The Fifth Elephant 2016

India's most renowned data science conference

DATE

28-29 July 2016, Bangalore

STATUS

Open for feedback


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.

Tracks

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

Format

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

Venue

The Fifth Elephant will be held at the NIMHANS Convention Centre, Dairy Circle, Bangalore.

Contact

For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.


Confirmed sessions

Using Data to Identify the Genomic Cause of Disease

Ramesh Hariharan

  • Full talk
  • Intermediate
  • 2 upvotes
  • 0 comments
  • Thu, 21 Jul

Reasoning: The Next Frontier in Data Science

Shailesh Kumar (@shkumar)

  • Full talk
  • Intermediate
  • 4 upvotes
  • 1 comments
  • Thu, 21 Jul
  • slideshow

Scaling the Largest Functional DataSet @Flipkart aka Catalog

Anuj Mittal (@anujmittal)

  • Full talk
  • Intermediate
  • 5 upvotes
  • 0 comments
  • Tue, 19 Jul

Allocation and Forecasting in Guaranteed Delivery of Advertisements

Aditya Ramana Rachakonda (@arrac)

  • Full talk
  • Intermediate
  • 1 upvotes
  • 0 comments
  • Tue, 19 Jul
  • slideshow

Real Time Fulfilment Planning at Flipkart Scale

Jagadeesh Huliyar (@jagadeesh-huliyar)

  • Full talk
  • Intermediate
  • 1 upvotes
  • 0 comments
  • Tue, 19 Jul

Hierarchical Bayes Approach and Implementation of MCMC in an Ecological Study

Soumen Dey (@soumendey)

  • Full talk
  • Advanced
  • 2 upvotes
  • 0 comments
  • Mon, 18 Jul
  • slideshow

Deciphering Driving Behaviour using Geospatial Temporal Data Collected from Smartphone Sensors

Aditya Karnik (@adityakarnik)

  • Full talk
  • Intermediate
  • 1 upvotes
  • 0 comments
  • Mon, 18 Jul

Hadoop & Cloud Storage: Object Store Integration in Production

Rajesh Balamohan

  • Crisp talk
  • Intermediate
  • 1 upvotes
  • 0 comments
  • Fri, 15 Jul
  • slideshow

Meet the needs of content marketing with the power of NLP

Balaji Vasan (@balajivasan)

  • Full talk
  • Intermediate
  • 1 upvotes
  • 0 comments
  • Wed, 13 Jul

Lessons Learned : Real-life NLP

Martin Andrews (@mdda)

  • Crisp talk
  • Intermediate
  • 3 upvotes
  • 0 comments
  • Tue, 12 Jul
  • slideshow

Machine Learning the Walmart Way with a Deep Dive into Automated Forecasting System

Anindya Sankar Dey (@asd1)

  • Crisp talk
  • Intermediate
  • 14 upvotes
  • 0 comments
  • Mon, 11 Jul

Taking Analytics Applications from Labs to the Real World: Transfer Learning in Practice

Shourya Roy (@shourya)

  • Full talk
  • Intermediate
  • 3 upvotes
  • 0 comments
  • Mon, 11 Jul
  • slideshow

The Alternative Data revolution on Wall St

Gene Ekster (@geneman)

  • Full talk
  • Intermediate
  • 1 upvotes
  • 0 comments
  • Mon, 11 Jul
  • slideshow

Convolutional Neural Networks from the Other Side

Sumod Mohan (@sumod)

  • Full talk
  • Advanced
  • 3 upvotes
  • 0 comments
  • Sat, 9 Jul

Advanced Deep Learning Workshop – Hands-on

Martin Andrews (@mdda)

  • Workshop
  • Advanced
  • 6 upvotes
  • 0 comments
  • Wed, 6 Jul
  • slideshow

Scalable Realtime Analytics using Druid

Nishant Bangarwa (@nishantbangarwa)

  • Full talk
  • Intermediate
  • 3 upvotes
  • 2 comments
  • Wed, 6 Jul
  • slideshow

Deep Learning for Computer Vision

Anand Chandrasekaran (@anandchandrasekaran)

  • Workshop
  • Intermediate
  • 7 upvotes
  • 0 comments
  • Thu, 23 Jun

Looking under the hood - demystifying data tools

Simrat Hanspal (@simrathanspal)

  • Crisp talk
  • Intermediate
  • 19 upvotes
  • 2 comments
  • Fri, 17 Jun
  • slideshow

