-
Notifications
You must be signed in to change notification settings - Fork 1
/
talk.json
197 lines (197 loc) · 19.3 KB
/
talk.json
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
[
{
"about_speaker": "Siddarth Venkatraman is a second year CSE student. In 2017, he joined Project Manas(the autonomous car student project), and since then AI has been what he has devoted most of my time towards. In the past year and a half, Siddarth has worked on various projects relating to ML. Some of these are road lane detection, object segmentation, image reconstruction and classification, sentiment analysis as well as small models made for various Kaggle competitions. He has also ventured briefly into research on ensemble deep learning, RL safety, and am currently working with faculty in MIT to build an automated Hypertension Retinopathy model. \nSiddarth dedicates his time to ML simply because the very nature of the field makes it intensely satisfying and exciting.",
"begin_time": "201810281545",
"description": "The talk will start of with a brief overview of the main problem statements in the field of Natural Language processing. Then, the data representation of language which can be usable by ML models is discussed. Word embeddings, and how to build them or use pretrained embeddings in Python. Moving on to Neural Networks and briefly talk about CNN models for NLP before diving into RNN's. LSTM and related memory cells will be briefly discussed, along with their implementation in Keras. Finally, we will go over the state of the art use of Reinforcement Learning for NLP which allows us to use non differentiable language metrics.",
"duration": "30 minutes",
"github": "https://github.com/HyperPotatoNeo",
"image": "https://preview.ibb.co/ketgMV/IMG-20181024-232533-Bokeh-01.jpg",
"linkedin": "https://www.linkedin.com/in/siddarth-venkatraman-59b863157/",
"location": "ICT Seminar Hall 2",
"speaker": "Siddarth Venkatraman",
"speaker_email": "",
"talk_id": "siddvenk",
"title": "Modern approach to NLP using Recurrent Neural Networks",
"type": "Track Two"
},
{
"about_speaker": "Shayantan is a 3rd Year Electrical and Electronics student who takes a keen interest in how humans,try to make machines human via Deep Neural Networks and Artificial Intelligence .Having participated in Google Code In , Summer Of Code for the open source organisations KDE and Libre, he stays active in the open source community and can be found tinkering with his Raspberry Pi during his free time.After discovering Python3's flexibility and it's application in the field of AI , there was no looking back for him.",
"begin_time": "201810281200",
"description": "The speaker will demonstrate and explain a basic motion detection and tracking system for area surveillance using computer vision techniques and follow it up with demonstrating three sets of modules that are to be executed in order to train the AI so that it can recognize N faces and their instances (like photos or selfies from smart phones) which it captures in the camera’s FOV. Finally discussion on Single Shot Detectors and MobileNets. When combined together these methods can be used for super-fast, real-time object detection. The speaker is open to taking all kinds of questions regarding the content and will explain the modules workng and the role of Python and its packages in each of the modules.",
"duration": "30 minutes",
"github": "https://github.com/compilerator",
"image": "https://lh3.googleusercontent.com/3pRbkSG0n8a-vqQoGwLzF9BOfr3Sc8pxkNUQGToeWayXKVsodks0_HlcuN2lNdaKXROGM76PoGDNo9O0WYxcX3ZhKTokt9WqC2wde2RHDZgaG6VxHEhETs584L9tqW4SMNGC12faqQ=w2400",
"linkedin": "http://ww.linkedin.com/in/palshayantan",
"location": "ICT Seminar Hall 2",
"speaker": "Shayantan Pal",
"speaker_email": "[email protected]",
"talk_id": "shayapal",
"title": "Motion Detection,Face Detection and Object Detection using OpenCV",
"type": "Track Two"
},
{
"about_speaker": "Siddhartha is a final year Computer Science student interested in Deep Learning research. He has collaborated with scientists at Google Brain to improve learning mechanisms of neural networks. He also worked with CERN as a Google Summer of Code 2018 student. He loves playing around with new ideas and is here to share.",
"begin_time": "201810281400",
"description": "Artificial intelligence is probably the fastest evolving field these days and it is so for a good reason. With applications ranging from Medical diagnosis to Quantum physics, AI is redefining the boundaries of computer science. The mathematical models that we use to understand the world around us are flawed and the learning algorithms are very brittle. Thanks to Python and a few frameworks, adoption of AI in the industry is prevalent. But, commercial usage without a proper understanding of what's under the hood has direct consequences and the outcome can get ugly. This talk would elaborate on what the problems with AI are and why we're far from the 'intelligence' part of AI.",
