27-28 July 2017, Bangalore
Status: Submissions and voting closed, awaiting jury selection

Theme and format

The Fifth Elephant 2017 is a four-track conference on:

  1. Data engineering – building pipelines and platforms; exposure to latest open source tools for data mining and real-time analytics.
  2. Application of Machine Learning (ML) in diverse domains such as IOT, payments, e-commerce, education, ecology, government, agriculture, computational biology, social network analysis and emerging markets.
  3. Hands-on tutorials on data mining tools, and ML platforms and techniques.
  4. Off-the-record (OTR) sessions on privacy issues concerning data; building data pipelines; failure stories in ML; interesting problems to solve with data science; and other relevant topics.

The Fifth Elephant is a conference for practitioners, by practitioners.

Talk submissions are now closed.

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-record, 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 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 documents showing the full workshop plan.

About the conference

This year is the sixth edition of The Fifth Elephant. The conference is a renowned gathering of data scientists, programmers, analysts, researchers, and technologists working in the areas of data mining, analytics, machine learning and deep learning from different domains.

We invite proposals for the following sessions, with a clear focus on the big picture and insights that participants can apply in their work:

Selection Process

  1. Proposals will be filtered and shortlisted by an Editorial Panel.
  2. Proposers, editors and community members must respond to comments as openly as possible so that the selection processs is transparent.
  3. Proposers are also encouraged to vote and comment on other proposals submitted here.

Selection Process Flowchart

We will notify you if we move your proposal to the next round or reject it. A speaker is NOT confirmed for a slot unless we explicitly mention so in an email or over any other medium of communication.

Selected speakers must participate in one or 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.

Travel grants

Partial or full grants, covering travel and accomodation are made available to speakers delivering full sessions (40 minutes) and workshops. Grants are limited, and are given in the order of preference to students, women, persons of non-binary genders, and speakers from Asia and Africa.

Commitment to Open Source

We believe in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like for 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), you should consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support the conference in return for giving you an audience. Your session will be marked on the schedule as a “sponsored session”.

Important Dates:

