29 July 2017, Bangalore
Status: Open for feedback

About AnthillInside:

In 2016, The Fifth Elephant branched into a separate conference on Deep Learning. Anthill Inside is the new avataar of the Deep Learning conference.
Anthill Inside attempts to bridge the gap bringing theoretical advances closer to functioning reality. Proposals are invited for full length talks, crisp talks and poster/demo sessions in the area of ML+DL. The talks need to focus on the techniques used, and may be presented independent of the domain wherein they are applied.
We also invite talks on novel applications of ML+DL, and methods of realising the same in hardware/software.
Case studies of how DL and ML have been applied in different domains will continue to be discussed at The Fifth Elephant.


Topics: we are looking for talks covering the following:


Anthill Inside is a two-track conference:

We are inviting proposals for:

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 or last year at Deep Learning.
  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.

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.

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 to start evaluating your proposal.

Selection Process Flowchart

You can check back on this page for the status of your proposal. We will notify you if we either move your proposal to the next round or if we reject it. 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.

A speaker is NOT confirmed a slot unless we explicitly mention so in an email or over any other medium of communication.

There is only one speaker per session. Entry is free for selected speakers.

We might contact you to ask if you’d like to repost your content on the official conference blog.

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:


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

Please note, we will not evaluate proposals that do not have a slide deck and a video in them.

Confirmed sessions

# Speaker Section Level +1 Submitted
1 Deep Reinforcement Learning : A tutorial
Vikas Raykar (@vikasraykar) (proposing) Full talk Beginner 1 0 Tue, 25 Jul
2 OTR - DL and image
Sandhya Ramesh (@sandhyaramesh) (proposing) Full talk Beginner 1 0 Sat, 22 Jul
3 Apache MXNet, a highly memory efficient deep learning framework  
Girish Patil (@bookworm) Crisp talk Intermediate 1 0 Sat, 22 Jul
4 AI in self driving vehicles - a practitioner's perspective
Saad Nasser (@sdnssr) Full talk Beginner 1 0 Sat, 22 Jul
5 AI on IA
Mukesh Gangadhar (@mukgbv) Workshop Intermediate 1 0 Tue, 18 Jul
6 AI: Unleashing the next wave
Rebanta Dutta (@anthillevent) (proposing) Full talk Intermediate 1 0 Mon, 17 Jul
7 Panel on product and AI
Vijay Gabale (@vijaygabale) Birds of a Feather (BOF) session Beginner 4 0 Fri, 14 Jul
8 Keep Calm and Trust your Model - On Explainability of Machine Learning Models    
Praveen Sridhar (@psbots) Full talk Intermediate 2 0 Mon, 10 Jul
9 Identifying Urban Makeshift Communities using satellite imagery and geo-coded data    
Akarsh Zingade (@akarsh-zingade) Crisp talk Intermediate 18 2 Mon, 10 Jul
10 How Deep is Deep Learning?    
Amar Lalwani (@amar1707) Crisp talk Intermediate 3 0 Sun, 9 Jul
11 Practical Deep Learning
saurabh agarwal (@saurabh-agl) (proposing) Workshop Intermediate 2 0 Thu, 22 Jun
12 Adversarial attacks on deep learning models    
Konda Reddy Mopuri (@mkreddy) Full talk Intermediate 3 1 Sat, 10 Jun
13 Synthetic Gradients – Decoupling Layers of a Neural Nets  
Anuj Gupta (@anujgupta82) Full talk Intermediate 6 0 Fri, 9 Jun
14 PyTorch Demystified, Why Did I Switch    
Sherin Thomas (@hhsecond) Full talk Beginner 8 3 Sun, 28 May
15 Hitchhiker’s Guide to Generative Adversarial Networks (GANs)  
Ramanan Balakrishnan (@ramananbalakrishnan) Full talk Intermediate 14 4 Sat, 29 Apr
16 Unsupervised and Semi-Supervised Deep Learning for Medical Imaging    
Kiran Vaidhya (@kiranvaidhya) Full talk Advanced 15 0 Sat, 29 Apr
17 Learning representations of text for NLP  
Anuj Gupta (@anujgupta82) Workshop Intermediate 27 4 Thu, 20 Apr
18 Saving the Princess with Deep Learning    
Navin (@navinpai) Crisp talk Intermediate 3 1 Mon, 10 Apr

