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Research Areas

Within this section, you can explore the primary research areas undertaken by the MIND laboratory. This represents the laboratory’s overarching activities, and not all members may be equally engaged in every activity

 
 
 

Natural Language Processing

Natural Language Processing (NLP) is a field of computer science and artificial intelligence that focuses on the interaction between computers and human language. The primary goal of NLP is to enable computers to understand, interpret, and generate natural language in a manner similar to humans. Through the analysis of semantics, syntax, and language structure, NLP enables machines to grasp its meaning.
Our team focuses on advancing Natural Language Processing (NLP) by addressing complex challenges such as hate speech detection, sentiment analysis, and topic modeling.

We have developed models for automatic misogyny identification, including the detection of misogynistic language on Twitter and the classification of misogynistic content in memes. Additionally, we have explored unintended biases in misogyny detection systems and proposed methods for bias mitigation. In the realm of topic modeling, our research includes cross-lingual zero-shot approaches using contextualized embeddings and the development of tools like OCTIS for comparing and optimizing topic models.

All Related Projects

List of Natural Language Processing Projects

Machine Learning

Machine Learning is a field of artificial intelligence that focuses on the development of algorithms and models enabling computers to learn from data and improve their performance over time. Unlike traditional programming, where instructions are manually coded, in Machine Learning, machines are trained through exposure to large amounts of data, so they can learn to recognize patterns, draw conclusions, and make autonomous decisions.

We explore transformer-based architectures for detecting harmful online content and develop strategies to reduce biases in automated decision-making, while also investigating model behavior at different interpretability levels to understand their decision process. Additionally, our work extends to optimizing topic modeling with contextualized embeddings and zero-shot learning approaches, enhancing cross-lingual adaptability.

All Related Projects

List of Machine Learning Projects

Optimization

Optimization in the field of computer science refers to the process of enhancing or fine-tuning the efficiency, performance, and effectiveness of computer systems, algorithms, resources, or processes. This may involve seeking better solutions for complex problems, optimizing the utilization of computational resources, maximizing software performance, reducing execution times, and more.

Our team integrates advanced optimization techniques into various domains to enhance the efficiency and effectiveness of computational systems.
In the healthcare sector, we have developed machine learning-driven diagnostic pipelines, such as those utilizing Raman spectra of saliva samples for disease detection. In the field of transportation, our research focuses on data science applications to improve system performance and decision-making processes.

All Related Projects

List of Optimization Projects

Networks Analysis

Network Analysis is a branch of data analysis that examines and interprets the relationships and interactions between individual entities within a complex system, often represented as nodes and edges in a network graph. By studying these connections, Network Analysis uncovers patterns, structures, and dynamics that may not be apparent through traditional data analysis methods.

Our team employs Network Analysis to investigate complex systems, with a particular emphasis on social networks and transportation systems. We have developed innovative approaches for sentiment analysis, such as the Approval Network model, which examines user interactions to enhance the understanding of sentiment dynamics within social platforms.
In the field of transportation, our research focuses on optimizing mobility networks, analyzing traffic flow patterns, and improving decision-making processes for urban mobility.

All Related Projects

List of Networks Analysis Projects

Discover all Active and Expired Projects

Press the button below to view all the active and completed projects of the MIND research laboratory

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Work With Us

Join the research group of the MIND laboratory. Explore the opportunities and get in touch with us

Postdoc &
Scolarship
position
Contact the MIND Lab

Postdoc & Scolarship Position

Please reach out to us at the provided email address with the subject line ‘Application for Postdoc/Scholarship Opportunity’. Share a brief description about yourself and your proposal, including links to relevant publications and attaching your curriculum vitae (CV)

Enza.Messina@Unimib.it
Internships
& Theses for
students (it)
Postdoc &
Scolarship
position
Contact the MIND Lab

Postdoc & Scolarship Position

Please reach out to us at the provided email address with the subject line ‘Application for Postdoc/Scholarship Opportunity’. Share a brief description about yourself and your proposal, including links to relevant publications and attaching your curriculum vitae (CV)

Enza.Messina@Unimib.it
Internships
& Theses for
students (it)

Models in Decision Making and Data Analysis

enza.messina@unimib.it
123456789
Viale Sarca 336, Milan – Building U14, 2nd Floor, Room 1042

Models in Decision Making and Data Analysis

enza.messina@unimib.it

123456789

Viale Sarca 336, Milan – Building U14, 2nd Floor, Room 1042