"duration": "30 minutes",
"github": "https://github.com/srk97",
"image": "https://drive.google.com/file/d/1nmOPZSp9yxdfOgn6bK3lC0tTt3_cO8Mm/view?usp=sharing",
"linkedin": "https://www.linkedin.com/in/siddhartha-rao-kamalakara/",
"location": "ICT Seminar Hall 2",
"speaker": "Siddhartha Rao Kamalakara",
"speaker_email": "[email protected]",
"talk_id": "srkamal",
"title": "Problems with Deep Learning",
"type": "Track Two"
},
{
"about_speaker": "A second year student at MIT, with significant contributions to various open source projects. Projects on GitHub have crossed over 500 stars and have trended on the main page. Projects are also featured in the official implementations of id3.org (ID3 tags are the audio file data standard for MP3 files). Currently specialising in DevOps and container technology, Lakshay has experience in managing and designing services that are expected to run at scale.",
"begin_time": "201810281700",
"description": "Daemons are background applications in Linux. The talk will be focussed on why it might be necessary to create daemons out of Python applications and how to create & manage daemons out of Python applications.",
"duration": "30 minutes",
"github": "https://github.com/kalbhor",
"image": "https://i.imgur.com/eAbog8H.jpg",
"linkedin": "https://www.linkedin.com/in/lakshaykalbhor",
"location": "ICT Seminar Hall 2",
"speaker": "Lakshay Kalbhor",
"speaker_email": "[email protected]",
"talk_id": "kalbhoro",
"title": "Daemonizing Python Applications",
"type": "Track Two"
},
{
"about_speaker": "Manish Agnihotri is a 4th year CCE student who has researched in the field of Computer Vision and Continual Learning. He is also the co-founder of Research Lab, Manipal's first collaborative research club.",
"begin_time": "201810280930",
"description": "Computer programs that learn to perform tasks also typically forget them very quickly. Continual Learning is being able to train your model in a way that takes into account different tasks and different data distributions at once and is able to retain all that knowledge. This is an important step towards more intelligent programs that are able to learn progressively and adaptively. We will discuss the basics, the current state of the art and the future challenges followed by a demonstration.",
"duration": "30 minutes",
"github": "https://github.com/ambicorp",
"image": "https://preview.ibb.co/jL5g3A/Whats-App-Image-2018-10-24-at-23-05-48.jpg",
"linkedin": "http://www.linkedin.com/in/manish-agnihotri-50b9ab135",
"location": "ICT Seminar Hall 2",
"speaker": "Manish Agnihotri",
"speaker_email": "[email protected]",
"talk_id": "maniagni",
"title": "Continual Learning: Key to Machine Intelligence",
"type": "Track Two"
},
{
"about_speaker": "Shaurya is passionate about learning new skills, and has working knowledge of 30+ programming languages across multiple domains varying from OS development to Web/Application development and now developing Deep Learning solutions. As an expert in neural networks, Shaurya has delivered deep learning solutions for retail sales predictions, customer churn model and user behavior analysis.",
"begin_time": "201810280930",
"description": "Through this talk, Shaurya will showcase the extensive applications of python across various domains with focus in Data Science, Machine Learning and Deep Learning. He will give an insight into Neural Networks, working of CNN, libraries like TensorFlow, Keras, openCV and PIL.",
"duration": "60 minutes",
"github": "https://github.com",
"image": "https://media.licdn.com/dms/image/C5103AQFfJIe1pjsK0A/profile-displayphoto-shrink_800_800/0?e=1545868800&v=beta&t=rCV2nxeZW4KIQ_2MihWmhm9Vj_o0a8seV8MQo0QAP1c",
"linkedin": "https://www.linkedin.com/in/shauryakuchhal/",
"location": "ICT Seminar Hall 1",
"speaker": "Shaurya Kuchhal",
"speaker_email": "[email protected]",
"talk_id": "shauryak",
"title": "Convolution Neural Networks in Keras",
"type": "Track One"
},
{
"about_speaker": "Abhishek is presently working as Deep Learning Scientist at Predible Health.\n\nThey have build state of the art segmentation network for liver and tumour and vessel segmentations.\n\nHe has spoken at Shri Mata Vaishno Devi University at their SFD celebrations and will also be submitting a proposal at PyCon India.\n\nHe has been a constant contributor in the open source world and a regular attendee of PyCon and other conferences every year.",
"begin_time": "201810281200",
"description": "Coming up soon!",
"duration": "60 minutes",
