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The Fifth Elephant round the year submissions for 2019

The Fifth Elephant round the year submissions for 2019

Submit a talk on data, data science, analytics, business intelligence, data engineering and ML engineering

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Accepting submissions till 31 Dec 2020, 11:59 PM

If you missed the deadline for submitting your talk for The Fifth Elephant 2019 – to be held in Bangalore on 25 and 26 July – you can propose a talk here.

We are accepting talks on:

  1. Data engineering – engineering and architecture approaches; problems that teams were attempting to solve (and therefore the solutions that they built).
  2. ML engineering – engineering and architecture approaches; problems that teams were attempting to solve (and therefore the solutions that they built).
  3. Data science – and its applications in diverse domains.
  4. Open source algorithms
  5. Data privacy and its solutions in technology; engineering implementations of HIPPA compliance, GDPR and other data protection frameworks.
  6. Data security – standards, approaches to solving data security, challenges and problems to solve for data security at scale.
  7. Business intelligence – how non-technical teams are accessing data in companies to mine intelligence; approaches to BI; real-life case studies and applications of BI; what counts as business intelligence for businesses.
  8. Decision science.

Perks for submitting proposals:

Submitting a proposal, especially with our process, is hard work. We appreciate your effort.
We offer one conference ticket at discounted price to each proposer.
We only accept one speaker per talk. This is non-negotiable. Workshops may have more than one instructor.
In case of proposals where more than one person has been mentioned as collaborator, we offer the discounted ticket and t-shirt only to the person with who the editorial team corresponded directly during the evaluation process.

Selection criteria:

The first filter for a proposal is whether the technology or solution you are referring to is open source or not. The following criteria apply for closed source talks:

  1. If the technology or solution is proprietary, and you want to speak about your proprietary solution to make a pitch to the audience, you should pick up a sponsored session. This involves paying for the speaking slot. Write to fifthelephant.editorial@hasgeek.com
  2. If the technology or solution is in the process of being open sourced, we will consider the talk only if the solution is open sourced at least three months before the conference.
  3. If your solution is closed source, you should consider proposing a talk explaining why you built it in the first place; what options did you consider (business-wise and technology-wise) before making the decision to develop the solution; or, what is your specific use case that left you without existing options and necessitated creating the in-house solution.

The criteria for selecting proposals, in the order of importance, are:

  1. Key insight or takeaway: what can you share with participants that will help them in their work and in thinking about the ML, big data and data science problem space?
  2. Structure of the talk and flow of content: a detailed outline – either as mindmap or draft slides or textual description – will help us understand the focus of the talk, and the clarity of your thought process.
  3. Ability to communicate succinctly, and how you engage with the audience. You must submit link to a two-minute preview video explaining what your talk is about, and what is the key takeaway for the audience.

No one submits the perfect proposal in the first instance. We therefore encourage you to:

  1. Submit your proposal early so that we have more time to iterate if the proposal has potential.
  2. Talk to us on our community Slack channel: https://friends.hasgeek.com if you want to discuss an idea for your proposal, and need help / advice on how to structure it. Head over to the link to request an invite and join #fifthel.

Our editorial team helps potential speakers in honing their speaking skills, fine tuning and rehearsing content at least twice - before the main conference - and sharpening the focus of talks.

How to submit a proposal (and increase your chances of getting selected):

The following guidelines will help you in submitting a proposal:

  1. Focus on why, not how. Explain to participants why you made a business or engineering decision, or why you chose a particular approach to solving your problem.
  2. The journey is more important than the solution you may want to explain. We are interested in the journey, not the outcome alone. Share as much detail as possible about how you solved the problem. Glossing over details does not help participants grasp real insights.
  3. Focus on what participants from other domains can learn/abstract from your journey / solution. Refer to these talks from The Fifth Elephant 2017, which participants liked most: http://hsgk.in/2uvYKI9 and http://hsgk.in/2ufhbWb
  4. We do not accept how-to talks unless they demonstrate latest technology. If you are demonstrating new tech, show enough to motivate participants to explore the technology later. Refer to talks such as this: http://hsgk.in/2vDpag4 and http://hsgk.in/2varOqt to structure your proposal.
  5. Similarly, we don’t accept talks on topics that have already been covered in the previous editions. If you are unsure about whether your proposal falls in this category, drop an email to: fifthelephant.editorial@hasgeek.com
  6. Content that can be read off the internet does not interest us. Our participants are keen to listen to use cases and experience stories that will help them in their practice.

To summarize, we do not accept talks that gloss over details or try to deliver high-level knowledge without covering depth. Talks have to be backed with real insights and experiences for the content to be useful to participants.

