The Fifth Elephant 2016

India's most renowned data science conference

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:

  1. Deep Learning
  2. Text Mining
  3. Computer Vision
  4. Social Network Analysis
  5. Large-scale Machine Learning (ML)
  6. Internet of Things (IoT)
  7. Computational Biology
  8. ML in healthcare
  9. ML in education
  10. ML in energy and ecology
  11. ML in agriculrure
  12. Analytics for emerging markets
  13. ML in e-governance
  14. ML in smart cities
  15. 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.

Selection process

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).

Commitment to open source

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.

Key dates and deadlines

  • 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 or call +91-7676332020.

Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

Udit Poddar


Data-Driven Decision Making in Indian Agriculture: the Present and the Future

Submitted Apr 30, 2016

Data-driven decision making is critical in sectors like agriculture, health, and education where well-planned initiatives have the power to literally change lives. Lack of a consolidated platform with access to relevant data, however, hinders objectivity and efficiency in the decision making process for the decisions that matter most. In this session, we reveal how we integrated relevant data — previously divided into silos — to undertake targeted investment decisions in agriculture. We then explore what decision science means for the future of agriculture in India.


  1. Introduction to data-driven decision making in agriculture.
    a. Overview of current decision-making process in agriculture sector.
    b. Discussion of the types of decisions that can be driven by data in the agriculture sector.
  2. The current state of agriculture data in India.
    a. Overview of data that is openly available in agriculture sector.
    b. Importance of specific data sets for information about agriculture in India.
    c. Insights from Government MIS systems
  3. Challenges and solutions in consolidating data.
    a. Overview of challenges faced in consolidating independent data sets into a master data set that can be used for generating insights.
    b. Explanation of the solutions developed by us to stitch different datasets together.
    c. Data curation problems with the current agricultural data in India
  4. Regularity of data and data gaps in the agricultural sector.
    a. Overview of current data gaps in agricultural sector in India.
    b. Explanation of difference between input and output metrics in the context of agriculture.
    c. Argument for importance of tracking output metrics at the lowest administrative division.
  5. Introduction to precision farming
    a. Overview of the concept of precision farming.
    b. Explanation of how can sensor-based precision farming revolutionize the agriculture sector in India.
    c. Challenges to implementation of precision farming in the Indian context.
  6. Machine learning in agriculture
    a. How can machine learning help in farmer preparedness on various issues? Predicting crop productivity, disease outbreaks, pest infestations etc. using machine learning algorithms.

Speaker bio

Udit is a Data Scientist at SocialCops, a data intelligence company in New Delhi. He has considerable experience in decision science and works on analyses to solve critical problems in agriculture, health, and retail. Previous projects include targeting agriculture investments to the people and places with the greatest impact, analyzing the socio-economic potential of international markets, and analyzing granular data on online retailers’ customer base. His mission is to create data-centered solutions to problems faced by agricultural India. Previous speaking experience includes debating and conducting sessions on the R programming language.



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Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more