Networking and Distributed Systems at HPE Labs
Abstract: Artificial Intelligence has quickly become a powerful tool for addressing complex systems problems, and networking has been no exception. Yet, the journey from promising idea to practical impact often reveals unexpected challenges and deeper insights. This reflects lessons learned from applying AI to networking problems, drawing on experiences from our Maestro and Wixor projects. These efforts tackled issues such as Wi-Fi QoE orchestration and cellular (5G) resource scheduling, showing both the promise and the limits of AI in networked systems. Several themes emerged across these projects: the critical role of formulating the right learning problem, the tradeoffs between model complexity and system usability, and the value of embedding domain knowledge into AI-driven solutions. Along the way, we also discovered that applying AI to networking is not just about better algorithms—it can reshape how we think about networks themselves. This talk will take a step back to distill these experiences into broader reflections: when does AI truly help in networking, what pitfalls should we anticipate, and how can we design systems that are both intelligent and trustworthy?
Date and Time
Location
Hosts
Registration
-
Add Event to Calendar
- Rice University
- 6100 Main Street
- Houston, Texas
- United States 77005
- Building: O'Connor Building for Engineering and Science
- Room Number: 406
- Contact Event Hosts
-
Prof. Joseph Cavallaro, cavallar@rice.edu
- Co-sponsored by Rice University ECE and IEEE Student Branch
Speakers
Puneet Sharma of HPE Labs
Networking and Distributed Systems at HPE Labs
Abstract: Artificial Intelligence has quickly become a powerful tool for addressing complex systems problems, and networking has been no exception. Yet, the journey from promising idea to practical impact often reveals unexpected challenges and deeper insights. This reflects lessons learned from applying AI to networking problems, drawing on experiences from our Maestro and Wixor projects. These efforts tackled issues such as Wi-Fi QoE orchestration and cellular (5G) resource scheduling, showing both the promise and the limits of AI in networked systems. Several themes emerged across these projects: the critical role of formulating the right learning problem, the tradeoffs between model complexity and system usability, and the value of embedding domain knowledge into AI-driven solutions. Along the way, we also discovered that applying AI to networking is not just about better algorithms—it can reshape how we think about networks themselves. This talk will take a step back to distill these experiences into broader reflections: when does AI truly help in networking, what pitfalls should we anticipate, and how can we design systems that are both intelligent and trustworthy?
Biography:
Bio: Dr. Puneet Sharma is an HPE Fellow, Vice President, and Director of the Networking and Distributed Systems Lab at HPE Labs, leading research in Edge-to-Cloud-to-Exascale Infrastructure, Multi-Cloud Resource Orchestration, AI for Infrastructure, 5G/WiFi, and Security. Since joining HP Labs in 1998 after earning his Ph.D. from the University of Southern California, he has driven innovations in software-defined networking (SDN), GPU virtualization, container orchestration, edge computing, Private 5G, and AI/ML systems, enabling major technology transfers across HPE business units. A recognised global thought leader, Puneet has authored 150+ papers, holds 100+ patents, co-authored IETF RFCs, and delivered keynote talks at IEEE and industry events. He is an IEEE Fellow, ACM Distinguished Scientist, and two-time Tsinghua AI 2000 Most Influential Scholar. He earned his B.Tech from IIT Delhi. His leadership continues to advance AI-powered, distributed computing and networking infrastructure worldwide.
Email:
Address:HPE Labs, , Palo Alto, California, United States
Agenda
Presentation at 12:00 to 1:00 pm CDT at O'Connor Building for Engineering and Science, Room 406 at Rice University