Contact

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

Confirmed sessions

# Speaker Section Level +1 Submitted
1 Bits and joules: data-driven energy systems
Deva P. Seetharam (@dpseetharam) Full talk for Data in Government track Beginner 1 0 Tue, 25 Jul
2 How We Built Our Machine Intelligence To Help Humans Save Lives
Zainul Charbiwala (@zainulcharbiwala) Full talk for Data in Government track Beginner 1 0 Sat, 22 Jul
3 Open data in government: challenges, and the case of Telangana Open Data Initiative  
Rakesh Dubbudu (@rakeshdubbudu) Full talk for Data in Government track Beginner 1 0 Wed, 12 Jul
4 Time Processing and Watermarks using Google Pub\Sub and Google DataFlow.
Swapnil Dubey (@swapnildubey) Pune Meetup Advanced 5 0 Thu, 29 Jun
5 Finding topics in short texts
Yash Gandhi (@yashgandhi) Pune Meetup Intermediate 17 1 Wed, 28 Jun
6 Introduction to recommendation systems with Python
Harshad Saykhedkar (@harshss) Pune Meetup Intermediate 13 0 Thu, 22 Jun
7 Interactive Data Visualisation using Markdown    
Amit Kapoor (@amitkaps) Full talk for data engineering track Beginner 3 0 Mon, 12 Jun
8 Maps ❤️ Data: A voyage across the world of geo-visualization  
Rasagy Sharma (@rasagy) Full talk for data engineering track Intermediate 4 0 Sat, 10 Jun
9 Distributed Machine Learning - Challenges and Oppurtunities    
Anand Chitipothu (@anandology) Crisp talk for data engineering track Intermediate 7 0 Sat, 10 Jun
10 Augmenting Solr’s NLP Capabilities with Deep-Learning Features to Match Images    
Kumar Shubham (@kumar-shubham) Crisp talk for data engineering track Intermediate 10 2 Fri, 9 Jun
11 Near Real time indexing/search in E-commerce marketplace : Approaches and Learnings    
Umesh Prasad (@umeshprasad) Full talk for data engineering track Intermediate 8 1 Fri, 9 Jun
12 Interactive Realtime Dashboards on Data Streams using Kafka, Druid and Superset  
Nishant Bangarwa (@nishantbangarwa) Full talk for data engineering track Intermediate 4 1 Tue, 6 Jun
13 Machine Learning as a Service
Bargava Subramanian (@barsubra) Workshops Beginner 4 1 Mon, 29 May
14 Apache Atlas Introduction: Need for Governance and Metadata management  
Vimal Sharma (@svimal2106) Full talk for data engineering track Intermediate 2 1 Fri, 26 May
15 Lessons learned from building a globally distributed database service from the ground up    
Dharma Shukla (@dharmashukla) Full talk for data engineering track Intermediate 25 8 Fri, 26 May
16 What explains our marks?  
Anand S (@sanand0) Crisp talk for Data in Government track Beginner 7 3 Wed, 24 May
17 Do you know what's on TV?    
Bharath Mohan (@bharathmohan) Full talk for data engineering track Intermediate 6 6 Mon, 22 May
18 Developing and Deploying Analytics for Internet of Things (IoT)  
Amit Doshi (@amitdoshi) Sponsored session Intermediate 7 7 Mon, 22 May
19 What database? - a practical guide to selection from NoSQL, SQL and Polyglot data stores    
Regunath Balasubramanian (@regunathb) Full talk for data engineering track Intermediate 2 2 Mon, 22 May
20 Plumbing data science pipelines    
Krishnapriya Satagopan (@kpsatagopan) Crisp talk for data engineering track Intermediate 11 2 Mon, 22 May
21 Wait, I can explain this! (ML models explaining their predictions)    
Ramprakash R (@ramprakashr) Crisp talk for data engineering track Intermediate 19 4 Mon, 22 May
22 Gabbar: Machine learning to guard OpenStreetMap    
Bhargav Kowshik (@bkowshik) Full talk for data engineering track Intermediate 5 5 Sun, 30 Apr
23 Adapting Bandit Algorithms to optimise user experience at Practo Consult    
Santosh GSK (@santoshgadde) Crisp talk for data engineering track Intermediate 30 4 Sun, 30 Apr
24 How we are building serverless architectures for Deep Learning & NLP at Episource    
Manas Ranjan Kar (@manasrkar-episource) Crisp talk for data engineering track Intermediate 7 2 Sun, 30 Apr
25 Transforming India's Budgets into Open Linked Data    
Gaurav Godhwani (@gggodhwani) Full talk for Data in Government track Intermediate 10 2 Sun, 30 Apr
26 5 Lessons I’ve Learned Tackling Product Matching for E-commerce  
Govind Chandrasekhar (@gc20) Full talk for data engineering track Intermediate 4 2 Sat, 29 Apr
27 Designing Machine Learning Pipelines for Mining Transactional SMS Messages    
Paul Meinshausen (@pmeins) Full talk for data engineering track Intermediate 12 2 Fri, 28 Apr
28 Fraud Detection & Risk Management in Payment Systems implemented using a Hybrid Memory Database    
Srini V. Srinivasan (@drvsrinivasan) Full talk in Payment Analytics track Intermediate 22 0 Thu, 27 Apr
29 Suuchi - Toolkit to build distributed systems    
Sriram R (@brewkode) Full talk for data engineering track Intermediate 26 9 Wed, 26 Apr
30 Machine Learning from Practice to Production    
Ramanan Balakrishnan (@ramananbalakrishnan) Full talk for data engineering track Beginner 13 2 Tue, 25 Apr
31 Distributed Consensus and Data Safety: NewSQL Perspective    
Vijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran) Full talk for data engineering track Intermediate 8 5 Tue, 18 Apr
32 From a recommendations carousel to personalizing entire app - personalization story at paytm  
Charumitra Pujari (@charupujari) Full talk in Payment Analytics track Advanced 10 1 Tue, 4 Apr

