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.
Dr. Ameres returned to RPI after a successful career in industry developing multimedia tools and technology in a number of fields. He has developed groundbreaking MIDI and music software, tools for game developers as well as video and audio compression and streaming technology (including over a dozen patents now held by Google) that has become the format of choice on many of the most popular video platforms on the internet.
Ameres completed his M.S. and Ph.D. at RPI while working as Sr Research Engineer at Rensselaer's Experimental Media and Performing Arts Center (EMPAC) where he and collaborators developed "The Campfire", a novel, immersive and interactive visualization system allowing for a unique form of "spatialization" of complex data. He continues to develop applications for The Campfire as an affiliate of Rensselaer's Institute for Data Exploration and Analytics (IDEA).
Fun facts: Ameres' family connection to RPI goes back to the class of 1918 and includes 6 alumni of the Institute (so far)! Coincidentally, Ameres' high school best friend is a direct descendent of none other than Stephen Van Rensselaer himself!
BS Computer and Systems Eng., RPI 1988 MS Computer and Systems Eng., RPI 2011 PhD Cognitive Science, RPI 2018
Focus AreaVideo Game Engines, Graphics and Audio Programming, Data Visualization
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.
The Defense Advanced Research Projects Agency (DARPA) was established in 1958 to prevent strategic surprise from negatively impacting U.S. national security and create strategic surprise for U.S. adversaries by maintaining the technologicalsuperiorityoftheU.S.military. Tofulfillitsmission,theAgencyreliesondiverseperformerstoapply multi-disciplinary approaches to both advance knowledge through basic research and create innovative technologies that address current practical problems through applied research.