Established in 2020, this year’s edition recognizes Italian researchers in the USA providing fundamental contributions to all aspects of artificial intelligence, including technological and engineering advancements, transformative applications across disciplines, education, economic impact, ethical development to support societal needs, and solutions to mitigate harmful use of AI.
We are excited to congratulate the exceptional finalists for this year's edition:
Luca Luceri
Marco Romanelli
Carmelo Sferrazza
Discover more about their groundbreaking research, which they will present to the Jury, led by Prof. Fil Menczer, from Indiana University, during the Symposium on October 21st, 9:45am PST.
Register here: 2024 YI Embassy of Italy Award Symposium.
The winner will be revealed at the ISSNAF 2024 Annual Event in Washington D.C. on November 14.
LUCA LUCERI
Luca Luceri has an extensive background in computer science, with a focus on using AI and machine learning for social good. He began his academic journey with a Bachelor's degree in Telecommunications Engineering from the Polytechnic University of Bari (2009-2012), followed by a Master's from the Polytechnic University of Milan (2012-2014). He then pursued a Ph.D. in Computer Science at the University of Bern, Switzerland (2015-2020), which set the stage for his future research.
After earning his Ph.D., Luca joined the Information Sciences Institute (ISI) at the University of Southern California (USC) as a Postdoctoral Fellow (2022-2023), later becoming a Research Scientist (2023-2024). Currently, he serves as a Research Assistant Professor at USC and Lead Scientist at ISI, where his work centers on AI, computational social science, and human-machine interaction.
Luca is co-Principal Investigator of the DARPA-funded INCAS project, focused on detecting and tracking geopolitical influence campaigns, and the Swiss NSF-funded CARISMA project, which develops computational models to support policy recommendations for mitigating online harms. Before his USC tenure, he worked as a Research Scientist at the University of Applied Sciences and Arts of Southern Switzerland (2020-2022), further advancing his expertise in data and network science.
https://www.linkedin.com/in/luceriluc/ https://www.isi.edu/directory/lluceri/ https://www.luceriluc.it/
Research Focus
Driven by the escalating threats posed by modern communication technologies, social media, and AI, my research is dedicated to identifying, analyzing, and mitigating online harms within socio-technical systems. By leveraging AI and data science, I have developed advanced methods to detect influence campaigns that span across geopolitical contexts, such as U.S. elections, the COVID-19 infodemic, and global conflicts. This work has led to tools that expose inauthentic actors, including state-sponsored trolls, and reveal their strategies for manipulating public opinion through the spread of misinformation. Additionally, I focus on identifying vulnerable sub-populations who are particularly susceptible to these deceptive efforts.
My contributions have set new benchmarks in the field and supported major frameworks like DARPA’s SocialSim and INCAS programs. Beyond academic impact, this research holds significant potential to inform policies aimed at safeguarding online communities, particularly from influence campaigns that threaten democratic processes, deepen societal divides, and incite real-world violence.
As the rise of Large Language Models (LLMs) introduces new risks, particularly in the creation of disinformation and personalized propaganda, my future work will focus on developing tools to evaluate and implement mitigation strategies. These efforts will target a range of online harms, including hateful, abusive, and deceptive behaviors, ensuring a more secure and informed digital landscape.
About me Luca Luceri is a Research Assistant Professor at the University of Southern California (USC), where his research focuses on using machine learning, data science, and network analysis to address online harms in socio-technical systems. His work spans two key areas. First, he applies AI and machine learning to detect and analyze coordinated inauthentic behavior and orchestrated influence campaigns on social media platforms. Second, he uses network and data science to examine the vulnerabilities of organic social media users, exploring the mechanics of influence, the spread of misinformation, and the processes of internet-fueled radicalization.
Luca’s long-term research goal is to strengthen the resilience of the digital information ecosystem. This includes not only advancing technical solutions but also considering ethical and legal frameworks for social media regulation. Ultimately, his work aims to develop effective mitigation strategies that can curb online harms and protect vulnerable users from exploitation.
MARCO ROMANELLI
Before joining Hofstra University as an Assistant Professor, Marco Romanelli was a Research Associate in the Department of Electrical and Computer Engineering at both NYU Tandon School of Engineering and Rutgers University. He holds a B.Sc. and M.Sc. from the University of Siena in Italy and earned his Ph.D. from École Polytechnique and Inria in Paris, France, where his thesis was honored with the prestigious UFI Vinci Best Thesis Award.
