(NEW YORK)–Columbia Data Science Day, which is run by Columbia Data Science Institute, brought out some of the top minds from the University, and across the country, to discuss how Artificial Intelligence (A.I.) and Machine Learning could solve some of the pressing problems of our day.
Columbia Data Science Day was a full day opportunity for Columbia students and professors to present their latest research to industry leaders and the general public, and to exchange ideas for using data science for the greater public good.
The day kicked off with panel discussions like Data Science for Health Discovery, and Climate + Finance: Use of Environmental Data to Measure and Anticipate Financial Risk.
By late morning the room at Lerner Hall became more crowded as the discussion turned to Machine Learning: The Good, The Bad and The Law. Professor David Blei of Columbia Statistics & Computer Science discussed Designing a Model to Show How Customers Choose Products.
This was followed by Junfeng Yang, Associate Professor of Computer Science discussing Effective Testing and Verification of Deep Learning Systems, and wrapped up by Joshua Mitts, Associate Professor of Law on the topic of Effect of Cybersecurity Breaches on Financial Markets.
After this the room was near capacity as keynote speaker Diane Greene, the CEO of Google Cloud, came on to discuss the promise of data science technologies as Big Data, artificial intelligence and cloud computing converge.
By this point Columbia Data Science Day was already a great success with a number of great topics and insight one could only find from the insightful minds at Columbia – but the best was yet to come!
After short lunch break, Lee Bollinger, the President of Columbia University, topped off the panel events with a fire side chat with Jeannette Wing, who heads Columbia’s Data Science Institute, to discuss threats to American democracy from the polarization of social media, whether the very notion of democracy may be changing because of it, and how privacy and first amendment issues clash in this new world.
Obviously the subject of Facebook and the recent controversy with Cambridge Analytica came up as Mr. Bollinger was a great panelist on subject of Big Data, privacy, and possible government regulations to come based on his sharp knowledge of 1st Amendment law.
The best part of day by far was the open demo and poster board session where Columbia students, and professors, got to present their latest research to industry leaders and the general public, and to addressed ideas for using data science for the greater public good.
On the conference floor you had A.I. and Machine Learning projects focused on financial risk models for institutional investors, climate change analysis, drug and gene therapy development, smart cities, virtual reality, user interface, and medical diagnostics just to name a few.
Tom Bustamante, the Founder and CEO of AI VentureTech, Inc. commented, “Once again Columbia really showcased what brings this university to the fore front in innovation, and technology development. Meeting some of the next generations brightest minds, and how they look to use A.I. and Machine Learning to solve major problems of the day was not only encouraging, but real fun for the nerdy type interested in a view of tomorrow. What Columbia does to nurture these new innovations by assisting them in taking these ideas to market through such departments as Columbia Technology Ventures shows Columbia’s real commitment to its students, and developing technologies open to collaboration with outside partners. It was a great event, and we look forward to attending more of these in the future, and possibly working with some of these technologies to help bring them to market.”
About Columbia Data Science Institute
The Data Science Institute at Columbia has a three-part mission that encapsulates the great promise this new field has to improve the quality of life for all. Our mission is:
– To advance the state-of-the-art in data science;
– To transform all fields, professions, and sectors through the application of data science;
– To ensure the responsible use of data to benefit society.
The Data Science Institute at Columbia University is training the next generation of data scientists and developing innovative technology to serve society. With over 250-affiliated faculty working in a wide range of disciplines, the Institute seeks to foster collaboration in advancing techniques to gather and interpret data, and to address the urgent problems facing society. The Institute works closely with industry to bring promising ideas to market. http://datascience.columbia.edu/
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