[CSEE Talk] talk: Probabilistic Approach to Modeling Socio-Behavioral Interactions, 12pm Thr. 3/24

[Tim Finin]

                          UMBC CSEE Colloquium

   A Probabilistic Approach to Modeling Socio-Behavioral Interactions

           Arti Ramesh, University of Maryland, College Park

                 Noon Thursday, 24 March 2016, ITE325b


The vast growth and reach of the Internet and social media have led to
a tremendous increase in socio-behavioral interaction content on the
web. The ever-increasing number of online interactions has led to a
growing interest to understand and interpret online communications to
enhance user experience. My work focuses on building scalable
computational methods and models for representing and reasoning about
rich, heterogeneous, interlinked socio-behavioral data. In this talk,
I focus on one such emerging online interaction platform---online
courses (MOOCs). I develop a family of probabilistic models to
represent and reason about complex socio-behavioral interactions in
the following real-world problems: 1) modeling student engagement, 2)
predicting student completion and dropouts, 3) modeling student
sentiment in discussion forums toward various course aspects (e.g.,
academic content vs. logistics) and its effect on their course
completion, and 4) designing an automatic system to predict
fine-grained topics and sentiment in online course discussion
forums. I demonstrate the efficacy of these models via extensive
experimentation on data from twelve Coursera courses. These methods
have the potential to improve learning and teaching experience of
online education participants and focus limited instructor resources
to increase student retention.

Arti Ramesh is a PhD candidate at University of Maryland, College
Park. Her primary research interests are in the field of machine
learning and data science, particularly on probabilistic graphical
models. Her advisor is Prof. Lise Getoor. Her research focuses on
building scalable models for reasoning about interconnectedness,
structure, and heterogeneity in socio-behavioral networks. She has
published papers in peer-reviewed conferences such as AAAI and
ACL. She has served on the TPC for ACL workshop on Building
Educational Applications and has served as a reviewer for notable
conferences and journals such as NIPS, Social Networks and Mining, and
Computer Networks. She has won multiple awards during her graduate
study including the outstanding graduate student Dean's fellowship
2016, Dean’s graduate fellowship (2012-2014), and yahoo scholarship
for grace hopper. She has worked at IBM research and LinkedIn during
her graduate study. She received her Masters in Computer Science from
University of Massachusetts, Amherst.

Host: Nilanjan Banerjee