Unconfirmed proposals

# Speaker Section Level +1 Submitted
1 Deep Learning approaches for Named Entity Recognition    
Vijay Ramakrishnan (@vijay120) Crisp talk Intermediate 1 2 Thu, 13 Jul
2 Getting Started with GPU Accelerated Deep Learning  
Gaurav Goswami (@gauravgoswami) Crisp talk Beginner 1 2 Mon, 10 Jul
3 Deep learning with limited data
Aman Neelapa (@aman42) Crisp talk Intermediate 6 0 Wed, 5 Jul
4 Augmenting Solr’s NLP Capabilities with Deep-Learning Features to Match Images    
Kumar Shubham (@kumar-shubham) Crisp talk Intermediate 3 0 Wed, 28 Jun
5 CNN for NLP    
Malaikannan Sankarasubbu (@malai) Full talk Intermediate 34 1 Fri, 23 Jun
6 Leonardo Machine Learning Foundation - Adding Intelligence to your Enterprise Business    
sainath v (@sapcloudengineers) Crisp talk Beginner 2 0 Thu, 22 Jun
7 Application Dependency Data Performance Mapping tool - Dynatrace    
Chandrish M (@chandrish) Crisp talk Beginner 2 0 Thu, 22 Jun
8 Developing agents with Deep Reinforcement learning    
Satwik Kansal (@satwikkansal) Full talk Beginner 1 2 Tue, 20 Jun
9 Neural Machine Translation    
Ashish Mogha (@ashishmogha) Full talk Intermediate 20 0 Mon, 19 Jun
10 Making a Text-Summarizer with Keras
Gur Raunaq Singh (@raunaqsoni) Crisp talk Intermediate 10 2 Mon, 19 Jun
11 Keras: Deep Learning for Python
Fariz Rahman (@farizrahman4u) Full talk Advanced 9 1 Fri, 16 Jun
12 Demystifying Visual Question Answering    
Laksh Arora (@techedlaksh) Full talk Intermediate 19 1 Wed, 14 Jun
13 From RNN to Attention
Sarath R Nair (@s4sarath) Full talk Intermediate 1 3 Mon, 12 Jun
14 Neural Stack: Augmenting Recurrent Neural Networks with Memory  
SATYAM SAXENA (@sam89) Full talk Intermediate 3 3 Sun, 11 Jun
15 Decoding Neural Image Captioning    
Sachin Kumar (@sachinkmr) Full talk Intermediate 36 1 Sat, 10 Jun
16 Highway Networks and ResNet : A deeper approach towards Deep Learning .  
Vasudev Singh (@vasu-dev) Full talk Intermediate 20 0 Sat, 10 Jun
17 Deep Learning Applications: A hands-on approach  
Shubham Dokania (@shubhamdokania) Workshop Intermediate 52 5 Sat, 10 Jun
18 The Importance of Knowing What We Don’t Know - Bayesianism and Deep Learning    
Abhijeet Katte (@abhik24) Crisp talk Beginner 22 2 Sat, 10 Jun
19 Supervised-machine-learning without coding
Rajesh Gudikoti (@ragudiko) Full talk Beginner 1 4 Wed, 7 Jun
20 Object Classification in 3D: Working with LiDAR point clouds    
Akbar Ladak (@bluplaneter) Crisp talk Intermediate 4 3 Wed, 7 Jun
21 Taming Convolution Neural Networks for Image Recognition    
saurabh agarwal (@saurabh-agl) Full talk Intermediate 14 0 Sun, 30 Apr
22 Retail Loss Prevention based on Deep Learning
Subramanya Mayya (@smayya) Full talk Intermediate 6 1 Sun, 30 Apr
23 Deep Type - deep convolutional neural networks for style transfer in typography
irfan basha sheik (@sheikirfanbasha) Full talk Intermediate 2 0 Sun, 30 Apr
24 Deep learning based OCR engine for the Indus script    
Satish Palaniappan (@satishpalaniappan) Crisp talk Intermediate 3 0 Sat, 29 Apr
25 Typography detection using Deep Convolutional Neural Networks    
Pallavi Ramicetty (@pallaviramicetty) Crisp talk Intermediate 2 4 Sat, 29 Apr
26 KERAS: A Versatile Modeling Layer For Deep Learning  
Ananth Krishnamoorthy (@akrishnamoorthy) Full talk Intermediate 5 0 Thu, 27 Apr
27 Malware Detection and Pattern Recognition using Deep Learning  
Vidyasagar Nallapati (@dumbyoda) Crisp talk Intermediate 1 2 Thu, 27 Apr
28 Information Retrieval using Deep Learning  
shashank gupta (@shash273) Full talk Intermediate 9 2 Wed, 26 Apr
29 Deep Learning with TensorFlow
Abdul Muneer (@abdul-muneer) Workshop Intermediate 7 0 Wed, 26 Apr
30 Streaming video analytics using deep learning on large scale surveillance data @ Fractal Analytics    
abhineet verma (@averma) Full talk for data engineering track Advanced 25 2 Tue, 25 Apr
31 Named Entity Recognition using DL methods
haridas n (@haridasn) Full talk Intermediate 7 1 Mon, 24 Apr
32 Introduction to Bounding Box Neural Networks  
Anil Hebbar (@ahebbar) Full talk Intermediate 2 2 Mon, 24 Apr
33 Deep learning for feature extraction from incident data  
Arthi Venkataraman (@arthi) Crisp talk Intermediate 6 4 Wed, 12 Apr
34 Understanding Neural Networks with Theano  
Jaidev Deshpande (@jaidevd) Workshop Intermediate 2 2 Mon, 10 Apr