Passes and honorarium for speakers:

We pay an honorarium of Rs. 3,000 to each speaker and workshop instructor at the end of their talk/workshop. Confirmed speakers and instructors also get a pass to the conference and networking dinner. We do not provide free passes for speakers’ colleagues and spouses.

Travel grants for outstation speakers:

Travel grants are available for international and domestic speakers. We evaluate each case on its merits, giving preference to women, people of non-binary gender, and Africans. If you require a grant, request it when you submit your proposal in the field where you add your location. The Fifth Elephant is funded through ticket purchases and sponsorships; travel grant budgets vary.

You must submit the following details along with your proposal, or within 10 days of submission:

  1. Draft slides, mind map or a textual description detailing the structure and content of your talk.
  2. Link to a self-recorded, two-minute preview video, where you explain what your talk is about, and the key takeaways for participants. This preview video helps conference editors understand the lucidity of your thoughts and how invested you are in presenting insights beyond the solution you have built, or your use case. Please note that the preview video should be submitted irrespective of whether you have spoken at past editions of The Fifth Elephant.
  3. If you submit a workshop proposal, you must specify the target audience for your workshop; duration; number of participants you can accommodate; pre-requisites for the workshop; link to GitHub repositories and a document showing the full workshop plan.

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

Accepting submissions till 31 Dec 2020, 11:59 PM

Not accepting submissions

If you missed the deadline for submitting your talk for The Fifth Elephant 2019 – to be held in Bangalore on 25 and 26 July – you can propose a talk here. We are accepting talks on: Data engineering – engineering and architecture approaches; problems that teams were attempting to solve (and therefo… expand

If you missed the deadline for submitting your talk for The Fifth Elephant 2019 – to be held in Bangalore on 25 and 26 July – you can propose a talk here.

We are accepting talks on:

  1. Data engineering – engineering and architecture approaches; problems that teams were attempting to solve (and therefore the solutions that they built).
  2. ML engineering – engineering and architecture approaches; problems that teams were attempting to solve (and therefore the solutions that they built).
  3. Data science – and its applications in diverse domains.
  4. Open source algorithms
  5. Data privacy and its solutions in technology; engineering implementations of HIPPA compliance, GDPR and other data protection frameworks.
  6. Data security – standards, approaches to solving data security, challenges and problems to solve for data security at scale.
  7. Business intelligence – how non-technical teams are accessing data in companies to mine intelligence; approaches to BI; real-life case studies and applications of BI; what counts as business intelligence for businesses.
  8. Decision science.
Make a submission

Accepting submissions till 31 Dec 2020, 11:59 PM

Aayushi Pathak Proposing

Building a large-scale Data as a Service (DaaS) platform to consistently deliver high-quality datasets

As a provider of Competitive Intelligence as a Service to eCommerce businesses and consumer brands, DataWeave aggregates and analyses product catalog data from eCommerce websites each day at massive scale. Once aggregated, this data is fed into a complex process of extraction, transformation, machine learning, and analyses. These operations are performed on a consistent basis to provide our custo… more
  • 4 comments
  • Rejected
  • 01 May 2019
Short talk of 20 mins

Aayushi Pathak Proposing

Finding needles in high dimensional haystacks: Product Matching in Retail

Matching the same and similar products is a problem fundamental to the online retail industry with multiple applications spanning across price optimization, recommending similar or substitute products to customers, understanding gaps in product assortments, and counterfeit product detection. Given that that there are no standard product identifiers, catalog data is often noisy, incomplete and non… more
  • 10 comments
  • Rejected
  • 01 May 2019
Short talk of 20 mins

Aayushi Pathak Proposing

Websites to Datasets

As a provider of Competitive Intelligence as a Service to eCommerce businesses and consumer brands, DataWeave aggregates and analyses product catalog data from eCommerce websites each day at massive scale. Once aggregated, this data is fed into a complex process of extraction, transformation, machine learning, and analyses. These operations are performed on a consistent basis to provide our custo… more
  • 11 comments
  • Rejected
  • 09 May 2019
Short talk of 20 mins

Pradip Thoke

A Journey of Building Dream11's Data Platform

Dream11 is India’s biggest fantasy sports platform that allows users to play fantasy cricket, hockey, football, kabaddi and basketball. Our total user base is over 70 million and expected to cross 100 million by end of 2019. more
  • 2 comments
  • Rejected
  • 10 May 2019

usha rengaraju

Deep Learning powered Genomic Research

The event disease happens when there is a slip in the finely orchestrated dance between physiology, environment and genes. Treatment with chemicals (natural, synthetic or combination) solved some diseases but others persisted and got propagated along the generations. Molecular basis of disease became prime center of studies to understand and to analyze root cause. Cancer also showed a way that or… more
  • 0 comments
  • Submitted
  • 21 May 2019
Workshop

usha rengaraju

Panel Discussion around Healthcare Analytics

Panel Discussion around Healthcare Analytics Outline more
  • 0 comments
  • Submitted
  • 21 May 2019
Birds of a Feather session of 1 hour

