Speakers

Rediet Abebe

Computer Science

https://www.cs.cornell.edu/~red/

http://md4sg.com/

http://blackinai.org/

Rediet Abebe is a Ph.D. candidate in computer science at Cornell University, advised by Professor Jon Kleinberg. Her research focuses on algorithms, AI, and applications to social good. She uses computational techniques, in conjunction with insights from the social sciences, to improve access to opportunity for communities of individuals for whom opportunities have historically been limited. As part of this research mission, she co-founded and co-organizes the Mechanism Design for Social Good (MD4SG) initiative, an interdisciplinary, multi-institutional research group. She also co-founded and co-organizes Black in AI, a transcontinental group aimed at increasing the presence and inclusion of Black individuals in the field of AI. Her research is deeply influenced by her upbringing in her hometown of Addis Ababa, Ethiopia, where she lived until moving to the U.S. in 2009. Her work has been generously supported by fellowships and scholarships through Facebook, Google, the Cornell Graduate School, and the Harvard-Cambridge Fellowship.

 

Sean Barnes, Ph.D.

Operations Management

http://scholar.rhsmith.umd.edu/sbarnes/biocv

Sean Barnes is an Assistant Professor of Operations Management in the Robert H. Smith School of Business at the University of Maryland. He received his doctoral degree in Scientific Computation from the University of Maryland in 2012 and previously studied Aerospace Engineering at the Georgia Institute of Technology (B.S. 2006, M.S. 2007). His research interests include infectious disease modeling, healthcare analytics, agent-based modeling and simulation, machine learning, and data visualization; and his current collaborations include the University of Maryland School of Medicine and Johns Hopkins University. His research has been published in the INFORMS Journal on Computing, IISE Transactions on Healthcare Systems Engineering, Journal of the American Medical Informatics Association, Annals of Emergency Medicine, and Infection Control and Hospital Epidemiology, as well as other engineering and clinical outlets. In the Robert H. Smith School of Business, he teaches analytics, simulation, and Python courses to MS, MBA, and undergraduate students.

 

Kira Goldner

Mechanism Design

https://homes.cs.washington.edu/~kgoldner/

http://md4sg.com/

Kira Goldner is a fifth-year PhD student in the Allen School of Computer Science and Engineering at the University of Washington in Seattle, advised by Anna Karlin. Her research is in algorithmic mechanism design: designing algorithms that guarantee that, even when the data that they run on is produced by strategic individuals who act in their own self-interest, the designer’s objectives are achieved. Kira’s work ranges from social good questions in healthcare and online platform design to revenue maximization problems inspired by practice. In 2016, Kira co-founded the Mechanism Design for Social Good (MD4SG) initiative. She is a 2017 recipient of the Microsoft Research PhD Fellowship and was a 2016 recipient of a Google Anita Borg Scholarship.

Sanmi (Oluwasanmi) Koyejo, Ph.D.

Machine Learning

http://sanmi.cs.illinois.edu/index.html

Sanmi (Oluwasanmi) Koyejo an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Koyejo’s research interests are in the development and analysis of probabilistic and statistical machine learning techniques motivated by, and applied to various modern big data problems. He is particularly interested in the analysis of large scale neuroimaging data.

Koyejo completed his Ph.D in Electrical Engineering at the University of Texas at Austin advised by Joydeep Ghosh, and completed postdoctoral research at Stanford University with a focus on developing Machine learning techniques for neuroimaging data. His postdoctoral research was primarily with Russell A. Poldrack and Pradeep Ravikumar. Koyejo has been the recipient of several awards including the outstanding NCE/ECE student award, a best student paper award from the conference on uncertainty in artificial intelligence (UAI) and a trainee award from the Organization for Human Brain Mapping (OHBM).

Destenie Nock, Ph.D.

