CNI CONNECT

Monthly Newsletter from CNI

Issue - April 2026

Upcoming Talks

April carries forward the momentum at CNI, with a new set of seminars and a workshop bringing together ideas across theory, systems, AI, and emerging networked technologies. The lineup this month continues to reflect the range of questions and perspectives shaping ongoing research in the field.

Here’s what’s ahead:

15 April – Dr. Mansi Sood, MIT

20 April – Prof. Frank den Hollander, Leiden University, Netherlands

20 April – Prof. Remco van der Hofstad, Eindhoven University of Technology, Netherlands

21 April – Prof. Sarath Yasodharan, IIT Bombay

22 April – Prof. Arpan Mukhopadhyay, University of Warwick

27 April – Prof. Gautam Menon, Ashoka University

04 May – Prof. Ganesh Ayalvadi, University of Bristol

Talk titles, abstracts, and full details are available on the CNI Seminar Series page. Do take a look and mark your calendars.

CNI Technical Workshop on  Future Communications and Networking

CNI will be organising the UK–India Workshop on Future Communications and Networking, bringing together researchers from both countries to explore emerging directions in communication systems and networked technologies.

The workshop aims to foster collaboration and exchange of ideas across academia and industry, with discussions spanning next-generation wireless systems, AI-driven networking, and distributed systems.

Further details are available on the CNI workshop page.

Sixth Edition of CNI Summer School in July 2026!

This year, we're fortunate to have Prof. Aditya Mahajan (McGill University), known for his research and teaching on Stochastic Control and Decision Theory, as the faculty for CNI Summer School.

The programme will centre on model approximation techniques in Partially Observable Markov Decision Processes (POMDPs), covering core ideas in stochastic systems and optimization, along with their connections to reinforcement learning.

Further details, including the schedule and application process, are available on the Summer School Webpage.

Research Spotlight

This month we have two papers by Prof. Parimal Parag accepted at the IEEE International Symposium on Information Theory (ISIT) 2026, Guangzhou, China:

• Random Walk Learning and the Pac-Man Attack by X. Chen, P. Parag, R. Bhagat, Z. Liu, and S. El Rouayheb.

• Perfect Privacy and Strong Stationary Times for Markovian Sources by F. Ye, Z. Liu, P. Parag, and S. El Rouayheb.

Join the CNI Team!

As our research expands, so does our team.

CNI is inviting applications for the following openings in the Distributed Systems Lab:

1. Research Associate:  For experienced professionals and fresh graduates planning to get into systems research.

2. Research Intern: For students who are interested in experimental research in systems/networks while pursuing their studies.

More details at the CNI opportunities page.

Highlights from Recent Talks

Near-Ground Precipitation Sensing for Next-generation Wireless Networks

Prof. Ashutosh Sabharwal (Rice University) explored how large-scale wireless networks can double as sensing systems. He presented methods to use base stations for near-ground precipitation monitoring, offering a complementary approach to traditional radar, and highlighted broader opportunities for integrating sensing into future wireless infrastructure.

Leveraging Analog Codes for Privacy and Robustness in Federated Learning

Prof. Harshan Jagadeesh (IIT Delhi) examined how federated learning systems can remain both private and resilient in untrusted settings. He discussed recent advances in secure aggregation, highlighting the FORTA framework, which combines coding techniques and outlier detection to guard against malicious participants while preserving data privacy.

Creating Datasets for Environmental Sustainability Problem in Developing Countries

Prof. Rijurekha Sen (IIT Delhi) addressed the challenges of building reliable environmental datasets in resource-constrained settings. Drawing from work on air pollution and traffic monitoring in Delhi, she highlighted how low-cost sensing and edge computing can help bridge critical data gaps for sustainability research.

Signal Processing Challenges in mmWave Radar

Sandeep Rao (Texas Instruments) offered an engaging look at how mmWave radar systems are evolving beyond automotive applications. Introducing core principles such as FMCW radar, he highlighted emerging research challenges and opportunities at the intersection of signal processing and machine learning in next-generation sensing systems.