The Fifth Elephant is India’s most renowned data science conference. It is a space for discussing some of the most cutting edge developments in the fields of machine learning, data science and technology that powers data collection and analysis.
Machine Learning, Distributed and Parallel Computing, and High-performance Computing continue to be the themes for this year’s edition of Fifth Elephant.
We are now accepting submissions for our next edition which will take place in Bangalore 28-29 July 2016.
We are looking for application level and tool-centric talks and tutorials on the following topics:
- Deep Learning
- Text Mining
- Computer Vision
- Social Network Analysis
- Large-scale Machine Learning (ML)
- Internet of Things (IoT)
- Computational Biology
- ML in healthcare
- ML in education
- ML in energy and ecology
- ML in agriculrure
- Analytics for emerging markets
- ML in e-governance
- ML in smart cities
- ML in defense
The deadline for submitting proposals is 30th April 2016
This year’s edition spans two days of hands-on workshops and conference. We are inviting proposals for:
- Full-length 40 minute talks.
- Crisp 15-minute talks.
- Sponsored sessions, 15 minute duration (limited slots available; subject to editorial scrutiny and approval).
- Hands-on Workshop sessions, 3 and 6 hour duration.
Proposals will be filtered and shortlisted by an Editorial Panel. We urge you to add links to videos / slide decks when submitting proposals. This will help us understand your past speaking experience. Blurbs or blog posts covering the relevance of a particular problem statement and how it is tackled will help the Editorial Panel better judge your proposals.
We expect you to submit an outline of your proposed talk – either in the form of a mind map or a text document or draft slides within two weeks of submitting your proposal.
We will notify you about the status of your proposal within three weeks of submission.
Selected speakers must participate in one-two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.
There is only one speaker per session. Entry is free for selected speakers. As our budget is limited, we will prefer speakers from locations closer home, but will do our best to cover for anyone exceptional. HasGeek will provide a grant to cover part of your travel and accommodation in Bangalore. Grants are limited and made available to speakers delivering full sessions (40 minutes or longer).
HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like it to be available under a permissive open source licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), please consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.
- Revised paper submission deadline: 17 June 2016
- Confirmed talks announcement (in batches): 13 June 2016
- Schedule announcement: 30 June 2016
- Conference dates: 28-29 July 2016
The Fifth Elephant will be held at the NIMHANS Convention Centre, Dairy Circle, Bangalore.
For more information about speaking proposals, tickets and sponsorships, contact email@example.com or call +91-7676332020.
What do machine learning and high performance computing have to do with big cats in the wild?
Science has played a crucial role in our understanding of big cats in the wild and in their conservation. When we focus on the aspect of “gaining knowledge” or “learning”, few other approaches have done better than rigorous application of scientific methods. As we all know too well, the scientific method involves careful observation, construction of relevant theories and confronting these theories with data.
In the context of understanding the world of big cats in the wild, the scientific method demands investigators to pose well-defined questions, spend vast amounts of time in the field carefully gathering field data and then spending time behind computers analyzing them before drawing conclusions. Hence there is a vast amount of human learning in the process. So how do tools such as machine learning, parallel and high performance computing contribute to such a seemingly earthy field of wildlife ecology and conservation?
In this talk, focusing on some of my recent ecological research work on tigers, lions and cheetahs, and quantitative methods, I will describe what it takes to make computing approaches (ML, PC and HPC) highly relevant to the field of ecology. I argue, with a potpourri of demonstrable examples, that such computational “tools” are extremely useful only when considered within a broader scientific study and a failure to do so may lead us into spurious conclusions that may prove costly!
Dr. Arjun M. Gopalaswamy is a Visiting Scientist at the Indian Statistical Institute, Bangalore Centre and Research Associate at the Department of Zoology, University of Oxford, UK. He is an accomplished ecological researcher focusing on large cats and has vast experience in ecological field research as well as with data analysis and computation methods. He has published over 20 scientific papers in international peer-reviewed journals. He completed his Master’s in Wildlife Ecology and Conservation from University of Florida, Gainesville and his PhD in Zoology from University of Oxford, UK.