using semantic data dictionaries to semantically represent
and integrate several publicly available datasets. His
current work includes the application of deductive and
abductive reasoning techniques over linked health data.
This research is being applied as part of the Health Empowerment by Analytics, Learning, and Semantics project to
help explain the actions of physicians, as well as adverse
drug reactions of patients, in the context of chronic diseases
such as diabetes.
Oshani Seneviratne is the director of health data research
at the Institute for Data Exploration and Applications at
the Rensselaer Polytechnic Institute. Seneviratne’s research
interests lie at the intersection of decentralized systems
and health applications. At Rensselaer Institute for Data
Exploration and Applications, Seneviratne is involved in
the Health Empowerment by Analytics, Learning, and
Semantics project, and leads the Smart Contracts Augmented
with Analytics Learning and Semantics project. Seneviratne
obtained her PhD in computer science from the Massachusetts Institute of Technology under the supervision of Sir
Tim Berners-Lee. Before Rensselaer, Seneviratne worked at
Oracle specializing in distributed systems, provenance, and
healthcare-related research and applications.
Daby Sow is a principal research staff member at IBM
Research. Since August 2017, he has managed the Biomedical
Analytics and Modeling group, part of the IBM Research
Center for Computational Health. In this role, he is leading
a team of AI scientists developing novel AI and machine
learning solutions for various open healthcare research
problems. These problems range from modeling the pro-
gression of complex chronic conditions, to pharmacovigi-
lance with the development of signal detection algorithms
for early adverse drug reaction detection from real-world
evidence data (electronic health records, claims, spontaneous
reporting systems) and the generation of time-varying treat-
ment strategies using data collected during clinical prac-
tice. Sow is an alumni of Columbia University, where he
received a PhD degree in electrical engineering in 2000.
Biplav Srivastava is a distinguished data scientist and
master inventor at IBM’s Chief Analytics Office. With over
two decades of research experience in AI, services computing
and sustainability, most of which was at IBM Research,
Biplav is also an Association for Computing Machinery Distinguished Scientist and Distinguished Speaker, and an Institute of Electrical and Electronics Engineers Senior Member.
Srivastava is exploring new approaches for goal-oriented,
ethical, human-machine collaboration via natural interfaces
using domain and user models, learning, and planning.
He is leading efforts for adoption of AI technologies in a
large-scale global business context and understanding their
impact on workforce. Srivastava received his MS and PhD
from Arizona State University, and a BTech from Indian
Institute of Technology, India, all in computer science.