Alessandro Moschitti

Information Engineering and Computer Science Department

University of Trento

moschitti [at]



My iKernels Group



Teaching Activities



Main Links

 - iKernels
 - Research Program: Deep and
   Structured Machine Learning


Alessandro Moschitti is a professor of the CS Department of the University of Trento, Italy. He is currently a Principal Research Scientist of the Qatar Computing Research Institute (QCRI), within the Hamad Bin Khalifa University.
He obtained his PhD in CS from the University of Rome in 2003. He has worked as (i) an research fellow for the University of Texas at Dallas, (ii) as a visiting professor for the University of Columbia (NY), Colorado and John Hopkins and (iii) as visiting researcher at the IBM Watson Research center (participating at the Jeopardy! Challenge) and at MIT-CSAIL.
His expertise concerns theoretical and applied machine learning (ML) in the areas of Natural Language Processing (NLP), Information Retrieval (IR) and Data Mining. He has devised innovative structural kernels and neural networks for advanced syntactic/semantic processing, documented by more than 260 scientific articles published in NLP, IR and ML communities.
He has been the General Chair of EMNLP 2014, a PC co-chair of CoNLL 2015, an action editor of TACL, and on the editorial board of MLJ, JAIR and JNLE. He has received four IBM Faculty awards, one Google Faculty award, five best paper awards and the best researcher award from Trento University. He has lead many projects, currently is the PI (QCRI side) of a large collaboration project between MIT CSAIL and QCRI.


Machine Learning for Natural Language Processing, Information Retrieval and Data Mining

The iKernels group led by Prof. Moschitti carries out advanced research on machine learning methods for syntactic and semantic processing of natural language. The group aims at improving the state of the art in Information Search and Retrieval by enriching language models (typically based on bag-of-words) with structural representations and semantics.

In the context of natural language, the group owns internationally recognized expertise in the following applications: Question Answering, FrameNet and PropBank Predicate Argument Extraction (Semantic Role Labeling), Relation Extraction, Syntactic and Semantic Parsing, Co-reference resolution, Text Categorization, Textual Entailment Recognition, Word Sense Disambiguation, Entity Recognition and Normalization, Opinion Mining, Speech and Noisy Text Processing, Text Similarity, Summarization and Link Open Data.

Regarding Machine Learning, the group has developed new theory and methods for Kernel Machines: Kernel Methods, Structural Kernels, Support Vector Machines, On-line Learning, Structured Output Spaces, Multi-label and Hierarchical Classification and Re-Ranking, and reverse kernel engineering for efficient processing and automatic feature engineering.
In the last two years, they have developed breakthrough models for Neural Networks in opinion mining, question answering and named entity recognition.

Theory and methods are also applied to broader ICT areas than natural language processing and Information Retrieval, such as Automatic Telecommunication Network Management, Electronic Failure detection, Anomaly Detection, Bioinformatics, Automatic Software Analysis (e.g., code classification).


Group Awards (selected)

  Other Awards

Selected Past Funded Projects

Past Academic Support to the Research Community (selected)

PC committees: too many to be listed (see my Curriculum)

News/Current Activities

Senior PC member WWW 2018
Senior PC member AAAI 2018

Editorial Boards

Journal of Natural Language Engineering (since 2013)

Journal of Artificial Intelligence Research  (since 2012)

Journal of Data Semantics
(since 2011)

  SIGIR 2013 
Kernel-based Learning to Rank with Syntactic and Semantic Structures


ACL 2012:
State-of-the-Art Kernels for Natural Language Processing

Coling 2010
Kernel Engineering for Fast and Easy Design of Natural Language Applications

Interspeech 2010
Kernel Engineering for Fast and Easy Design of Natural Language Applications

ACL Workshops

Co-Chair of TextGraphs-6: Graph-based Methods for NLP (ACL-NAACL 2011)

Co-Chair of Learning Structured Information in Natural Language Applications 
(EACL 2006)


  Web Question Answering, Beyond Factoids 2016

Semantic Matching in IR 2014

EternalS Workshops

Co-Chair of 3rd International Workshop on Eternal Systems 2013 (EternalS'13)

Co-Chiar of 2nd International Workshop on Eternal Systems: JIMSE'12 (EternalS'12)

Co-Chair of 1st International Workshop on Eternal Systems (EternalS'11)

Chair of EternalS Track at ISoLA (International Symposium on Leveraging Applications of Formal Methods 2010)

John Hopkins Summer Workshop 
(JHU 2007)

Automatic Text Categorization: from Information Retrieval to Support Vector Learning

A didactic book introducing Support Vector Machines and Text Categorization