Current lab members:
|Daniel B. Neill
Daniel B. Neill is the Dean’s Career Development Professor and Associate Professor of Information Systems at Carnegie Mellon University’s Heinz College, where he directs the Event and Pattern Detection Laboratory and the Joint Ph.D. Program in Machine Learning and Policy. He holds courtesy appointments in Machine Learning and Robotics at CMU and is an adjunct professor in the University of Pittsburgh’s Department of Biomedical Informatics. He received his M.Phil. from Cambridge University and his M.S. and Ph.D. in Computer Science from CMU. His research focuses on machine learning and event detection in massive datasets, with applications ranging from medicine and public health to law enforcement and security. His detection methods have been incorporated into deployed disease surveillance systems throughout the world, and his “CityScan” software is in day-to-day operational use by police to predict and prevent emerging hot spots of violent crime. Dr. Neill was the recipient of an NSF CAREER award and an NSF Graduate Research Fellowship, and was recently named one of the “top ten artificial intelligence researchers to watch” by IEEE Intelligent Systems.
Dylan Fitzpatrick is a Ph.D. student in Machine Learning and Public Policy at Carnegie Mellon University. His research focuses on informing public policy decisions through intelligent use of machine learning and other tools for large-scale data analytics, particularly in the areas of urban analytics, natural resource management, and computational ecology. Dylan earned a B.A. in Economics from Middlebury College and an M.S. in Computer Science from Carnegie Mellon University.
Seth Flaxman grew up outside Chicago, studied computer science and mathematics at Harvard, and worked at the World Health Organization before starting his Ph.D. in machine learning and public policy in 2011. He works on forecasting and prediction with high-dimensional spatio-temporal data and hierarchical Bayesian models, applied to public health and criminology. He was the 2013 winner of Heinz College’s Suresh Konda Best Paper Award, for his work on “Correlates of homicide: new space/time interaction tests for spatio-temporal point processes”.
William Herlands is a joint PhD student in Machine Learning and Public Policy developing novel anomaly detection and rare event modeling techniques for critical applications in healthcare and cybersecurity. Before joining the lab, William was a researcher at MIT Lincoln Laboratory, where he focused on developing cybersecurity guarantees for robotic swarms. William graduated from Princeton in 2012 with a degree in Electrical Engineering and minors in Computer Science and Near Eastern Studies. He is a recipient of an NSF Graduate Research Fellowship as well as an ARCS scholarship for his graduate work.
Abhinav Maurya is a graduate student at CMU studying Information Systems with research interests in Machine Learning, Data Mining, and Optimization Theory. As an undergraduate at VJTI Bombay, he was awarded the JRD Tata Scholarship for three consecutive years. He has earned a masters degree in Computer Science and Engineering from IIT Bombay, where he worked on using machine learning for traffic congestion detection in developing countries. He fondly remembers the place for having the most thoughtful and intelligent people he has met in his life. He was also a part of the Microsoft Bing team in Seattle for a year before heading to Pittsburgh for graduate studies.
|Edward McFowland III
Ed McFowland is a Ph.D. candidate in Information Systems and has earned a secondary master’s degree in Machine Learning. His research interests include the development of computationally efficient algorithms for large-scale statistical machine learning and data mining, with a focus on applications to business, policy, and management. He is a recipient of both an AT&T Labs Fellowship and a National Science Foundation Graduate Research Fellowship, for his work in developing efficient methods for detection and discovery of anomalous patterns in massive multivariate data. He was the 2012 winner of Heinz College’s Suresh Konda Best Paper Award, for his work on “Fast generalized subset scan for anomalous pattern detection”, and the 2015 winner of Heinz College’s William W. Cooper Doctoral Dissertation Award, for his Ph.D. thesis on “Efficient Methods for Pattern Detection and Discovery”.
Yun Ni is a master’s student in Information Security Policy Management at CMU’s Heinz College. His major research interest is in applying machine learning techniques to security applications like intrusion detection systems, masquerade and malware detection. He is also interested in computational learning theory. He earned a B.S. degree in Information Security from Fudan University.
Mallory Nobles is a third year Ph.D. student in Information Systems. Her research interests include anomaly detection and active learning, applied to disease surveillance and social media applications. She earned a B.S. in mathematics from Davidson College and a Masters in Operations Research from Georgia Tech.
As a doctoral student in the Heinz College, Sriram Somanchi is driven by solving problems that have real-world impact and policy implications. His interest is in developing computationally efficient statistical machine learning algorithms for pattern detection in large scale data, with applications to the public good. His work introduces the use of large scale pattern detection to the domain of digital pathology, and makes additional methodological contributions to domains ranging from healthcare and disease surveillance to law enforcement. He was the 2013 winner of Heinz College’s George Duncan Best Paper Award, for his work on “Detecting anomalous patterns in large digital pathology images”, and the winner of Heinz College’s Graduate Student Teaching Award in 2015.
Skyler Speakman‘s research focuses on developing novel scan statistics for data generated from sensors and devices, applied to policy relevant problems such as public health, sanitation, and sustainability. He believes that creating intelligent information systems is the key to overcoming the inherent randomness in data collected by these complex systems. Skyler had a background in mathematics and statistics before starting his Ph.D. in Information Systems. He also received a masters degree in machine learning from Carnegie Mellon University. He was the winner of Heinz College’s Graduate Student Teaching Award in 2012 as well as the Carnegie Mellon Graduate Student Teaching Award in 2014.
Zhe Zhang is a third year Ph.D. student at CMU’s Heinz College. His research, at the intersection of economics, public policy and machine learning, focuses on how social science and policy analysis can be augmented with machine learning techniques and approaches. Areas of particular interest are urban policy, geospatial data, the impacts of information technology in cities, and urban development in emerging countries. Previously, Zhe studied economics and statistics at Stanford University, and then, before his Ph.D., did energy and environmental economic research and worked at the NRDC and UCS non-profits.
Feng Chen (Assistant Professor of Computer Science, SUNY Albany).
David Choi (Assistant Professor of Statistics and Information Systems, Heinz College, CMU)
Wilpen Gorr (Professor of Public Policy and Management Information Systems, Heinz College, CMU)
Rema Padman (Professor of Management Science and Healthcare Informatics, Heinz College, CMU)
Tarun Kumar (M.S., Very Large Information Systems, CMU). Now Software Engineer in Data Analysis, Data Mining and Machine Learning at LinkedIn.
Yandong Liu (M.S., Language Technologies, CMU). Now Tech Lead/Research Engineer at Yahoo! Labs.
Kai Liu (M.S., Very Large Information Systems, CMU). Now Software Engineer at Facebook.
Rajas Lonkar (M.S., Information Systems Management, CMU). Now Senior Consultant in Advanced Analytics and Optimization at IBM.
Kenton Murray (M.S., Language Technologies, CMU). Now Ph.D. student at University of Notre Dame.
Amrut Nagasunder (M.S., Very Large Information Systems, CMU). Now Senior Software Engineer at Netflix.
Kan Shao (Ph.D., Engineering and Public Policy, and M.S., Machine Learning, CMU). Now Assistant Professor of Environmental Health at Indiana University- Bloomington, School of Public Health.
Xin Wu (M.S., Very Large Information Systems, CMU). Now Software Engineer at Google.
Yating Zhang (M.S., Information Systems Management, CMU). Now Ph.D. student at Kyoto University.
Huanian Zheng (M.S., Information Technology, CMU)