The Machines, Languages, and Networks (MLN) Team Manifesto
Welcome to the website of the Machines, Languages, and Networks (MLN) team, a collective force of innovation and intellect built up and led by Andrea Tagarelli, powered by skilled and passionate computer-science researchers and Ph.D. students. We invite you to join us on a journey at the forefront of cutting-edge AI-based research, where the realms of Machine Learning, Natural Language Processing (NLP), Graph Mining, and Network Science converge to unravel the complexities of emergent phenomena and pave the way for transformative applications across diverse domains.
We aim to explore avenues with the potential for high societal impact, also in crucial domains such as law and healthcare. We’re dedicated to solving computational problems in these fields and using what we discover to make things that actually help in everyday life. The MLN team thrives on the belief that diversity in research questions leads to richer, more comprehensive answers. We delve into the intricacies of semantic search and generative AI in diverse data domains — documents, images, sequential and audio data — decipher the dynamics of Web3, NFTs, and decentralized online social networks, navigate the complex landscapes of multilayer heterogeneous networks and knowledge graphs, deal with advanced optimization problems to improve our understanding of challenging scenarios dealing with such aspects as fairness, diversity, polarization, and many more. As we venture into possibly uncharted territories, our collective goal is not only to expand the boundaries of what is known but also to foster innovation that transcends academia and finds meaningful applications in the world at large. Join us in this exciting expedition where theory meets practice, and together, let’s chart new frontiers in the ever-evolving landscape of research.
Our research endeavors span a diverse array of topics, primarily focusing on the intersection of Machine Learning, Natural Language Processing, Graph Mining and Network Science. Our research activities aim to provide insights into emergent phenomena and develop applications with both theoretical and practical significance in various domains, possibily of high-societal impact, such as law and healthcare. Topics include Graph Mining and Learning, Social Media, NLP and Information Retrieval, Multimodal Learning, Advanced Clustering Problems.
Here at the MLN Team, technology transfer comes with the primary intention of pursuing a profitable synergy with the research sphere: involvement in research & development projects continuously represents a testbed for ideas and methods built within scientific research environments and, conversely, the problems and challenges identified in research project activities become a stimulus to explore new directions of research, possibly in an interdisciplinary way.
The MLN Team is based in the DIMES Department, University of Calabria, 87036 Rende, Italy.