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.
We are looking for application level and tool-centric talks and tutorials on the following topics:
- Deep Learning
- Text Mining
- Computer Vision
- Social Network Analysis
- Large-scale Machine Learning (ML)
- Internet of Things (IoT)
- Computational Biology
- ML in healthcare
- ML in education
- ML in energy and ecology
- ML in agriculrure
- Analytics for emerging markets
- ML in e-governance
- ML in smart cities
- ML in defense
The deadline for submitting proposals is 30th April 2016
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.
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
The Fifth Elephant will be held at the NIMHANS Convention Centre, Dairy Circle, Bangalore.
For more information about speaking proposals, tickets and sponsorships, contact email@example.com or call +91-7676332020.
Knowledge Inference: Estimating how much the student knows
Very high student-teacher ratios, lack of infrastructure and other socio-economic issues have affected quality and accessibility of education significantly. Moreover, Education can also benefit from the potential and promises of technology (particularly AI), which has already transformed our lives in many aspects. An Intelligent Tutoring System (ITS) is a computer system which enables learning in some domain of study. By this abstract definition, an ITS is supposed to possess knowledge about the domain, knowledge about the learner and knowledge about the teaching strategies.
Enhancing student knowledge being the primary goal of education, it is important to be able to measure the student knowledge. If we can measure it, we would know whether we are making it any better. Of course, if we can measure it, we can make automated pedagogical decisions and also inform instructors and other stakeholders about it.
This talk is about techniques to model students’ changing knowledge state during the process of skill (knowledge) acquisition, also known as Knowledge Tracing. This model enables the system to maintain the estimate of the probability that the student has mastered the concepts. Based on these probability estimates, the system individualizes the learning path and provides assistance as necessary.
The talk will mainly focus on the following topics:
i) Modelling of Knowledge, KC (Knowledge Component) Models
ii) Bayesian Knowledge Tracing (BKT): A classical approach to Knowledge Inference and Tracing
iii) Variants of BKT
iv) Other models like PFA(Performance Factor Analysis), IRT(Item Response Theory) and other ML models which use all the unutilized features.
Responsible for Research and Development of the algorithms to make funtoot (Intelligent and Adaptive personal tutor for K-12 Education) intelligent and powerful using the tools of AI & ML.
- This is a talk at RMIT (Ramanujan, Math & IT) 2014, where I presented my research thesis work. https://youtu.be/YJ1l6DLLK34
- A talk at Sri Kumaran Children’s Home for the students, parents and teachers about AI & ML. https://youtu.be/fWUYxwv36Jk