RightFit- A Data Science Approach to Reduce Product Returns in Fashion e-Commerce

Ashish Kulkarni (@kulashish)

  • Crisp talk
  • Intermediate
  • 12 upvotes
  • 2 comments
  • Wed, 15 Jun
  • slideshow

Building a scalable Data Science Platform ( Luigi, Apache Spark, Pandas, Flask)

Nischal HP (@nischalhp)

  • Workshop
  • Intermediate
  • 10 upvotes
  • 0 comments
  • Tue, 14 Jun

Introduction to Statistics and Basics of Mathematics for Data Science - the hacker's way

Bargava Subramanian (@barsubra)

  • Workshop
  • Beginner
  • 15 upvotes
  • 2 comments
  • Tue, 7 Jun

Continuous online learning for classification tasks

Saurabh Arora (@tanish2k)

  • Full talk
  • Intermediate
  • 7 upvotes
  • 0 comments
  • Tue, 7 Jun

ML in fin-tech - Transforming 60 crore Indian lives

Riddhi Mittal (@riddhimittal)

  • Full talk
  • Beginner
  • 19 upvotes
  • 0 comments
  • Sat, 30 Apr
  • play_arrow
  • slideshow

Reducing the world with JavaScript

Aruna S (@arunasank)

  • Full talk
  • Intermediate
  • 5 upvotes
  • 1 comments
  • Sat, 30 Apr
  • play_arrow

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

Udit Poddar (@poddarudit)

  • Crisp talk
  • Intermediate
  • 41 upvotes
  • 0 comments
  • Sat, 30 Apr
  • slideshow

Logging at scale using Graylog - Billion+ messages, 100K req/sec

Rohit Gupta (@rohit01)

  • Crisp talk
  • Intermediate
  • 9 upvotes
  • 2 comments
  • Fri, 29 Apr

Purpose, Speed & Visibility : Facilitating product discovery & engagement on a e-commerce website

Ekta Grover (@ekta1007)

  • Full talk
  • Intermediate
  • 1 upvotes
  • 0 comments
  • Fri, 29 Apr
  • slideshow

Dr. Elephant - Self-Serve Performance Tuning for Hadoop and Spark

Akshay Rai (@akshayrai)

  • Crisp talk
  • Intermediate
  • 21 upvotes
  • 1 comments
  • Mon, 25 Apr

Taking Fashion and Lifestyle Commerce Towards SKUs Using Deep Image and Text Parsing

Vijay Gabale (@vijaygabale)

  • Full talk
  • Intermediate
  • 7 upvotes
  • 0 comments
  • Mon, 25 Apr
  • play_arrow
  • slideshow

What do machine learning and high performance computing have to do with big cats in the wild?

Arjun Mallipatna Gopalaswamy (@arjun-4bigcats)

  • Full talk
  • Intermediate
  • 3 upvotes
  • 0 comments
  • Fri, 15 Apr
  • slideshow

Model Visualisation

Amit Kapoor (@amitkaps)

  • Full talk
  • Beginner
  • 10 upvotes
  • 0 comments
  • Wed, 13 Apr
  • slideshow

Increasing Trust and Efficiency of Data Science using dataset versioning

Venkata Pingali (@venkatapingali)

  • Crisp talk
  • Intermediate
  • 12 upvotes
  • 5 comments
  • Sun, 27 Mar
  • slideshow

Timely Dataflow

Bharani (@bharanisub)

  • Crisp talk
  • Advanced
  • 28 upvotes
  • 0 comments
  • Tue, 22 Mar
  • slideshow

Let your Big Data Processing take flight with Apache Falcon

Pallavi Rao (@pallavi-rao)

  • Crisp talk
  • Beginner
  • 20 upvotes
  • 0 comments
  • Thu, 25 Feb
  • play_arrow
  • slideshow

Unconfirmed proposals

Bootstrapping inspired by Hacking Human Cognition

Akbar Ladak (@bluplaneter)

  • Crisp talk
  • Intermediate
  • 3 upvotes
  • 0 comments
  • Fri, 17 Jun
  • play_arrow

Building a Large scale Augmented classifier ensemble to predict in noisy data

Arthi Venkataraman (@arthi)

  • Full talk
  • Advanced
  • 5 upvotes
  • 0 comments
  • Wed, 15 Jun
  • slideshow

How Intuit solved big scan problem in real time

Ashish Jain (@toashishj)

  • Crisp talk
  • Beginner
  • 13 upvotes
  • 1 comments
  • Tue, 14 Jun

Intuit’s Data journey to Public cloud

Abhishek Jain (@abhi111jain)

  • Crisp talk
  • Intermediate
  • 25 upvotes
  • 0 comments
  • Tue, 14 Jun

Distributed change data capture platform

Chandraprakash Bhagtani (@cpbhagtani)

  • Full talk
  • Intermediate
  • 19 upvotes
  • 1 comments
  • Tue, 14 Jun

Don’t just build a data lake, build data powerhouse.

