Last updated on : 20th October, 2019
- Presented my ACM WebSci 2019 paper titled “Understanding Brand Consistency from Web Content” at the “Out-of-India” track of India HCI 2019 [Slides]
- CNeRG Reading Group talk on 17th October 2019, where I presented the AAAI 2018 paper titled “Weakly Supervised Induction of Affective Events by Optimizing Semantic Consistency”[Slides]
In the previous blog, we discussed some points to remember while preparing for a technical or research presentation. Especially when you have very less amount of time to spare.
From personal experience in academia
Over the last 2.5 years of my MS degree, both as part of my coursework as well as my research curriculum, I gave some presentations, which I am going to share with you in verbatim. After a great deal of advice and feedback from my seniors and my supervisors, I was able to identify the points of a technical presentation I was blatantly overlooking previously.
You can find the slides in the Github repo containing some of the presentations I had personally prepared and presented in IIT Kharagpur. Please note that I had not made any modifications or polishing whatsoever after delivering it. So, kindly consider the rough edges :).
The presentations are ordered in terms of oldest to recent.
Presentations made by me
1. An article from the reputed Science magazine :
The spread of true and false news online, published in Science (March 2018 issue). In this presentation prepared by me and Amrith Krishna Da(a Ph.D. scholar, CSE, IIT Kharagpur), we presented the above article. [PPT]
2. My 1st conference paper presentation
My first conference paper was “Understanding Email Interactivity and Predicting User Response to email” and went to present it at Second International Conference on Computational Intelligence, Communications, and Business Analytics (CICBA) 2018 organised at Kalyani Government Engineering College, West Bengal, India.
Here, they already provided a presentation template from beforehand which also included the organisation of the slides.
3. Reading Group (internal) talk at IIT Kharagpur
Here, I introduce the topic of semi-supervised deep learning techniquesa and present a NIPS 2017 paper in this domain titled “Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results”
4. My own compilation for a Research panel discussion:
Semi-supervised Learning techniques and Active Learning [PPT]
I have only provided my segment, which was a part of a panel discussion covering a broader topic titled Leveraging Unlabeled Data and Environment Access for ML. In the discussion panel, we also covered recent literature in Transfer learning, Zero-shot learning, Reinforcement Learning(with different variants) and finally, Imitation Learning.
The following papers were discussed :
4.1 Semi-supervised learning :
Estimating Accuracy from Unlabelled Data, NIPS 2017
4.2 Reinforcement learning
4.3 Transfer, multi-task and few shot learning
One Shot Imitation Learning , NIPS 2017
When will You Arrive, Estimating Travel Time Based on Deep Neural Networks, AAAI 2018 (Multi-task Learning)
Deep contextualized word representations (Elmo) NAACL, 2018 ]
High-risk learning: acquiring new word vectors from tiny data EMNLP 2017 (short paper)
5. Reading Group (internal) talk at IIT Kharagpur [Slides]
I and Bidisha Di presented the AAAI 2018 paper titled “Weakly Supervised Induction of Affective Events by Optimizing Semantic Consistency” in the Reading Group of our research group on 17th October, 2019.
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