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.

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.

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

Tanmay Gupta

@tanmaygupta

Emerging patterns of lifestyle impact on personal health & wellness

Submitted Apr 10, 2016

Lifestyle is changing at a very rapid pace as we enter the internet era. Pace of evolution in terms of technology, lifestyle, work environment, etc. is more rapid than ever before and has resulted in how our lifestyle and health has changed. To be able to understand the new health and wellness patterns emerging, and help a preventive health care based start-up design improved solutions to help people preserve their health, I conducted a study using data collected by their team to understand some of the relationships between lifestyle, common medical complaints faced by people and their inter-relationships. The correlation analysis performed on the dataset identified various connections between different health related problems. These results were then visualized to draw insights using network analysis, and communities amongst the different connections were identified using modularity index. The whole study presented some very interesting relationships like regular stress and lack of sleep being closely associated with a combination of heartburn, gastritis & headaches etc. and many more similar findings.

Outline

This talk will present some of the interesting facts derived from handshake between healthcare & machine learning techniques. Few questions that would be answered are:

Does our lifestyle has any effect on our health?
We often hear people talking about health and fitness and how the modern lifestyle has affected the way we live. But how many of us are truly serious about our health? Health is largely impacted by a combination of lifestyle, environmental factors, genetic make-up an individual and the kind of care the individual receives.

How the real time data was collected and refined?
We conducted a survey and asked over 4,000 people to fill in a questionnaire which included an individual’s demographic, lifestyle, medical complaints, family history, and even gynecology details. The population comprised of 70% males & 30% females with mean population age of 35 years.

What does correlation analysis tells about health conditions?
One of the clusters in the network analysis depicted a close connection between comorbidities viz. heartburn, gastritis, Hhead aches, sleep & stress which a clear showed an association between long working hours, unhealthy food habits and low physical activity of today’s working force.

What should be our next steps?
The study was able to identify a series of correlation between various lifestyle patterns and clusters in the young population, to be able to develop more effective preventive /mitigation strategies for some of the new age health problems.

Requirements

This session would present insights on health related problems using machine learning techniques for everyone. So, the only requirement would be a basic understanding of network analysis (as in social network), a curiosity to learn and open mind for a healthy diccussion.

Speaker bio

Tanmay is a researcher with a background in application of machine learning algorithms to product development & enhancement. His specialties include predictive analytics & mathematical modeling using R as the primary tool. He has developed predictive models on patient readmission, length of stay, cost model etc. and published case study & research papers in International Journal of Medical Science and Public Health (IJMSPH), Harvard Business Journal (HBJ) & International Journal of Science & Research (IJSR). He has also presented some of his work at the annual American Medical Informatics Conference (AMIA) as well.
He has more than 9 years of industry experience with 6+ years in healthcare domain. He did his B.Tech in Electronics Engineering and pursued professional course in Business Analytics & Intelligence from IIM-B.

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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