His research lies at the intersection of information theory and machine learning, with a strong emphasis on developing trustworthy and secure AI systems. Romanelli has authored numerous papers in leading conferences, including NeurIPS, ICML, ICLR, AISTATS, ACM CCS, and IEEE CSF, and has also served as a reviewer for several of these top-tier venues.
Research focus
My research advances Machine Learning within the framework of Trustworthy AI, integrating principles from Information Theory, Privacy, Security, and Inference Error Detection. It is centered around two main areas of focus:
Security and Privacy in Machine Learning: I develop methods to enhance security and privacy through machine learning techniques. This includes creating sanitized data with generative models and designing formal attack frameworks to quantify privacy risks.
Trustworthy AI and Detection of Unwanted Behaviors: I employ entropy and statistical dissimilarity to measure uncertainty in model predictions and detect issues such as incorrect predictions, adversarial attacks, out-of-distribution inputs, and data poisoning.
My contributions are particularly impactful in deep neural networks, especially in safety-critical sectors like autonomous driving, medical diagnosis, and fraud detection, where reliance on non-transparent, pre-trained models is common. Collaboration between scientists and policymakers is essential to ensure AI's development and application align with societal benefits. My research takes an important step in this direction, offering strong theoretical guarantees to address pressing challenges. By tackling key concerns in trustworthiness, security, and privacy, my work supports the creation of ethical, people-centric AI systems.
About me
I am truly honored to be selected as a finalist for this award. With an academic career spanning three countries and two continents, I bring a broad, diverse perspective to my work. My expertise lies in combining a solid theoretical foundation, particularly in information theory, with advanced research to uncover the root causes of machine learning failures and develop effective solutions.
I believe in the importance of close collaboration between scientists and policymakers to ensure AI serves the public good. This recognition inspires me to continue advancing research in AI, focusing on trustworthiness, security, and privacy, while contributing to the development of ethical, human-centered AI systems that make a positive impact on society.
CARMELO SFERRAZZA
Carmelo (Carlo) Sferrazza is a postdoctoral researcher in AI and Robotics at UC Berkeley, working under the guidance of Prof. Pieter Abbeel. His research is focused on advancing humanoid intelligence, with the goal of enabling robots to assist humans in everyday tasks and navigate complex environments.
Carlo completed his Ph.D. at ETH Zurich in 2021, where he worked with Prof. Raffaello D'Andrea. His doctoral research centered on equipping robots with a sense of touch, a breakthrough aimed at improving their ability to interact with the physical world. Prior to that, he earned a Master’s degree in Robotics, Systems, and Control from ETH Zurich in 2016, following a Bachelor's degree in Automation Engineering from Politecnico di Milano. He also participated in an exchange program at Tongji University in Shanghai, where he earned a Double Bachelor's Degree in Information Technology Engineering (2016).
Carlo’s work has earned several accolades. His Ph.D. thesis was awarded the prestigious ETH Medal, and in 2022, he was recognized as a Robotics Science and Systems Pioneer. He has also received an SNSF Postdoctoral Fellowship, the Best Paper Award at the 2020 IEEE International Conference on Soft Robotics, and the ETEL Award in 2017.
Research Focus Humanoid robots are often seen as ideal generalist agents due to their potential to assist humans in a wide range of tasks within human-centric environments. However, despite significant progress in humanoid hardware, current AI algorithms still face challenges in enabling robots to autonomously perform practical, everyday tasks. My research addresses this gap by developing robot-aware learning architectures and enhancing robots' environmental perception through the integration of tactile sensing, similar to the human sense of touch.
By improving both the capabilities and safety of robots, my work has the potential to transform industries such as household robotics, logistics, manufacturing, and healthcare. These advancements could lead to greater workplace efficiency and reduced human exposure to hazardous environments. Moreover, incorporating tactile sensing into embodied AI systems will foster more intuitive and effective human-robot interactions, unlocking new possibilities in areas like eldercare and rehabilitation.
About me
Born and raised in Sicily, Italy, I am a passionate robotics and AI researcher driven to enable robots to assist humans in their daily tasks. I moved to UC Berkeley about two years ago for my postdoctoral research, after completing my PhD studies in Zurich, Switzerland.
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