Akash Mishra (@sleepythread)

  • Full talk
  • Intermediate
  • 4 upvotes
  • 0 comments
  • Mon, 13 Jun

Distributed Computing Abstractions for Big Data Science

Vijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran)

  • Full talk
  • Intermediate
  • 6 upvotes
  • 0 comments
  • Thu, 9 Jun
  • slideshow

RNNs for multimodal information fusion

Om Deshmukh (@omdesh)

  • Crisp talk
  • Intermediate
  • 3 upvotes
  • 0 comments
  • Thu, 9 Jun

Leveraging Streaming Systems for Machine Learning

Vipul Gupta (@vipulgupta)

  • Crisp talk
  • Intermediate
  • 6 upvotes
  • 0 comments
  • Wed, 8 Jun

Data Simulation as a means to intuitively grasp Statistics and it's direct application to prediction problems

Lakshman Prasad (@becomingguru)

  • Full talk
  • Beginner
  • 6 upvotes
  • 0 comments
  • Tue, 7 Jun

Exploit conceptual data models using ontology modeling

Udaya Chitta (@uchitta)

  • Crisp talk
  • Beginner
  • 2 upvotes
  • 0 comments
  • Mon, 2 May

Anti-patterns in designing machine learning systems

Suchana Seth (@suchana)

  • Advanced
  • 25 upvotes
  • 0 comments
  • Mon, 2 May

An Approach for recommending TopK Digital Artworks

Vivek Anand Rao T S (@vtemker)

  • Crisp talk
  • Beginner
  • 2 upvotes
  • 0 comments
  • Mon, 2 May

Four horsemen of the IoT

Anuj Deshpande (@anujdeshpande)

  • Full talk
  • Intermediate
  • 0 upvotes
  • 0 comments
  • Sun, 1 May
  • slideshow

Challenges in Data Warehouse Augmentation on Hadoop

koteswara Vemu (@koteswara)

  • Sponsored
  • Intermediate
  • 3 upvotes
  • 0 comments
  • Sat, 30 Apr

Recommender Engines : A Peak into Predictive Analytics

Raghav Bali (@baliraghav)

  • Full talk
  • Beginner
  • 14 upvotes
  • 2 comments
  • Sat, 30 Apr
  • play_arrow
  • slideshow

Data pipelines - Cakewalk with Docker and Luigi

Shubhadit Sharma (@shubhadit)

  • Advanced
  • 15 upvotes
  • 1 comments
  • Sat, 30 Apr

Apache Drill - Optimising Time to market

shubham sharma (@gabber12)

  • Crisp talk
  • Intermediate
  • 10 upvotes
  • 0 comments
  • Sat, 30 Apr

Sentiment analysis to evaluate the performance of Fund Managers

Geeyavudeen Musthafa (@geeyamusthafa) (proposing)

  • Crisp talk
  • Beginner
  • 0 upvotes
  • 0 comments
  • Sat, 30 Apr

A large scale IOT platform architecture using open source apache projects like Nifi, Kafka, Storm, Spark and Hadoop.

Satish Duggana (@satishd)

  • Full talk
  • Intermediate
  • 10 upvotes
  • 2 comments
  • Sat, 30 Apr

Stream in a Flink way

Sharath B. Patel (@sharathsteel)

  • Full talk
  • Intermediate
  • 13 upvotes
  • 0 comments
  • Sat, 30 Apr
  • slideshow

Building a large scale fully automatic machine learning platform from scratch

Dipayan Maiti (@dipayanm)

  • Full talk
  • Advanced
  • 5 upvotes
  • 0 comments
  • Sat, 30 Apr

Knowledge Inference: Estimating how much the student knows

Amar Lalwani (@amar1707)

  • Full talk
  • Intermediate
  • 18 upvotes
  • 0 comments
  • Sat, 30 Apr
  • slideshow

