Meet the Finalists of the 2026 ISSNAF Young Investigator Mario Gerla Award
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 2026 edition:
Mattia Fazzini
Riccardo Paccagnella
Federico Rossi
The winner will be announced on November 12 at the ISSNAF 2026 Annual Event in Washington, D.C.
The Jury, chaired by Elisa Bertino (Purdue University), also includes Ferdinando Fioretto (University of Virginia) and Anna Squicciarini (Penn State University).
Learn more about the three finalists and their researches.
MATTIA FAZZINI
Mattia Fazzini is an Assistant Professor in the Department of Computer Science & Engineering at the University of Minnesota. He received his Ph.D. in Computer Science from the Georgia Institute of Technology.
His research focuses on improving software quality through automated techniques for software testing and maintenance. A central theme of his work is transforming information generated throughout the software lifecycle into effective tests. His research has led to innovative techniques for automatically generating tests, reproducing software failures, and maintaining test suites as software evolves. These techniques have demonstrated significant improvements in testing effectiveness and developer productivity, with contributions adopted by real-world software projects. His work has been published in leading software engineering conferences and journals, including ICSE, ISSTA, ASE, TSE, and TOSEM.
His research has been recognized with the National Science Foundation CAREER Award, the Facebook Testing and Verification Award, and Distinguished Paper Awards from IEEE and ACM. His work has also received funding from industry partners, including Medtronic.
He actively contributes to the research community, serving on program committees for major conferences (e.g., ICSE, FSE, ISSTA, ASE) and reviewing for leading journals (e.g., TSE, TOSEM).
Research Focus Software plays an essential role in nearly every aspect of modern life, making its quality
and reliability increasingly important. Mattia Fazzini's research develops automated techniques that help developers test software more effectively.
The central idea behind his work is that valuable information is continuously generated throughout the software lifecycle. Software executions reveal how systems behave, user-reported failures expose problems, and software logs provide insights into execution paths. His research transforms this information into effective tests through three complementary areas: test generation, failure reproduction, and test maintenance.
His techniques have demonstrated significant practical benefits. They can automatically generate focused tests from complex software executions, reproduce a large portion of analyzed real-world software failures, and improve existing tests, with 80 pull requests accepted into real-world projects. His research on failure reproduction has also involved professional developers from Google, Meta, and Netflix in user studies, demonstrating the practical relevance of his work.
Building on these contributions, his NSF CAREER research aims to automatically generate, recommend, and maintain focused tests by reusing existing testing resources. Ultimately, his research helps developers identify problems earlier, resolve failures more efficiently, and deliver more reliable software.
About Him
Mattia Fazzini earned his undergraduate degree from the University of Ferrara in his hometown, followed by a master's degree from Politecnico di Milano, before moving to the United States to pursue his Ph.D. He is a founding member of the ISSNAF Minnesota Chapter and is committed to strengthening scientific ties between Italy and the United States. Through connections established via ISSNAF, he hosted an Italian Ph.D. student in his research lab last year and is currently hosting another. He is passionate about mentoring the next generation of Italian researchers and creating opportunities for research collaborations between the United States and Italy.
RICCARDO PACCAGNELLA
Riccardo Paccagnella is an assistant professor of computer science at Carnegie Mellon University. His research is in system security, with a focus on uncovering and mitigating new classes of microarchitectural vulnerabilities and their impact on secure software. His work prompted major companies and open-source projects to change widely deployed systems and update security guidance, received an IEEE S&P Distinguished Paper Award and several "Top Picks" distinctions, and attracted extensive national and international press coverage.
Research Focus
Modern computing relies on abstractions that assume hardware behaves predictably with respect to sensitive data. This assumption is increasingly false. Optimizations that make modern hardware faster and more energy-efficient can also be exploited by attackers to reveal sensitive data, even when software follows established security practices. Because these optimizations are complex and largely outside software’s control, such leakage is difficult to reason about and even harder to prevent.
Riccardo's research addresses this problem by developing a systematic understanding of how hardware optimizations undermine software security guarantees and designing principled defenses that preserve those guarantees in real systems. His work has uncovered entirely new vulnerability classes and demonstrated some of the first timing attacks on constant-time cryptographic code (i.e., code specifically designed to prevent timing leakage). He has also designed defenses that provably limit leakage while preserving the benefits of hardware optimizations. Finally, he has introduced some of the first practical methods to repurpose hardware optimizations for stealthy computation.
FEDERICO ROSSI
Dr. Federico Rossi is a Robotics Technologist with the Multi-Agent Robotics Group (358P) within the Robotics section of NASA’s Jet Propulsion Laboratory. He received a Ph.D. in Aeronautics and Astronautics at Stanford University under the guidance of Prof. Marco Pavone in 2018 with a thesis On the Interaction between Autonomous Mobility-on-Demand Systems and the Built Environment: Models and Large Scale Coordination Algorithms. Prior to that, Federico received a dual M.Sc. in Space Engineering from Politecnico di Milano and Politecnico di Torino, Italy, in 2013. He is an alumn of the Alta Scuola Politecnica. At JPL,
Federico leads the multi-agent autonomy team for NASA’ Coordinated Autonomous Distributed Robotics Explorers (CADRE) mission, which will deliver a team of three autonomous rovers to the Moon’s Reiner Gamma region. Federico’s research focuses on decision-making under uncertainty in multi-agent robotic systems and operations of autonomous agents, with applications to planetary exploration and Earth science. At JPL, he has developed autonomy technologies for cooperative robotic exploration, joint orbit and observation optimization for exploration of small bodies, and under-ice navigation in Antarctica.
Research Focus
Teams of autonomous driving, swimming, and flying robots hold immense promise to revolutionize planetary and Earth science. Distributed gas sensors can localize observed methane emissions on Mars to investigate potential signatures of life; altitude-controlled aerobots can illuminate Venusian geology by monitoring volcanic eruptions up close; under-ice vehicles are vital to measure Antarctic glacier melt rates to ground climate models; and coordinating satellite constellations can deliver rapid data to humanitarian organizations following natural disasters.
Realizing this vision requires autonomy tools capable of coordinating robotic teams faster than ground operators can manage. Algorithms must adapt to infrequent communication, tight power and computational budgets, and hardware failures; they must be provably safe to protect high-value assets; they must handle heterogeneous platforms with diverse sensors; and their decisions must remain interpretable to scientists.
Dr. Rossi's research develops foundational tools to tackle these challenges. Building on his work as multi-agent autonomy lead for NASA’s CADRE lunar rover mission, Dr. Rossi designs coordination algorithms for Venus aerobots, under-ice Antarctic explorers, and spacecraft constellations, alongside intuitive user interfaces that enable scientists to seamlessly interact with autonomous robotic teams.
About Him Federico is passionate about exploration and about building technologies that will help scientists answer the great questions.
He studied in Milan, Turin, Toulouse, and Stanford before landing at NASA JPL, where he helps put cameras (and radars, and spectrometers, and seismometers) in new places across the Solar System.
Federico loves mentoring, and has hosted a number of students (many of them Italian) for research internships at JPL.
When he is not in the office, you can likely find him roaming the Mojave desert (if at night, with binoculars), or helping rhino conservation with his wife Valentina.
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