"github": "https://github.com/vibrantabhi19",
"image": "https://avatars3.githubusercontent.com/u/6832471?s=400&v=4",
"linkedin": "https://www.linkedin.com/in/abhishek-kumar-74299887/",
"location": "ICT Seminar Hall 1",
"speaker": "Abhishek Kumar",
"speaker_email": "[email protected]",
"talk_id": "abhikumr",
"title": "Exploring PyTorch to dive into the world of Computer Vision",
"type": "Track One"
},
{
"about_speaker": "Aabir is a researcher, currently at the Tata Institute of Fundamental Research in India. With an interdisciplinary background in engineering, physics, data science and social science, he enjoys tackling big problems at different scales, and is particularly fascinated by the theory of information. While not coding experiments and simulations, he enjoys playing the guitar, discussing philosophy and politics, and traveling.",
"begin_time": "201810281045",
"description": "Data is often high-dimensional - millions of pixels, frequencies, categories. A lot of this detail is unnecessary for data analysis - but how much exactly? This talk will discuss the basic principles and techniques of dimensionality reduction, provide (just a little!) mathematical intuition about how it's done, and use scikit-learn to show you how Netflix uses it to lead you from binge to binge.",
"duration": "60 minutes",
"github": "https://github.com/bakerwho",
"image": "https://www.icts.res.in/sites/default/files/styles/people_thumbnail/public/media/people/images/Aabir-Abubaker-grid-img.jpg?itok=EdyV_fwX&c=7565903ff73648fc7d0eb6f780b8f2d9",
"linkedin": "https://www.linkedin.com/in/aabir/",
"location": "ICT Seminar Hall 1",
"speaker": "Aabir Abubaker Kar",
"speaker_email": "[email protected]",
"talk_id": "aabirkar",
"title": "Dimensionality Reduction with PCA",
"type": "Track One"
},
{
"about_speaker": "Surya is a high schooler from Silicon Valley, California. He has had experience with Machine Learning, Computer Vision and has published a paper titled 'Rapid Autonomous Car Control based on Spatial and Temporal Visual Cues'. He has previously spoken at HAILCon, where he was selected to present on Generative Adversarial Networks, their implementations, variations, and fundamental concepts to understand what they are.",
"begin_time": "201810281045",
"description": "In this talk, Surya will give a background of Reinforcement Learning so that the audience has a basic understanding of the same. This will be followed by the uses and applications of Reinforcement Learning and an introduction to OpenAI Gym. Surya will also talk about the current reaseach opportunities in Reinforcement Learning.",
"duration": "60 minutes",
"github": "https://github.com/dantuluri",
"image": "https://media.licdn.com/dms/image/C5603AQHZ3n1KHOzQKw/profile-displayphoto-shrink_800_800/0?e=1545868800&v=beta&t=xXWffZsiUIULNh4Pp3-KG_zxKkUhTD6J5nP-AT9Z8lA",
"linkedin": "https://www.linkedin.com/in/surya-d/",
"location": "ICT Seminar Hall 2",
"speaker": "Surya Dantuluri",
"speaker_email": "[email protected]",
"talk_id": "surydant",
"title": "Reinforcement Learning",
"type": "Track Two"
},
{
"about_speaker": "Saptak Sengupta is a contributor and maintainer of various open source projects. FOSSASIA, jQuery, Freedom of the Press Foundation and Gitcoin are few organizations under his belt. He is currently working as a Software Developer at Gitcoin. He is also associated with programs like Google Summer of Code, Google Code-In, and Rails Girls Summer of Code as a mentor/supervisor. As an open-source evangelist, he also likes to help out people with programming in general. His core area of dabbling is JavaScript and Python. He has previously given talks in FOSSASIA Summit, FOSSMeet, DevConf India, PyCon India Devsprint and other local meetups.",
"begin_time": "201810281430",
"description": "Open Source Software and Open Source contributors provide for a massive percentage of today's softwares and web and other technical ecosystems. It provides a freedom and global way of contributing to make things better. However, Open Source contributions are mostly driven by intrinsic motivations. This often leads to burn out due to lack of sustainability. Gitcoin provides a solution to help all the wonderful Open Source contributors earn by doing what they do best. Gitcoin is a bountying platform which helps bounty open source issues which now the contributors can work on and also earn and sustain themselves.",
"duration": "60 minutes",
"github": "https://github.com/saptaks",
"image": "https://media.licdn.com/dms/image/C4E03AQF-NrCmMaaEQA/profile-displayphoto-shrink_200_200/0?e=1545868800&v=beta&t=itNqh8SVg2jLZvsWpDleIoFmAGQJ8rKn1kOlPZMb5ZE",
"linkedin": "https://in.linkedin.com/in/saptaks",
"location": "ICT Seminar Hall 1",
