Network Science and Technology Center
The Network Science and Technology (NEST) Center is focused on the fundamental research and engineering of natural and technological networks, ranging from social and cognitive networks to computer networks.
The Network Science and Technology (NEST) Center is focused on the fundamental research and engineering of natural and technological networks, ranging from social and cognitive networks to computer networks.
The Rensselaer-IBM Artificial Intelligence Research Collaboration (AIRC), a member of the IBM AI Horizons, is dedicated to advancing the science of artificial intelligence and enabling the use of AI and machine learning in research investigations, innovations, and applications of joint interest to both Rensselaer and IBM.
Dr. Morgan has spent over forty years doing what is now called data analytics, much of it on big data sets in remote sensing and image analysis. He has conducted data acquisition, processing and analysis research for a variety of public and private organizations in oil and gas exploration, medical imaging, non-destructive testing and radio astronomy.
Multi-way (tensor) data arises in many applications such as seismic data interpolation, hyperspectral imaging, higher order web link analysis, face recognition, EEG and fMRI data analysis, and so on. To explore the intrinsic structure of the multi-way data, people treat the data in higher-order format instead of simply reshaping it into a vector, and formulate the problems to tensor optimization problems. In this talk, I will utilize the idea of "divide and conquer" and give different forms of block coordinate descent methods to solve these problems.
Despite the many amazing applications of statistics, machine learning, and visualization in industry, many attempts at doing "data science" are anything but scientific. Specifically, data science processes often lack reproducibility, a key tenet of science in general and a precursor to having true collaboration in a scientific (or engineering) community.
YouTube is consistently one of the most popular linked-to destinations across online platforms, has been blamed for promoting radicalization pathways through its recommendations, and has been used by foreign entities for political manipulation. While recent work has started to investigate YouTube’s role in these issues, open questions remain about YouTube’s ideological distribution, efficacy of its moderation, and its role in propagating disinformation.
The proliferation of social media has given rise to widespread study and speculation about the impact of digital technologies on politics, activism, and social change. Key among these debates is the role social media play in shaping the contemporary public sphere, and by proxy, democracy in the US and around the world. Maligned by some as “slacktivism,” I will argue social computing platforms such as Twitter create unique opportunities for traditionally excluded voices to challenge the terms of public debate.
There are now thousands of online social and commercial platforms available on the web. Yet, many of these face specific challenges causes by malicious actors such as trolls on Slashdot and Twitter, bots on Twitter, vandals on Wikipedia, sockpuppets in online discussion forums, and review fraud on e-commerce sites. In this talk, I will quickly provide some examples of the challenges caused by such malicious actors and then focus on two specific case studies.