Industrial Engineering and Operations Research

https://destenienock5.wixsite.com/destenienock

https://www.linkedin.com/in/desdes/

https://twitter.com/destenienock

Destenie Nock recently completed a Ph.D. in Industrial Engineering and Operations Research from the University of Massachusetts Amherst, where she was an NSF Graduate Research Fellow, and an Offshore Wind Energy IGERT Fellow. Prior to this she was a Mitchell Fellow in Northern Ireland where she earned an MSc in Leadership for Sustainable Development at Queens University of Belfast. Her research is focused on applying optimization and decision analysis tools to evaluate the sustainability and reliability of the electricity grid in disparate energy systems. She has two B.S. degrees from North Carolina A&T State University in Electrical Engineering and Applied Mathematics.  In addition, she has spent time volunteering in Malawi, held internships at Argonne National Lab, the Utility Regulator of Northern Ireland, and Exxon Mobil.

 

Jennifer Lewis Priestley, Ph.D.

Analytics and Data Science

http://facultyweb.kennesaw.edu/jpriestl/index.php

http://datascience.kennesaw.edu/

Dr. Priestley is the Associate Dean of The Graduate College and the Director of the Analytics and Data Science Institute at Kennesaw State University. In 2012, the SAS Institute recognized Dr. Priestley as the 2012 Distinguished Statistics Professor of the Year. She served as the 2012 and 2015 Co-Chair of the National Analytics Conference. Datanami recognized Dr. Priestley as one of the top 12 “Data Scientists to Watch in 2016.”

Dr. Priestley has been a featured speaker at SAS Analytics, Big Data Week, Technology Association of Georgia, Data Science ATL, The Atlanta Chief Data Officer Summit, The Atlanta CEO Council, Predictive Analytics World, INFORMS and dozens of corporate events addressing issues related to advanced analytics and the challenges and opportunities of “Big Data”. She is a member of the Advisory Board for the Southern Data Science Conference.

Prior to receiving a Ph.D. in Statistics, Dr. Priestley worked in the Financial Services industry for 11 years. Her positions included Vice President of Business Development for VISA EU in London, as well as for MasterCard US and an analytical consultant with Accenture’s strategic services group. Dr. Priestley received a Ph.D. from Georgia State, a MBA from The Pennsylvania State University, where she was president of the graduate student body, and a BS from Georgia Tech.

Kaitlin Rizk

Artificial Intelligence

Stempowerinc.org

Kaitlin Rizk is a consulting analyst at Accenture in Washington, DC. She graduated from the Industrial and Systems Engineering Department at Georgia Tech in May 2018 with the best scholastic record of her class. She received the Love Family Foundation award for being the top student of her graduating class. At Accenture, Kaitlin has been involved with an AI project for a travel industry client and has supported many nonprofit projects as well.While at Georgia Tech, Kaitlin co-founded a nonprofit, Stempower, aimed to empower the next generation of women in STEM. She aims to bring diversity into the global technology workforce.

 

Alba C. Rojas-Cordova, Ph.D.

Healthcare Analytics

https://www.smu.edu/Lyle/Departments/EMIS/People/Faculty/RojasCordovaAlba

Alba Rojas-Cordova is an Assistant Professor in the Department of Engineering Management, Information, and Systems (EMIS) at Southern Methodist University. She earned her Ph.D. and Master’s degrees in Industrial and Systems Engineering at Virginia Tech in 2017 and 2011, respectively, and her Bachelor’s degree in Industrial Engineering at the Bolivian Catholic University. After completing her Master’s degree, Alba spent two years working as a production planner in a manufacturing company. Her primary research interest is in sequential decision-making under uncertainty in the public and private sectors. Alba’s current research focuses on the analysis of resource allocation decisions in biopharmaceutical R&D, especially within adaptive clinical trial settings, with the application of stochastic dynamic programming, simulation, and system dynamics. Alba’s research has been published in highly recognized journals such as Service Science, and has been recognized with the INFORMS Bonder Scholarship for Applied Operations Research in Health Services, the INFORMS Seth Bonder Foundation Research Award, and an Honorable Mention in the System Dynamics Society Dana Meadows Student Paper Award, among others. Alba is an active member of the INFORMS Minority Issues Forum (MIF) since 2016, and is involved in different initiatives to increase representation of underrepresented minorities in Operations Research and Management Science.