Sensor Analytics for IoT and Embedded Systems

Amit Doshi (@amitdoshi)

  • Crisp talk
  • Intermediate
  • 2 upvotes
  • 0 comments
  • Sat, 30 Apr

Machine Learning Application in MicroFinance

Anubhav Dikshit

  • Crisp talk
  • Beginner
  • 8 upvotes
  • 0 comments
  • Sat, 30 Apr

Security Analytics at Web Scale

pratim mukherjee (@pratimkm)

  • Full talk
  • Intermediate
  • 15 upvotes
  • 0 comments
  • Fri, 29 Apr
  • slideshow

High performance computing using Spark

Anand Katti (@anandkatti)

  • Intermediate
  • 2 upvotes
  • 1 comments
  • Fri, 29 Apr

Interactive data transformations at scale

Abhilash L L (@abhilashll)

  • Sponsored
  • Beginner
  • 10 upvotes
  • 0 comments
  • Fri, 29 Apr

Discovering App Relationships in Smart Phones through Large Scale Mining of User Journey Data

Hanu Susarla (@susarlah)

  • Full talk
  • Intermediate
  • 13 upvotes
  • 1 comments
  • Fri, 29 Apr

Artificial Intelligence for Efficient Financial Markets

Sivasankari Ramamurthy (@sivas)

  • Crisp talk
  • Intermediate
  • 0 upvotes
  • 0 comments
  • Fri, 29 Apr

Machine Learning - Democratized

BrijRaj Singh (@brijrajsingh)

  • Full talk
  • Beginner
  • 6 upvotes
  • 0 comments
  • Thu, 28 Apr

Forecasting the degradation of Network KPIs

Roshni Mohandas (@roshnimohandas)

  • Crisp talk
  • Intermediate
  • 17 upvotes
  • 3 comments
  • Thu, 28 Apr

Visually reading the configuration of a Rubiks cube using Probabilistic Graphical Model

Sunil S Nandihalli (@sunilnandihalli)

  • Intermediate
  • 3 upvotes
  • 0 comments
  • Wed, 27 Apr

(Workshop) Understanding neural networks by building few from scratch

Harshad Saykhedkar (@harshss)

  • Workshop
  • Intermediate
  • 1 upvotes
  • 0 comments
  • Wed, 27 Apr

Apache Storm past, present and future

Arun Mahadevan (@arunm)

  • Intermediate
  • 5 upvotes
  • 0 comments
  • Tue, 26 Apr

Designing Data Products

Mahendra Kariya (@mahendrakariya)

  • Intermediate
  • 4 upvotes
  • 0 comments
  • Tue, 26 Apr

Unified & Distributed Test Infrastructure at Scale (Hortonworks Data Platform Testing)

Shankar Hiremath (@shankarhiremath)

  • Crisp talk
  • Intermediate
  • 2 upvotes
  • 0 comments
  • Sun, 24 Apr
  • slideshow

Big Data Structures

Ranganathan B (@ranganathan)

  • Full talk
  • Beginner
  • 21 upvotes
  • 3 comments
  • Sun, 24 Apr

Statistical Models for Better Customer Engagement

Venkatramanan P.R. (@venkatpr)

  • Intermediate
  • 8 upvotes
  • 0 comments
  • Thu, 21 Apr

Emerging patterns of lifestyle impact on personal health & wellness

Tanmay Gupta (@tanmaygupta)

  • Crisp talk
  • Beginner
  • 4 upvotes
  • 0 comments
  • Sun, 10 Apr

Design Patterns in IoT/IoE

Srinivasa Rao Aravilli (@aravilli)

  • Crisp talk
  • Intermediate
  • 4 upvotes
  • 0 comments
  • Wed, 30 Mar

Smart Energy

Srinivasa Rao Aravilli (@aravilli)

  • Crisp talk
  • Intermediate
  • 4 upvotes
  • 0 comments
  • Tue, 15 Mar

Long Running Services on YARN: Future of Service Deployment & Management via Hadoop

Prasath Venkatraman (@ask4prasath)

  • Advanced
  • 36 upvotes
  • 12 comments
  • Mon, 14 Mar

Real-time Ingestion of logs into Hive with a low latency, to query and respond to events

Pallav Jakhotiya (@pallavjakhotiya)

  • Crisp talk
  • Intermediate
  • 9 upvotes
  • 0 comments
  • Mon, 14 Mar
  • slideshow