Unconfirmed proposals

# Speaker Section Level +1 Submitted
1 Building a converged platform for data analytics
David Sangma (@davidsangma) (proposing) Crisp talk for data engineering track Advanced 0 1 Mon, 12 Jun
2 Democratising Data in the Microservices World
Rajaram Mallya (@rajarammallya) Full talk for data engineering track Intermediate 4 1 Sat, 10 Jun
3 Gen Z BI Paradigm - A Scalable , hybrid and collaborative Visualization Architecture using Spark , No SQL and Restful API    
Deepikavalli A (@deepikavalli) Crisp talk for data engineering track Intermediate 1 2 Sat, 10 Jun
4 Zero down time ML model swap using docker and kubernetes    
anugrah nayar (@codewalker) Full talk for data engineering track Beginner 8 0 Sat, 10 Jun
5 Multi-channel conversational chatbot platform powered by NLP engine
Prakash Mall (@prakashmall) Crisp talk for data engineering track Beginner 1 0 Sat, 10 Jun
6 Building camera based intelligent applications    
Nabarun Pal (@palnabarun) Crisp talk for data engineering track Intermediate 10 0 Sat, 10 Jun
7 Making sense of Digital and Physical Documents using ML and Optical Character Recognition    
Nitin Saraswat (@chunky) Full talk for data engineering track Intermediate 17 0 Sat, 10 Jun
8 ML Goes Fruitful    
Preeti Negi (@preeti14dec) Workshops Beginner 1 0 Sat, 10 Jun
9 How Machine Learning Algorithms evolved at Haptik while it's Chatbot catered to 200 million messages    
krupal Modi (@superkrups) Full talk for data engineering track Intermediate 26 0 Fri, 9 Jun
10 Application Dependency Data Performance Mapping tool - Dynatrace    
Chandrish M (@chandrish) Crisp talk for data engineering track Beginner 3 0 Fri, 9 Jun
11 Leonardo Machine Learning Foundation - Adding Intelligence to your Enterprise Business    
sainath v (@sapcloudengineers) Crisp talk for data engineering track Beginner 2 0 Fri, 9 Jun
12 Data in drug discovery    
Shefali Lathwal (@shefalilathwal) Full talk for data engineering track Beginner 2 1 Fri, 9 Jun
13 Using Probabilistic Data Structures to Build Real-Time Monitoring Dashboards    
Rahul Ramesh (@rahul-ramesh-17) Crisp talk for data engineering track Beginner 10 0 Fri, 9 Jun
14 Recommendation Engine for Wide Transactions    
Harjindersingh Mistry (@harjinder-hari) Full talk for data engineering track Beginner 2 0 Fri, 9 Jun
15 Lessons Learnt building and optimizing a self service Data Platform on Apache Spark at Indix    
Matild Reema (@matild-reema) Full talk for data engineering track Intermediate 22 0 Fri, 9 Jun
16 Unless you measure it; you can’t improve it - Data pipelines for your business KPIs and KRAs    
Ketan Khairnar (@ketankhairnar) Workshops Intermediate 10 0 Thu, 8 Jun
17 Modeling intent of the user using Probabilistic Machine Learning    
Sarah Masud (@sara-02) Full talk for data engineering track Intermediate 4 2 Wed, 7 Jun
18 Unlock sub-second SQL analytics over terrabytes of data with Hive and Druid
Nishant Bangarwa (@nishantbangarwa) Full talk for data engineering track Beginner 1 1 Tue, 6 Jun
19 How to build scalable and robust data pipeline iteratively.
Danish M (@pixelgenie) Full talk for data engineering track Intermediate 3 1 Sun, 4 Jun
20 Talk Less, Chat More    
Ashutosh (@ashutrv) Full talk for data engineering track Beginner 2 2 Fri, 2 Jun
21 Saving taxes without breaking laws using Machine Learning    
GS Jayendran (@vyakyajay) Full talk in Payment Analytics track Beginner 9 0 Thu, 1 Jun
22 Reality of Data Modelling: Many analysts, one dataset: Multiple Results
Lakshman Prasad (@becomingguru) Full talk for data engineering track Intermediate 3 0 Wed, 31 May
23 Building a Generic but highly customizable and scalable Anomaly Detection System @ Badoo
Akash Mishra (@sleepythread) Full talk for data engineering track Intermediate 6 1 Tue, 30 May
24 How to prepare your language for Machine Learning and NLP with an open audio documentation toolkit    
Subhashish Panigrahi (@psubhashish) Full talk for Data in Government track Intermediate 4 0 Sun, 28 May
25 How to read a user's mind? Designing algorithms for contextual recommendations  
Bharath Mohan (@bharathmohan) Crisp talk for data engineering track Beginner 5 1 Mon, 22 May
26 Scalability truths and serverless architectures - why it is harder with stateful, data-driven systems  
Regunath Balasubramanian (@regunathb) Full talk for data engineering track Intermediate 3 5 Mon, 22 May
27 Interestingness of interestingness measures  
Simrat Hanspal (@simrathanspal) Full talk for data engineering track Advanced 17 7 Sun, 30 Apr
28 Learnings from building TV viewership platform for 100 Million users at zapr    
Agam Jain (@agamj20) Full talk for data engineering track Intermediate 6 3 Sun, 30 Apr
29 Seamless Hadoop Deployments - Myth or Reality?  
Ragesh Rajagopalan (@rajagopr) Crisp talk for data engineering track Beginner 10 3 Sun, 30 Apr
