi-plant production planning in capacitated
self-configuring two-stage serial systems.
*European Journal of Operational Research*119 (1999), 451-460. - F. Fumero, C. Vercellis. Integrating distribution, lot-sizing
and machine loading via Lagrangean relaxation.
*International Journal of Production Economics*49 (1997), 45-54. - F. Fumero, C. Vercellis. Capacity management through Lagrangean
relaxation: an application to tires production.
*Production Planning and Control*7 (1996), 604-614. - A. Marchetti-Spaccamela, C. Vercellis. Stochastic on-line
knapsack problems.
*Mathematical Programming*68 (1995), 73-104. - C. Vercellis. Constrained multi-project planning problems: a
Lagrangean decomposition approach.
*European Journal of Operational Research*78 (1994), 267-275. - F. Fumero, C. Vercellis. Capacity analysis in repetitive
assemble-to-order manufacturing systems.
*European Journal of Operational Research*78 (1994), 204-215. - F. Stella, C. Vercellis, M. Zaffalon. A GAP formulation for
solving production planning problems in Telecom industry.
*Operations Research*1994, Springer, 1995, 324-328. - A.H.G. Rinnooy Kan, L. Stougie, C. Vercellis. A class of
generalized greedy algorithms for the multi-knapsack problem.
*Discrete Applied Mathematics*42 (1993), 279-290. - M.G. Speranza, C. Vercellis. Hierarchical models for
multi-project planning and scheduling.
*European Journal of Operational Research*64 (1993), 312-325. - M.G. Speranza, C. Vercellis. A hierarchical multiobjective
approach to project management.
*Multiple criteria decision support,*Springer, 1991, 191-204. - C. Vercellis. Multi-criteria models for capacity analysis and
aggregate planning in manufacturing systems.
*International Journal of Production Economics*23 (1991), 261-272. - M. Meanti, A.H.G. Rinnooy Kan, L. Stougie, C. Vercellis. A
probabilistic analysis of the multiknapsack value function.
*Mathematical Programming*46 (1990), 237-248. - P.M. Camerini, F. Maffioli, C. Vercellis. Multi-constrained
matroidal knapsack problems.
*Mathematical Programming*45 (1989), 211-231. - E. Tosini, C. Vercellis. An interactive approach to crew
scheduling problems.
*Computer-aided transit scheduling*, Springer, 1988, 41-53. - A. Marchetti Spaccamela, C. Vercellis. Efficient on-line
algorithms for knapsack problems.
*Automata, languages and programming*. Springer, 1987, 445-456. - B. Betr?, C. Vercellis. Bayesian nonparametric inference and
Monte Carlo optimization.
*Optimization*17 (1986), 681-694. - F. Archetti, A. Sciomachen, C. Vercellis. Optimal design of a
remote heating network.
*System modelling and optimization*. Springer, 1986, 25-33. - C. Vercellis. A probabilistic analysis of the set packing
problem.
*Stochastic programming*. Springer, 1986, 272-285. - A. Frigessi, C. Vercellis. A probabilistic analysis of Monte
Carlo algorithms for a class of counting problems.
*Stochastic programming*. Springer, 1986, 272-285. - C. Vercellis. A threshold for multiple edge coverings in random
hypergraphs.
*Annals of Discrete Mathematics*25 (1985), 311-320. - A. Frigessi, C. Vercellis. An analysis of Monte Carlo algorithms
for counting problems.
*Calcolo 27*(1985), 413-428. - P.M. Camerini, C. Vercellis. The matroidal knapsack: a class of
(often) well-solvable problems.
*Operations Research Letters*3 (1984), 157-162. - C. Vercellis. A probabilistic analysis of the set covering
problem.
*Annals of Operations Research*1 (1984), 255-271. - F. Maffioli, M.G. Speranza, C. Vercellis. Randomized algorithms:
an annotated bibliography.
*Annals of Operations Research*1 (1984), 331-345. - F. Archetti, C. Vercellis. An application of nonlinear
programming techniques to the energy-economic optimization of
buildings design.
*Optimization techniques*. Springer, 1980, 569-576.

### Papers in international books

- C. Orsenigo, C. Vercellis. Protein folding classification
through multicategory discrete SVM In:
*Mathematical Methods for Knowledge Discovery and Data Mining*, G. Felici and C. Vercellis eds., IGI, 2007, 116-129 . - C. Orsenigo, C. Vercellis. Rules induction through discrete
support vector decision trees. In:
*Data Mining and Knowledge Discovery. Approaches Based on Rule Induction Techniques*, E. Triantaphyllou and G. Felici eds., Springer, 2006, 305-325. - F. Fumero, C. Vercellis. Investigating the determinants of sales
agents efficiency via data envelopment analysis.
*Operations Research*2000, Springer, 2000, 471-476. - C.G.E. Boender, A.H.G. Rinnooy Kan, C. Vercellis. Stochastic
optimization methods.
*Stochastics in combinatorial optimization*. World Scientific, 1987, 94-112. - F. Maffioli, M.G. Speranza, C. Vercellis. Randomized algorithms.
*Combinatorial Optimization*. Wiley, 1985, 89-105. - F. Archetti, A. Frigessi, C. Vercellis. Variance reduction
techniques in Monte Carlo evaluation of the reliability of
stochastic networks.
*Applied Optimization Techniques in Energy Problems*. Teubner, 1985, 63-79. - F. Archetti, D. Ballabio, C. Vercellis. Cost-benefit analysis of
insulation in buildings via nonlinear optimization.
*Numerical Optimization of Dynamic Systems*. North Holland, 1980, 363-375.

### Papers in international conference proceedings

- C. Orsenigo, C. Vercellis. Classification of social networks
entities by exploiting relational measures.
*INFORMS Proc. Artificial Intelligence and Data Mining Workshop*, Seattle, 2007. - C. Orsenigo, C. Vercellis. Time series classification by
discrete support vector machines.
*INFORMS Proc. Artificial Intelligence and Data Mining Workshop*, Pittsburgh, 2006, 1-6. - C. Orsenigo, C. Vercellis. Hard separation in discrete support
vector machines with relational marketing applications.
*Proc. 2nd Int. Workshop on Data Mining and Adaptive Modelling Methods for Economics and Management*, Pisa, 2004, 111-123.