"speaker": "Saptak Sengupta",
"speaker_email": "[email protected]",
"talk_id": "saptakse",
"title": "Making Open Source Sustainable",
"type": "Track One"
},
{
"about_speaker": "Sunil has a PhD in Computer Science (NLP and ML Specialization) from Bharathiar University, Coimbatore. He is a AI researcher with about 15 years industry experience. Currently, he works in the capacity of a Sr. Lead Data Scientist with Fidelity Investments, Bangalore. He has published several research papers in Scopus, IEEE journals and is a frequent speaker in various reputed colleges in and around Bangalore. He is an avid coder and has won multiple hackathons. In his spare time, Sunil likes to teach, travel and be on top of learning new advancements in AI.",
"begin_time": "201810281430",
"description": "Often in a business environment when machine learning models are built, just reporting the performance measurements obtained to confirm the goodness of the model may not be enough. The stakeholders generally are inquisitive to understand the 'whys' of the model i.e. What are the factors contributing to the model's performance? In other words, the stakeholders want to understand the causes for the effects. Essentially, the expectation from the stakeholders is to understand the importance of various features in the model and the direction in which each of the variable impacts the model.",
"duration": "60 minutes",
"github": "https://github.com/",
"image": "https://media.licdn.com/dms/image/C5103AQEjDR0kGlStDA/profile-displayphoto-shrink_800_800/0?e=1546473600&v=beta&t=-e-mudMqvNq6WijI23476buRZzHHzQlzknhVv7hAQQE",
"linkedin": "https://www.linkedin.com/in/sunilchinnamgari/",
"location": "ICT Seminar Hall 2",
"speaker": "Sunil Kumar",
"speaker_email": "[email protected]",
"talk_id": "sunilkmr",
"title": "Learning to Interpret Complex Machine Learning Models",
"type": "Track Two"
},
{
"about_speaker": "Ashok is a MIT alumnus, CSE 2010-2014 batch and currently working at Honeywell as a Product Design Senior Engineer where he develops ML based Facial Recognition systems for edge devices. He is the Co-founder and CTO at Zayyon IT Labs which deals in services like Gesture Recognition for gaming devices and smart watches. Ashok has several certifications like Six Sigma Green Belt from Honeywell and Vitualization and Cloud Computing by Carnegie Mellon.",
"begin_time": "201810281545",
"description": "",
"duration": "60 minutes",
"github": "https://github.com/ashokbugude",
"image": "https://media.licdn.com/dms/image/C5103AQGIOTk7fyVxbA/profile-displayphoto-shrink_800_800/0?e=1545868800&v=beta&t=OX7U7rBJk5VQPs9OGRAPpPp57kaXoWsT-raFBn1fKw4",
"linkedin": "https://www.linkedin.com/in/ashokbugude/",
"location": "ICT Seminar Hall 1",
"speaker": "Ashok Bugude",
"speaker_email": "[email protected]",
"talk_id": "ashokbug",
"title": "Face recognition using Machine Learning and Deep Neural Networks",
"type": "Track One"
},
{
"begin_time": "201810281700",
"about_speaker": "Vinayak is a Natural Language Understanding researcher at UMass Amherst where he is a graduate student working towards a Masters degree. A proud alumnus of Manipal, Vinayak has worked on cutting-edge NLP research in academia at the Indian Institute of Science as well as in the industry at Samsung Research America & Lexalytics. His research interests include latent semantic frames, conversation agents and word sense induction which he is pursuing at the IESL lab at UMass. Vinayak has also collaborated and published with the human-computer interface group at Stanford and is an active member of the MIT Media Lab's innovation in medicine community in India. He has published multiple peer-reviewed papers and has an AI patent under review at the US PTO.",
"description": "This talk will briefly introduce word embeddings that have become a standard representation in natural language processing. We will discuss the shortcomings of universal embeddings like word2vec and Glove and what new directions are being explored to overcome their disadvantages. The talk will give details about the new ELMo embedding model and give a general overview of how, when, and where should they be used in your NLP projects. Finally the talk will give a sneak peek into the work happening at UMass Amherst to overcome some of the problems encountered in the field.",
"duration": "60 minutes",
"github": "https://github.com",
"image": "http://vinayakmathur.com/wp-content/uploads/2016/08/cropped-vin-1-300x300.jpg",
"linkedin": "https://www.linkedin.com/in/vin101/",
"location": "ICT Seminar Hall 1",
"speaker": "Vinayak Mathur",
"speaker_email": "[email protected]",
"talk_id": "vinayakm",
"title": "Evolution of Word Embeddings for NLP tasks",
"type": "Track One"
}
]