30 Designing Cost Effective Cloud Native Applications  
Tarun Gupta (@tarung) Crisp talk for data engineering track Intermediate 5 1 Sun, 30 Apr
31 Processing mission critical events in real time    
Tarun Gupta (@tarung) Crisp talk for data engineering track Intermediate 5 3 Sun, 30 Apr
32 Human Centric API Design  
Gagan Gupta (@gagangupt16) Crisp talk for data engineering track Beginner 8 1 Sun, 30 Apr
33 Out of Stone age : Why investing in developer tools is necessary for big data development to scale.    
Shankar Manian (@shanm) Full talk for data engineering track Intermediate 11 1 Sat, 29 Apr
34 Beyond unit tests: Deployment and testing for Hadoop/Spark workflows    
Anant Nag (@nntnag17) Full talk for data engineering track Intermediate 11 1 Fri, 28 Apr
35 Making data scientists life easy with Docker    
Abhishek Kumar (@meabhishekkumar) Full talk for data engineering track Intermediate 14 3 Fri, 28 Apr
36 Real-time Monitoring of Big Data Workflows    
Akshay Rai (@akshayrai) Full talk for data engineering track Intermediate 12 4 Fri, 28 Apr
37 Causal Analytics in Retail and Telco  
Gaurav Goswami (@gauravgoswami) Crisp talk for data engineering track Intermediate 2 10 Fri, 28 Apr
38 Dr. Elephant: Achieving Quicker, Easier, and Cost-effective Big Data Analytics    
Akshay Rai (@akshayrai) Crisp talk for Data in Government track Intermediate 11 2 Thu, 27 Apr
39 Using data pipelines to navigate your data ocean  
Vipul Mathur (@vipulmathur) Full talk for data engineering track Beginner 15 2 Thu, 27 Apr
40 The Python ecosystem for data science - Landscape Overview    
Ananth Krishnamoorthy (@akrishnamoorthy) Full talk for data engineering track Beginner 8 3 Thu, 27 Apr
41 A Recommender for Match-making: Item-based CF, PageRank, Evaluation techniques & Deep-Learning
prabhakar srinivasan (@prabhacar7) Full talk for data engineering track Advanced 8 3 Thu, 27 Apr
42 Search Infrastructure @ Slack using Lambda Architecture    
Ananth Durai (@vananth22) Full talk for data engineering track Intermediate 9 5 Thu, 27 Apr
43 Discovery tools for Government data analytics    
Venkateswaran M (@venkateswaranm) Crisp talk for Data in Government track Intermediate 8 4 Tue, 25 Apr
44 Autonomous Grid using Machine Learning
Charan Puvvala (@charanpuvvala) Full talk for data engineering track Intermediate 6 2 Tue, 25 Apr
45 Optimising Model performance using automated ML pipeline for predicting purchase propensity @ Fractal Analytics    
PadmaCh (@padmach) Full talk for data engineering track Advanced 34 6 Tue, 25 Apr
46 Application of machine learning in oil and gas industry    
Priyanka Raghavan (@priyankaraghavan) Crisp talk for data engineering track Beginner 14 3 Tue, 25 Apr
47 Application of AI in e-commerce industry from product search to customer satisfaction
Dr Amit Garg (@garg78) Crisp talk for data engineering track Intermediate 26 4 Sat, 22 Apr
48 Learning representations of text for NLP  
Anuj Gupta (@anujgupta82) Workshops Intermediate 37 3 Wed, 19 Apr
49 Big Data Computations: Comparing Apache HAWQ, Druid, Google Spanner and GPU Databases    
Vijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran) Full talk for data engineering track Intermediate 6 3 Tue, 18 Apr
50 Working with Apache Spark in Eta
Jyothsna Srinivas (@jyothsnasrinivas) Full talk for data engineering track Intermediate 18 1 Sun, 16 Apr
51 ML For Personalization At Scale @ Nearbuy    
ankit kohli (@ankitko) Full talk for data engineering track Advanced 23 2 Wed, 12 Apr
52 Credit where Credit is due: Using data science to lend to customers without a credit history    
Vanitha DSilva (@vanithadsilva) Crisp talk for data engineering track Intermediate 16 4 Tue, 11 Apr
53 micro-ATMs: The what, the why and the how    
Vanitha DSilva (@vanithadsilva) Full talk in Payment Analytics track Intermediate 15 4 Tue, 11 Apr
54 Machine Learning Applications in Cisco Spark Collaboration SaaS
Narayanan Subramaniam (@narayanan-subramaniam) Crisp talk for data engineering track Intermediate 1 2 Sat, 8 Apr
55 How to engineer a personalization system that can handle Paytm scale
Harinder Takhar (@harindertakhar) (proposing) Full talk for data engineering track Advanced 11 2 Tue, 4 Apr
56 How Paytm uses k8s for global expansion
Pranshu Saxena (@pranshus) Full talk for data engineering track Intermediate 3 6 Tue, 4 Apr
57 Large scale business stats aggregation using Kafka    
Vinothkumar Raman (@vinothkumarraman) Full talk of 40 mins duration Intermediate 22 2 Thu, 30 Mar
58 Blockchain for business and government    
Mani Madhukar (@manimadhukar) Crisp talk for Data in Government track Beginner 4 5 Mon, 20 Mar
59 Streaming for life, universe and everything using Confluent Platform
Aastha Rai (@aastha0304) Crisp talk for data engineering track Intermediate 6 4 Tue, 14 Mar