PhD, Politecnico di Torino, Italy
🎓 Federico D’Asaro, born on April 18, 1997, in Palermo, Italy, is a dedicated Ph.D. student in Computer and Control Engineering at the Polytechnic University of Turin (PoliTo). With a strong foundation in data science, AI research, and practical applications, Federico is deeply engaged in advanced studies focused on multimodal feature spaces and AI fairness. His work involves developing cutting-edge solutions in AI, including sentiment analysis, speech emotion recognition, and recommendation systems. Federico is also active in academic mentorship, contributing to research papers, and project proposals.
Publication Profile
Strengths for the Award:
- Academic Excellence: Federico has demonstrated exceptional academic performance, achieving a perfect score of 110/110 cum laude in his BSc in Engineering and Management and a perfect score of 110/110 in his MSc in Data Science and Engineering. His strong academic foundation is complemented by his involvement in research during his Ph.D. studies at the Polytechnic University of Turin.
- Research Contributions: Federico’s ongoing research on the Modality-Gap in multimodal feature space, along with multiple article submissions to prestigious conferences like ECAI 2024, ESWA, and AICT 2024, highlights his active engagement in advancing AI research. His work spans various AI applications, including business analytics, sentiment analysis, speech emotion recognition, and retrieval and recommendation systems, showcasing his versatility and innovation in AI and machine learning.
- Professional Experience: As an AI Applied Researcher at LINKS Foundation, Federico has played a significant role in developing state-of-the-art (SOTA) AI models and applications, demonstrating his practical skills and industry experience. His participation in writing project proposals, deliverables, and AI conference paper reviews reflects his ability to contribute both technically and academically.
- Supervision and Mentorship: Federico has experience in supervising master’s thesis and internship students and serving as a tutor for the Applied Data Science Project master’s degree course. This experience indicates his leadership qualities and commitment to fostering the next generation of researchers.
- Technical Proficiency: Federico is proficient in multiple programming languages (Java, Python, R), deep learning frameworks (TensorFlow, PyTorch), and data tools (HDFS, Apache Spark, SQL). His diverse skill set enables him to handle complex AI and data science projects effectively.
Areas for Improvement:
- Language Skills: While Federico has a B2 level in English, which is sufficient for research communication, enhancing his proficiency to a higher level could improve his ability to engage with a broader international research community more effectively.
- Broader Research Impact: Although Federico has a solid foundation in AI and data science, focusing on publishing in top-tier journals and increasing citations could enhance his visibility and impact in the global research community.
- Collaboration and Networking: Expanding his network through international collaborations and participating in more global conferences could provide greater exposure and opportunities for interdisciplinary research.
Education
🎓 Federico completed his MSc in Data Science and Engineering from the Polytechnic University of Turin (2020-2021), graduating with a perfect score (110/110). His thesis, titled “FairML: Preventing Algorithm Discrimination,” reflects his commitment to ethical AI practices. Prior to this, he pursued individual courses in databases and programming at the same university and earned a BSc in Engineering and Management from the University of Palermo (2016-2019), graduating cum laude. Federico began his academic journey at the Scientific Lyceum “Galileo Galilei,” where he obtained his high school diploma in 2016.
Experience
💼 Federico has been a Ph.D. student at PoliTo since November 2023, focusing on multimodal feature space research. Concurrently, since December 2021, he has been an AI Applied Researcher at LINKS Foundation, where he has developed several AI applications, including business analytics tools, recommendation systems, and speech emotion recognition models. His experience also includes an internship at Technology Reply, where he specialized in NLP, sentiment analysis, and textual data modeling. Federico has reviewed AI conference papers, supervised master’s students, and served as a tutor for the Applied Data Science Project at PoliTo.
Research Focus
🔍 Federico’s research interests lie in AI ethics, multimodal learning, and the development of crossmodal recommendation systems. He is particularly focused on exploring modality gaps in multimodal feature spaces and preventing algorithmic unfairness. His work at LINKS Foundation includes using state-of-the-art pre-trained models for vision-language tasks, speech emotion recognition, and language models for tutoring systems.
Awards and Honours
🏆 Federico has earned multiple accolades, including authorization to practice as an Information Engineer (Italy, Section A, July 2022). He has also achieved the B2 First (FCE) English certification and actively contributes to high-impact research papers and AI conference reviews.
Publication Top Notes
📚 Federico’s notable publication, “Zero-Shot Content-Based Crossmodal Recommendation System,” co-authored with Sara De Luca, Lorenzo Bongiovanni, and Giuseppe Rizzo, was published in Expert Systems with Applications (2024). It explores innovative approaches to recommendation systems leveraging crossmodal learning.
Zero-Shot Content-Based Crossmodal Recommendation System
Sensitive attributes disproportion as a risk indicator of algorithmic unfairness
Conclusion:
Federico D’Asaro is a promising researcher with a strong academic background, substantial research contributions, and relevant professional experience in AI and data science. His active involvement in cutting-edge AI research, combined with his technical skills and mentorship abilities, makes him a suitable candidate for the Research for Best Researcher Award. By improving his English proficiency, aiming for publications in top-tier journals, and expanding his international research network, Federico could further strengthen his candidacy and enhance his impact in the field.