(Canceled) ACM MobiHoc Workshop on Distributed Information Processing in Wireless Networks (DIPON’2018)

Workshop Program Highlights


Quickest detection of dynamically evolving events in networks

Biography: Venugopal V. Veeravalli received the B.Tech. degree (Silver Medal Honors) from the Indian Institute of Technology, Bombay, India, in 1985, the M.S. degree from Carnegie Mellon University, Pittsburgh, PA, USA, in 1987, and the Ph.D. degree from the University of Illinois at Urbana-Champaign, Champaign, IL, USA, in 1992, all in electrical engineering. He joined the University of Illinois at Urbana-Champaign in 2000, where he is currently the Henry Magnuski Professor in the Department of Electrical and Computer Engineering, and where he is also affiliated with the Department of Statistics, the Coordinated Science Laboratory, and the Information Trust Institute. From 2003 to 2005, he was a Program Director for communications research at the U.S. National Science Foundation in Arlington, VA, USA. He has previously held academic positions at Harvard University, Rice University, and Cornell University, and has been on sabbatical at MIT, IISc Bangalore, and Qualcomm, Inc. His research interests include statistical signal processing, machine learning, detection and estimation theory, information theory, and stochastic control, with applications to sensor networks, cyberphysical systems, and wireless communications. A recent emphasis of his research has been on signal processing and machine learning for data science applications. Prof. Veeravalli was a Distinguished Lecturer for the IEEE Signal Processing Society during 2010 and 2011. He has been on the Board of Governors of the IEEE Information Theory Society. He has been an Associate Editor for Detection and Estimation for the IEEE Transactions on Information Theory and for the IEEE Transactions on Wireless Communications. The awards he received for research and teaching are the IEEE Browder J. Thompson Best Paper Award, the National Science Foundation CAREER Award, and the Presidential Early Career Award for Scientists and Engineers, and the Wald Prize in Sequential Analysis.

  Important Dates
April 1, 2018 Submission deadline
April 6, 2018 Extended submission deadline
May 2, 2018 Acceptance notification
May 10, 2018 Camera ready deadline


Workshop Co-Chairs

  • Ketan Rajawat, IIT Kanpur, India
  • Pramod Kumar Varshney, Syracuse University, USA

Technical Program Committee

  • Abhishek Sinha, Qualcomm Inc.
  • Alec Koppel, Army Research Labs
  • Hao Chen, Boise State University
  • Bhavya Kailkhura, Lawrence Livermore National Laboratory
  • Sijia Liu, IBM Research

Call For Papers

The unprecedented advances in sensing, communication, and storage technologies have motivated the development of a plethora of optimization and learning algorithms capable of distributed operation over networks. Some of the popular application areas where such algorithms have been widely applied include distributed signal processing in wireless sensor networks, distributed resource allocation in cellular and ad hoc networks, distributed machine learning algorithms for Big Data, and distributed localization and tracking.

Desired attributes of such decentralized information processing algorithms include parallelizability, scalability, robustness to channel impairments and network delays, low-cost operation, and the ability to handle uncertain and dynamic network topologies. Embedding such features into classical information processing techniques is challenging, and has sparked the development of a gamut of distributed algorithms.

The aim of the workshop is to provide an international forum for discussions of recent developments in distributed learning, optimization, signal processing, and resource management. The focus will be on the design and analysis of algorithms capable of handling the vagaries of wireless networks, such as delays, limited and heterogeneous abilities, channel impairments, and communication restrictions arising due to the network topology.

Topics of interest include (but are not limited to):

  • Machine learning over networks
  • Signal processing over networks
  • Statistical signal processing on networks
  • Distributed optimization for signal processing
  • Distributed optimization for communication systems
  • Distributed optimization for cyber physical systems
  • Distributed control over networked systems
  • Distributed resource management over networks
  • Non-convex optimization methods over networks
  • Robust and stochastic optimization methods over networks
  • Privacy preservation in distributed algorithms
  • Asynchronous coordination schemes

Submission Instructions

We solicit regular papers that present novel and unpublished research results. Workshop papers should not exceed 6 pages in standard double column ACM conference format, including figures, tables, references, and appendix. As per ACM policy, papers submitted to other conferences or journals will not be considered for publication. Accepted papers will appear in the conference proceedings published by the ACM.

For paper submission to ACM MobiHoc 2018 Workshop on Distributed Information Processing in Wireless Networks, please visit

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