Workshop on Machine Intelligence in Networked Data and Systems (MINDS)

Workshop Date: Monday, 7th January 2019

The inter-working of machine learning and networking is set to transform and disrupt many areas of business and everyday human life. MINDS (Machine Intelligence in Networked Data and Systems) aims to bring together researchers and practitioners to understand and explain this inter-working. MINDS will discuss and present latest achievements and innovations at the cross-section of machine learning, systems, and networking.

MINDS welcomes original research submissions that define challenges, report experiences, or discuss progress toward design and solutions that integrate machine learning, deep learning, mobile systems, and networked systems in various application areas. These application areas include but are not limited to healthcare, environment, retail, transportation, life sciences etc. Contributions describing techniques applied to real-world problems and interdisciplinary research involving novel networking architectures, system designs, IoT systems, big data systems with machine learning as the core component are especially encouraged.

The topics of interest include but are not limited to

  • Design and implementation of intelligent systems for applications such as home automation, self-driving vehicles, driver assistance systems
  • Cloud based machine and deep learning applications in retail and e-commerce
  • Machine learning systems for healthcare, weather modelling, life sciences, and environment monitoring
  • Machine learning driven analysis of text, image, and video data on social media
  • Intelligent networked systems for city-scale transportation and logistics
  • Machine learning driven systems using mobile phones, embedded devices, and sensor networks
  • Applications of machine learning in IoT, IIoT, manufacturing, and supply chain optimisation
  • System designs for data-driven intelligent networks
  • Root cause analysis and failure prediction using system and network logs
  • Applications of machine/deep/reinforcement learning in satellite networks, cellular networks and WiFi networks
  • Machine learning driven algorithms and tools for network anomaly detection and network security
  • Machine learning and data mining of large-scale network measurements
  • Stream-based machine learning for networked data
  • Machine learning driven algorithms for network scheduling and control

Papers can be submitted through EDAS : Click Here

Accepted and presented papers will be published in the conference proceedings and submitted to IEEE Xplore as well as other Abstracting and Indexing (A&I) databases.


Important Deadlines


Paper Submission 19th October 2018
Notification of Acceptance 30th November 2018
Camera-ready Submission 14th December 2018
Workshop Date 7th January 2019

Invited Speakers



Avi Patchava

Avi Patchava

InMobi, India

Sundara Ramalingam Nagalingam

Sundara Ramalingam Nagalingam

NVIDIA Graphics Pvt Ltd, India

Babu O Narayanan

Babu O Narayanan

SymphonyAI, India

Salil Kanhere

Salil Kanhere

UNSW Sydney, Australia


TPC Members


  1. Amar Prakash Azad, IBM Research, India
  2. Partha Dutta, Swiss Re, India
  3. Aditya Joshi, CSIRO, Australia
  4. Kirill Kogan, IMDEA, Spain
  5. Ravi Kokku, IBM Research, USA
  6. Abhishek Kumar, Cisco, Canada
  7. Mukundan Madhavan, Goldman Sachs, India
  8. Abderrahmen Mtibaa, New Mexico State University, USA
  9. Santosh Patil, CISCO, USA
  10. Nishanth Sastry, King's College, UK
  11. Uma Sawant, LinkedIn, India
  12. Mudhakar Srivatsa, IBM Research, USA


Workshop Co-Chairs


Vijay Gabale

Vijay Gabale

Huew, India

Vinay Kolar

Vinay Kolar

NVIDIA, USA