IIIT Delhi partners with Marvell to offer AI networking systems course

IIIT Delhi has partnered with the Indian affiliate of Marvell Technology Inc. to roll out an advanced academic industry program titled Networks for AI/ML Systems, aimed at training students in the systems foundations that power large-scale artificial intelligence.

According to an official statement, the program focuses on the systems layer of modern AI, where networking fabrics, memory architectures, and distributed execution play a decisive role in performance at scale.

The course has been designed to reflect real-world production AI infrastructure rather than purely theoretical models.

The program was jointly developed by IIIT Delhi and Marvell and is co-taught by Dr Rinku Shah from IIIT Delhi and Abed Mohammad Kamaluddin, a director at Marvell.

Engineers and system architects from Marvell are providing ongoing technical mentoring to students enrolled in the course.

Alongside the academic offering, IIIT Delhi and Marvell are also collaborating on research related to AI networking and systems, with the coursework aligned to support and advance these shared research priorities.

“Networks for AI/ML Systems is India’s first and the first known course of its kind globally. By integrating AI networking, CXL-based memory systems, and AI-scale simulation, the course exposes students to system-level challenges rarely addressed in traditional curricula,” said Prof Pushpendra Singh, head of the Department of Computer Science and Engineering at IIIT Delhi.

The inaugural edition of the course saw participation from nearly 45 students across BTech, MTech, and PhD programs. The teaching approach emphasized project-driven and peer-based learning.

A survey conducted after the course indicated a noticeable rise in student confidence when reasoning about AI systems, networking fabrics, and distributed machine learning workflows.

Student projects covered areas such as AI fabrics and transport layers, CXL-aware training and inference, distributed training and serving pipelines, in-network computing, telemetry-based optimization, and machine learning-driven security and observability.

Many students cited the open-ended and systems-intensive nature of the projects as central to their learning experience, helping them explain complex system behavior rather than simply deploying existing tools.

During a visit to the IIIT Delhi campus, Prasun Kapoor, AVP at the Indian affiliate of Marvell, reviewed student projects and interacted with participants.

He said, “The course exposes students to the cutting-edge ML network fabric technologies as they evolve in the industry, reflected in their systems thinking around scale, data movement, and real infrastructure constraints.”

The initiative highlights the impact of sustained industry-academia collaboration in emerging technology domains. It is expected to help build one of India’s early talent pipelines trained specifically in AI and ML systems and fabrics, while aligning with national priorities related to AI compute and semiconductor capabilities.

IIIT Delhi and Marvell said they plan to expand the partnership through joint research projects, advanced courses, and continued mentoring, with the aim of strengthening India’s position in next-generation AI systems and networking technologies.