Of the Community, By the Community, For the Community

One of the unique features of The Fifth Elephant (and HasGeek events in general) is the community’s defining role. The speakers, the curators and the attendees are all from the same community.

Anyone is welcome to propose a session on HasGeek Funnel. Participants who have purchased conference tickets will vote on session proposals. The Editorial Panel steering The Fifth Elephant 2014 will also vote on submissions and balance the community voting. The Programme Committee consists of data analysts and big data practitioners.

Proposal submissions are reviewed on the basis of use cases, how a problem was solved, or why a particular technology and/or approach was adopted for solving the problem. Proposers can refer to open source technologies and tools available for storage, analytics and visualisation in their submissions.

Status: Proposal submissions closed

View Funnel Submissions

The Programme Committee

This year’s programme committee boasts of experience and expertise from different spectrums of Big Data — practitioners working on storage and cloud computing as well as architects and technologists working on analytics and business intelligence.

  • Vinayak Hegde

    Helpshift

    @vinayakh

    Vinayak is an early adopter of technologies having worked across diverse and complex computer systems including embedded systems, networking, large-scale distributed systems and data-processing systems. He has more than a decade of experience in hardcore product development & software/deployment architecture.

    In prior to the work as VP Engineer at Helpshift, he has experience as Lead Architect/Manager at InMobi, Architect at Akamai Technologies, Software Engineer (Contract) at Microsoft India R&D, and as Development Lead at Aparna Web Services India Ltd.

    Beyond work, he’s an avid photographer and traveller. Also he posts random thoughts here.

  • Govind Kanshi

    Microsoft

    @govindk

    Govind works at Microsoft Technology Center (MTC) in Bangalore helping customers adopt technology platform, ranging from applied software solutions and processes. He can be usually found ‘learning’ more about ‘how things work’ and demystifying them in pragmatic way. His expertise lies in developing applications and finding/fixing bottlenecks. Data excites him, and terms like startburst and byzantine evoke his curiosity.

    Outside work, food, books and movies, travel keeps him busy. He blogs occasionally.

  • Shailesh Kumar

    Google

    Dr. Shailesh Kumar is a Member of Technical Staff at Google, Hyderabad where he works on Machine Learning, Information Retrieval, Data Mining, and Computer Vision problems for various Google products. Dr. Kumar has over fifteen years of experience in applying and innovating machine learning, statistical pattern recognition, and data mining algorithms to hard prediction problems in a wide variety of domains including information retrieval, web analytics, text mining, computer vision, retail data mining, risk and fraud analytics, remote sensing, and bioinformatics. He has published over 20 conference papers, journal papers, and book chapters and holds over a dozen patents in these areas.

  • Viral Shah

    Co-creator of Julia language

    @Viral_B_Shah

    Viral Shah is a co-creator of Julia Programming language - a high-level, high-performance dynamic programming language for technical computing.

    Viral has been working as senior scientist at Interactive Supercomputing; and then as Manager (Financial Inclusion) at Unique Identification Authority of India, where he designed the policies and the technology behind the Aadhaar-based payments systems for Government payments and the e-KYC platform. He had also co-created Circuitscape.

    Viral has published papers on Julia: A Fast Dynamic Language for Technical Computing, A unified framework for numerical and combinatorial computing and Using circuit theory to model connectivity in ecology, evolution and conservation. He also holds a patent on Methods and apparatus for parallel execution of a process.