Logesh kumar

Interpretable NLP Models

Deep learning models are always known to be a black box and lacks interpretability compared to traditional machine learning models. So,There is alway a hesitation in adopting deep learning models in user facing applications (especially medical applications). Recent progress in NLP with the advent of Attention based models , LIME and other techniques have helped to solve this. I would like to walk… more
  • 3 comments
  • Rejected
  • 31 May 2019
Tutorial

Jaydeep Vishwakarma

Real-Time DataQuality on Flink

My use case is to provide monitoring, and improving the overall search data quality, also to find the unusual patterns of user’s search behavior, and notifying the intent on-site back to the respective business stakeholders. To achieve the same, I explored various big data processing engines, which can process the huge data with complex business logic in real time. Eventually, I used Flink Stream… more
  • 4 comments
  • Rejected
  • 17 Jun 2019
Full talk of 40 mins

Sanjoy Bose

Building a Location Intelligence Platform for audience segmentation

The ROI of OOH (Out of Home Advertisement) depends on precise and intelligent targeting of advertisements. The media buyers therefore require detailed understanding and visibility of the audiences across various attributes so that they can then plan their OOH media buy to specifically target a selected set of audiences. Location information of the user, device level audience data, enriched with r… more
  • 4 comments
  • Rejected
  • 18 Jun 2019
Short talk of 20 mins

Anshul Singhle

How to make a kickass data platform with spark and S3

In this talk, we will explore the advantages and challenges faced while running an in-house data platform using spark and S3. We will also discuss how to add some essential features to your platform like autoscaling and access control. The latter part of the talk will also address some ways to organise data in S3, storage formats for big data and indexing to improve read performance for big-data … more
  • 5 comments
  • Under evaluation
  • 01 Jul 2019
Full talk of 40 mins

Tuhin Sharma

Anomaly Detection at Scale: Architectural Choices for Data Pipelines for 7B events per day

Cloud-native applications. Multiple Cloud providers. Hybrid Cloud. 1000s of VMs and containers. Complex network policies. Millions of connections and requests in any given time window. This is the typical situation faced by a Security Operations Control (SOC) Analyst every single day. In this talk, the speaker talks about the high-availability and highly scalable data pipelines that he built for … more
  • 0 comments
  • Submitted
  • 02 Jul 2019
Full talk of 40 mins

A Naveen Kumar

Deploying Deep Learning models on the Edge (Android, IOS, ...)

The ability to train the task specific deep learning models is very easy these days, with the wide range of available libraries and documentation around it. But, the difficulty lies in bringing it to production ready mode. Especially, if the application concentrates on Mobile platform. Though there are existing wrappers of certain libraries to make them work, but, as of now, they are slow and use… more
  • 0 comments
  • Submitted
  • 05 Jul 2019
Full talk of 40 mins

Ravi Ranjan

Machine Learning Model Management with MLflow

Background Data is the new oil and its size is growing exponentially day by day. Most of the companies are leveraging data science capabilities extensively to affect business decisions, perform audits on ML patterns, decode faults in business logic, and more. They run large number of machine learning model to produce results. more
  • 0 comments
  • Submitted
  • 15 Jul 2019
Tutorial

Chaitanya Hegde

Building a data pipeline inside and outside a vehicle

Ather 450 is a smart electric vehicle with data intensive features on the vehicle as well as on the cloud/mobile app. On the vehicle, the on-board software uses the vehicle data to make decisions regarding the vehicle behaviour and safety, while giving some user delight features like auto-indicator. Via the cloud, user has a mobile app using which the vehicle can be monitored and their ride stati… more
  • 1 comments
  • Submitted
  • 09 Jul 2019
Short talk of 20 mins

Chandini Jain

Data Science for the discretionary managers: Lessons from a 60 trillion$ traditional industry resistant to change and facing the quant threat

Investment management is a 60 Trillion$ industry, and despite the recent advancements in data science and machine learning, still remains fairly discretionary. Untill recently, less 20% of the funds called themselves quantitative. However, there is an absolutely massive transformation taking place right now within the discretionary investment management industry. Quantitative and systematic strat… more
  • 0 comments
  • Submitted
  • 19 Jul 2019
Short talk of 20 mins

Amit Garg

Case study: Outbound logistics optimization for multi depot problem with time window

Case study: Outbound logistics optimization for multi depot problem with time window more
  • 0 comments
  • Submitted
  • 25 Jul 2019
Short talk of 20 mins
Make a submission

Accepting submissions till 31 Dec 2020, 11:59 PM

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