Conference: KDD 2021
Organization: Alejandro Jaimes (Dataminr) and Joel Tetreault (Dataminr)
Contact Email: ajaimes@dataminr.com | jtetreault@dataminr.com
Date : August 14 or 15, 2021 (tbd)
Venue : Singapore
The amount of public data being generated on a daily basis has grown exponentially in the last few years and continues to increase at incredible speed. Most of this data is unstructured and includes text in different formats, in different languages, from many different sources; images, video, audio, and data from sensors. A lot of that data contains information about events happening all over the world, many of which require emergency response. Detecting events in public data, in real time, is therefore critical in many applications - from getting information to first responders as quickly as possible, to creating situational awareness in such emergency situations, as getting the right information to the right places as quickly as possible is critical in saving lives. When an event is ongoing, information on what is happening can be critical in making decisions to keep people safe and take control of the particular situation unfolding. First responders have to quickly make decisions that include what resources to deploy and where.
Fortunately, in most emergencies, people use social media to publicly share information. At the same time, sensor data is increasingly becoming available. In order to do this, efficient computational approaches must detect and deliver the right information to the right destination. This tutorial will cover techniques at the state-of-the art to detect events in real-time from large-scale heterogeneous sources. We will focus on NLP, Computer Vision, and Anomaly Detection techniques. We will give specific examples and discuss relevant future research directions in Machine Learning, NLP, Computer Vision and other fields relevant to real-time event detection. We will also discuss applications of event detection.
Target audience and prerequisites for the tutorial (e.g. audience expertise)
The tutorial is geared towards research scientists and practitioners who have general knowledge of Machine Learning concepts and Deep Learning.
Alejandro Jaimes is Chief Scientist & SVP of AI at Dataminr. Alex is a scientist with 15+ years of intl. experience in research (Columbia U., KAIST) and product impact at scale (Nauto, DigitalOcean, Yahoo, Telefónica, IDIAP-EPFL, Fuji Xerox, IBM, Siemens, and AT&T Bell Labs) in the USA, Japan, Chile, Switzerland, Spain, and South Korea. He has published 100+ technical papers in top-tier conferences and journals in diverse topics in AI and has been featured widely in the press (MIT Tech review, CNBC, Vice, TechCrunch, Yahoo! Finance, etc.). He has given 100+ invited talks all over the world, incl. talks at the AI for Good Global Summit (UN HQ, Geneva), the Future of Technology Summit, several O’Reilly conferences (AI, Strata, Velocity), the Deep Learning Summit (Re-Work), Tech Open Air, and Stanford, Cornell, & Columbia Universities. Alex is also a mentor in the Endeavor Network (which leads the high-impact entrepreneurship movement around the world), and was an early voice in Human-Centered AI (Computing). Alex's technical work focuses on mixing qualitative and quantitative methods to gain insights into user behavior and design, delivering data-driven technical solutions for product innovation. He’s been a professor (KAIST), and an executive at Yahoo, and at several startup companies. He holds a Ph.D. and an M.S. from Columbia University. He’s chaired multiple workshops at KDD.
Joel Tetreault is Senior Director of Research at Dataminr, a company that has raised over $1B in capital investment, and provides updates on breaking events across the world in real-time. His background is in AI, specifically Natural Language Processing and Machine Learning, and using techniques from those fields to solve real-world problems such as automatic essay scoring, grammatical error correction, hate speech detection, ranking user comments and dialogue systems, among others. Prior to joining Dataminr, he led research groups at Grammarly, Nuance and Educational Testing Service, and was a Senior Research Scientist at Yahoo Labs. Joel recently finished a six-year stint as NAACL Treasurer and was a long-time organizer of the Building Educational Application workshop series (10+ years) as well as organized workshops on Abusive Language, Metaphor and Event Detection. He was a program chair for ACL 2020. He also organized a tutorial at COLING on Grammatical Error Correction.