Graphs naturally represent data created in a host of real world processes, including interactions between people on social or communication networks, relations between entities in a knowledge graph, links between content with its creators and consumers in content platforms, and many others. These graphs are typically multi-modal, multi-relational and dynamic.

The objective of this meetup is to learn about some of the most cutting-edge research in mining networks. As an outcome, we expect participants to walk away with a better sense of the variety of different methods and tools available for network mining and analysis, and an appreciation for some of the interesting emerging applications.

There are many challenges involved in effectively mining and learning from this kind of data, including:

• Understanding the different techniques applicable, including graph mining algorithms, network embedding, graph convolutional networks etc.
• Dealing with the heterogeneity of the data.
• Need for information integration and alignment.
• Handling dynamic and changing data at scale

Attend ML Hikeathon and online webinar:

• ML Hikeathon: https://datahack.analyticsvidhya.com/contest/hikeathon/
• Online Webinar:https://datahack.analyticsvidhya.com/contest/webinar-building-products-in-the-ai-era/

Agenda

10:00 am:Registrations begin at Hike HQ

10:30 am - 11:15 am: "Community Analysis in Complex Networks:Unfolding Structure and Semantics", Prof.Tanmoy Chakraborty, IIIT Delhi

11:15 am - 12:00 pm:"Learning Combinatorial Algorithms over Graphs at Scale", Prof. Sayan Ranu, IIT Delhi

12:00 pm - 12:15 pm:Coffee Break

12:15 pm - 01:00 pm:"Network Embeddings for Link Prediction", Janu Verma, Senior Data Scientist, Hike Messenger

01:00 pm - 01:45 pm:"Learning multigraph node embeddings using guided levy flights", Vinayak Kumar, PhD Student, IIIT Delhi.

01:45 pm:Hikeathon Kick-off

02:00 pm:Lunch

Event Location

Hike Messenger

4th Floor, Worldmark 1, Northern Access Road, Aerocity, Indira Gandhi International Airport,

New Delhi, Delhi 110037

Google Map

Timing

10 am – 2 pm

Speakers:

Prof Sayan Ranu

IIT Delhi

Sayan Ranu is an assistant professor in the department of Computer Science and Engineering at IIT Delhi. His research interests include spatio-temporal data analytics, graph indexing, and mining, and bioinformatics. Prior to joining IIT Delhi, he spent close to three years as an Assistant Professor at IIT Madras and a year and a half in the role of a Research Scientist at IBM Research. He obtained his PhD from the Department of Computer Science, University of California, Santa Barbara (UCSB) in March 2012. He was a recipient of the “Distinguished Graduate Research Fellowship” at UCSB. He obtained his Bachelor of Science from Iowa State

University, where he received the “President’s top 2% of the class” award. He has published more than 35 papers in premier database, data-mining and bioinformatics venues including SIGMOD, VLDB, KDD, and WWW. He received the Best Paper Award at the International Conference on Web Information Systems Engineering (WISE) 2016, Best-of-IEEE-ICDM-2016 selection, and Most Reproducible Paper Award at SIGMOD 2018. Sayan regularly serves in the program committees and review panels of prestigious conferences and journals including KDD, ICDE, ICDM, WWW, CIKM, TKDE, and VLDB Journal. Sayan has been granted 4 US patents. Sayan’s dissertation on graph based techniques for querying and mining molecular databases served as the seed idea behind a life science based R&D start-up focusing on advanced technology for drug discovery. Sayan maintains his social footprint in his LinkedIn profile as well as his IIT D homepage.

Prof. Tanmoy Chakraborty

IIT Delhi

I am currently an Assistant Professor and a Ramanujan Fellow at Indraprastha Institute of Information Technology Delhi (IIIT-D), India since May 17, 2017. Before joining IIIT-D, I was a Postdoctoral Researcher at University of Maryland, College Park. I completed my PhD as a Google India PhD scholar from Dept. of Computer Science & Engineering, Indian Institute of Technology (IIT), Kharagpur, India in September, 2015.

My broad research interests include Data Mining, Complex Networks, Social Computing, Natural Language Processing, Data-driven Cybersecurity.

Janu Verma

Senior ML Scientist, Hike

Janu Verma is a Senior Data Scientist at Hike, New Delhi. He work is focussed on recommendation and personalization. Previously, he was a researcher at IBM TJ Watson Research Center in New York and at Cornell University. His background is in pure mathematics and physics. He is also a coffee entrepreneur and training to be an endurance athlete.