Meet the Finalists of the 2025 ISSNAF Young Investigator Mario Gerla Award
- chiaragallo7
- 4 days ago
- 5 min read
Established by the Gerla family in 2019, this award is in memory of Dr. Mario Gerla, pioneer in computer networking, professor of Computer Science at UCLA and ISSNAF founding member.
We are thrilled to announce and congratulate the exceptional finalists of the 2025 edition:
Antonio Loquercio
Riccardo Paccagnella
Tiziano Piccardi
Discover the three finalists and their innovative research, which they will present to the jury chaired by Prof. Leila De Floriani (University of Maryand) and including Dr. Elisa Bertino (Purdue University) and Prof. Fil Menczer (Indiana University)
The winner will be announced at the ISSNAF 2025 Annual Event in Washington, D.C., on November 6.
ANTONIO LOQUERCIO
Antonio Loquercio is an Assistant Professor at the University of Pennsylvania. He received his PhD and M.Sc. from UZH and ETH Zurich in 2021 and 2017. His research interests include learning-based robotics, computer vision, and machine learning. His work includes seminal results on simulation to real-world transfer for sensorimotor control. He is the recipient of the 2017 ETH Medal for Outstanding Master Thesis, the Best System Paper Award at the Conference on Robot Learning (CORL) 2018, the RSS’20 Best Paper Award Honorable Mention, and the T-RO’20 Best Paper Award Honorable Mention. His article on superhuman drone racing was featured on Nature's cover. He received the Georges Giralt PhD Award, the most prestigious award for PhD dissertations in robotics in Europe.
Research Focus
What is the role of perception? The dominant view in the research community embraces the idea that perception systems should be designed to create a detailed replica of the world. However, I believe that the goal of perception should be different: to construct a model of the world that is sufficient for effective decision-making. My research focuses on understanding the relationship between the accuracy of this model and the performance of autonomous systems in downstream tasks. Through this paradigm, my research has driven seminal advances in robotics, most notably the design of the first autonomous robot to outperform a human champion in drone racing. If successful, this research agenda could enable new capabilities for controlling complex systems that are currently too difficult to model, such as large-scale wind farms. Enabling advanced control in these settings would significantly boost operational efficiency and have a transformative impact on domains where learning-based techniques have traditionally struggled, such as the power grid.
About Him
Antonio is known for his research on high-performance agile robotics, particularly for drones and legged robots. Growing up in the countryside near Rome, he was always fascinated by the wonders of nature. The desire to understand and recreate such wonders motivated him to embark on a career in robotics. He was an undergraduate at the University of Rome, Tor Vergata, where he studied mechanical and electrical engineering. Afterward, he moved to Zurich, Switzerland, where he was first a master's and then a graduate student in computer science at the Swiss Federal Institute of Technology (ETH) and the University of Zurich.
RICCARDO PACCAGNELLA
Riccardo Paccagnella is an Assistant Professor of computer science at Carnegie Mellon University. His research interests are in computer security. His work has been covered by national and international press—including Ars Technica, New Scientist, and Wired—and recognized with several distinctions, including three "Top Pick" awards, three "Pwnie" awards, and a David J. Kuck Outstanding PhD Thesis Award. In light of his research, the cryptographic community, the open source community, and several companies (including Google, Microsoft, Apple, Intel, and Cloudflare) have taken action that includes patching their products and/or creating new guidance for writing secure software.
Reaserch Focus
Today's hardware cannot keep secrets. Indeed, a wave of recent work has demonstrated how attackers can exploit hardware features to leak software's sensitive data. These attacks have shaken the foundations of computer security and caused a disruption in the software industry. Yet, because hardware is highly complex and was long designed without sufficient attention to security, we still lack a comprehensive understanding of the problem—let alone how to fix it. Moreover, technological trends (e.g., the slowing of Moore’s law) are exacerbating the issue and suggest we may have only seen the tip of the iceberg.
Riccardo's research addresses this problem by developing a fundamental understanding of software security in the context of today's leaky hardware. For example, Riccardo's work demonstrated how several classes of hardware optimizations enable some of the first timing attacks on constant-time code (fundamentally undermining the prevailing mitigation strategy against these attacks); it also explored how these optimizations enable stealthy computation via microarchitectural weird machines. Riccardo is expanding these efforts by developing new techniques to understand and mitigate these vulnerabilities.
TIZIANO PICCARDI
Tiziano Piccardi is an Assistant Professor of Computer Science at Johns Hopkins University and a member of the Data Science and AI Institute. Previously, he was a postdoctoral scholar in the HCI group at Stanford University and earned his PhD in data science from EPFL in Switzerland. He has been a long-term collaborator of Wikimedia Research and is a recipient of fellowships from the Swiss National Science Foundation and Stanford Impact Labs.
His research lies at the intersection of social computing, artificial intelligence, and human-computer interaction, focusing on the design of online platforms that better serve both individuals and society. He studies social media, open knowledge projects such as Wikipedia, and user-facing AI systems. His work has been published in leading computer science venues and interdisciplinary journals.
He is also an active contributor to the research community, serving on program committees for major conferences (e.g., ICWSM, CHI, CSWC) and as a reviewer for journals (e.g., PNAS).
Research Focus
Tiziano Piccardi's research focuses on the online information ecosystem, aiming to design systems that simplify and empower access to reliable and meaningful information. Today, digital platforms have a profound impact on the real world by shaping how people learn, explore, and make decisions; yet, their design and algorithmic choices often lead to outcomes that are misaligned with societal needs, such as reinforcing divisions or limiting access to knowledge. Piccardi's work addresses this challenge by reimagining how technology can be designed to prioritize knowledge sharing, information reliability, and long-term societal benefit.
Through a long-term collaboration with the Wikimedia Foundation, Piccardi has advanced research on Wikipedia by modeling readership behavior at a global scale, developing methods to improve accessibility, and releasing AI models and datasets that have become resources for the broader research community. Complementing this work, his research on social media develops tools that enable independent experiments with alternative designs and explores how AI-driven ranking algorithms can be reimagined to better reflect human and societal values.
About Him
Piccardi is part of the ISSNAF mentoring program, where he advises Italian students interested in pursuing a PhD or research career in the United States.