Hi! I'm Deepak Nadig
I am an Assistant Professor in the Department of Computer and Information Technology at Purdue University, West Lafayette, IN. My research focus is primarily on the interplay between Software Defined Networks and Network Functions Virtualization for developing secure and intelligent next-generation networks. My research interests are in Computer Networks, Software Defined Networks, Network Functions Virtualization, Cloud-native Infrastructure, Network Security and AI/ML applications to networking.
My research philosophy is grounded in the fact that application-centric networks resulting from seamless collaboration between application-layer and network-layer have a marked impact on network management, security, policy frameworks, network services and big data analytics. Importantly, I focus on cross-layer approaches to optimize and secure networks rather than layer-3 approaches that are unaware of the applications’ service and resource requirements. Thus, my research seeks to uncover application-aware networking and its impact on security, service differentiation and efficient data transfers in distributed data-intensive applications.
Latest News
Dr. Nadig invited to serve as the Tutorials Chair for the 2023 IEEE ANTS Conference in Jaipur, India.
Dr. Nadig invited to serve as the Technical Program Committee Co-Chair for the 2024 IEEE INFOCOM CNERT Workshop in Vancouver, Canada.
Cloud-native Infrastructure and Networks
Developing application-awareness in cloud-native infrastructure, distributed clouds, cloud networks and softwarized networks.
Virtualized and Software-Defined Network Management
Software-defined and programmable network architectures for network management, traffic classification, monitoring and security.
Applied AI/ML for Clouds and Softwarized Networks
Applied AI, machine learning and data analytics for Cloud-native and SDN-based network architectures, management and security.
My research interests are in
Our Recent Projects
Scalable Edge Computing
ERGO is an edge-computing architecture that is highly scalable, modular, and affords composability benefits to infrastructure-less Ag-IoT systems. Our implementation and evaluations show that…
Application-Aware Load Balancing
APRIL is an application-aware, predictive and intelligent load balancing solution for data-intensive science.
Let’s work and build something great together.
Recent distinctions
and awards.
2019 IEEE INFOCOM
Best-in-session Award
2017 IEEE ANTS Best Paper Award