Eugenio Grippo

Eugenio Grippo received his M.S. and Ph.D. in EE (Electrical Engineering) from
University of Southern California (USC), where he also conducted Postdoctoral studies
in Computer Science (CS); he received his “Automation and Industrial Control
Engineer” degree from Universidad Nacional de Quilmes (UNQUI, Buenos Aires,
Argentina).

Eugenio worked in the ANRG (Autonomous Network Research Group)
center at USC where he conducted research in machine learning, distributed
computing, IoT and cybersecurity. After that, he worked in the ICAROS LAB
(Interactive and Collaborative Autonomous Robotics Lab) at USC where he
contributed to the development of the UCLA buoyancy assisted legged
lightweight unit robot (UCLA BALLU).

Eugenio also worked as a Visiting Assistant Professor of Computer
Science at Occidental College, Los Angeles, USA; and as an Adjunct Professor
in Data Science at Pacific States University, Los Angeles, USA.

Eugenio’s research is at the nexus of mathematical modeling, network
science, and applied machine learning, addressing critical challenges in power
systems, cybersecurity, decentralized finance, and communications. He has
developed (along with colleagues) innovative applications of differential
geometry in power grid modeling and provided new insights into congestion
detection and load balancing, with implications extending to various types of
networks, including social and data networks. Looking ahead his research
endeavors to focus on designing low-latency, adaptive network synthesis
methods suitable for adversarial environments, and advancing curvature-based
analysis techniques for directed graphs to enhance the modeling of complex
communication and social networks. Through these interdisciplinary efforts he
aims to contribute robust, scalable solutions to some of the most pressing
technological challenges of our time.

RESEARCH INTEREST
Analysis of Networks
Internet of Things (IoT)
Decentralized Finance (DeFi)
Cybersecurity
Artificial Intelligence / Machine Learning (AI/ML)
Power Grid / Smart Grid
Control Systems

- Hekmati Arvin, Eugenio Grippo, Bhaskar Krishnamachari and Nishant
Jethwa."Correlation-Aware Neural Networks for DDoS Attack Detection in IoT
Systems". IEEE/ACM Transactions on Networking, May 8, 2024.

- Hekmati Arvin, Eugenio Grippo, and Bhaskar Krishnamachari. “Neural Networks for
DDoS Attack Detection using an Enhanced Urban IoT Dataset”. International
Conference on Computer Communications and Networks (ICCCN), July 25 – 28, 2022.

- Tzanis Anevlavis, Jonathan Bunton, Jared Coleman, Mine Dogan, Eugenio Grippo,
Abel Souza, Christina Fragouli, Bhaskar Krishnamachari, Matthew Maness, Karl Olson,
Prashant Shenoy, Paulo Tabuada, Gunjan Verma. “Network Synthesis for Tactical
Environments: Scenario, Challenges, and Opportunities”. SPIE Defense + Commercial
Sensing. Orlando, Florida, USA, April 3- 7, 2022.

- Jonckheere, Edmond, and Eugenio Grippo. “Anticipation of Line Tripping Cascade by
Grid Curvature and Entropy”. International Conference on Electrical, Computer and
Energy Technologies. Cape Town, South Africa, on Dec 9 – 10, 2021.
- Hekmati Arvin, Eugenio Grippo, and Bhaskar Krishnamachari. “Large-scale Urban
IoT Activity Data for DDoS Attack Emulation”. Proceedings of the 19th ACM
Conference on Embedded Networked Sensor Systems, pages 560-564, November 15-18,
2021.

- Krishnamachari, Bhaskar, Qi Feng, and Eugenio Grippo. “Dynamic Automated
Market Makers for Decentralized Cryptocurrency Exchange”. 2021 IEEE International
Conference on Blockchain and Cryptocurrency (ICBC), on May 3-6, 2021.

- E. Jonckheere, E. Grippo and R. Banirazi. “Curvature, Entropy, Congestion
Management and the Power Grid”. 3rd IEEE Conference on Control Technology and
Applications (2019 CCTA), Hong Kong, China, on August 19-21, 2019. (Chair of the
Section).

- E. Jonckheere and E. Grippo. “Ollivier-Ricci Curvature approach to Cost-Effective
Power Grid Congestion Management”. 31st Chinese Control and Decision
Conference (2019 CCDC), Nanchang, China, on June 3-5, 2019.

- E. Jonckheere, E. Grippo and Reza Banirazi, “Congestion Management for Cost-
effective Power Grid Load Balancing using FACTS and Energy Storage Devices
allocated via Grid Curvature Means”, 2019 American Control Conference, Philadelphia,
PA, USA on July 10-12, 2019. (Chair of the Section).

- E. Jonckheere and E. Grippo. “Effective resistance criterion for negative curvature:
application to congestion control.” In 2016 IEEE Conference on Control Applications
(CCA), Part of 2016 IEEE Multi-Conference on Systems and Control, pages 129–136,
Buenos Aires, Argentina, Sept. 19-22, 2016.