Prof.Zoran Obradovic is program co-chair for the IEEE BigData 2017 conference (jointly with Prof. Jian-Yun Nie from University of Montreal and Dr. Toyotaro Suzumura from IBM T.J. Watson Research Center).
Prof.Zoran Obradovic is program co-chair for the IEEE BigData 2017 conference (jointly with Prof. Jian-Yun Nie from University of Montreal and Dr. Toyotaro Suzumura from IBM T.J. Watson Research Center). This conference will be on Dec 11-14 in Boston, MA.Paper submissions are due by Aug 7, 2017. Call for papers is at http://cci.drexel.edu/bigdata/bigdata2017.
The SIAM Data Mining / IBM Early Career Data Mining Researcher Award for Excellence in Data Analytics recognizes one individual who has made outstanding,
The SIAM Data Mining / IBM Early Career Data Mining Researcher Award for Excellence in Data Analytics recognizes one individual who has made outstanding, influential, and lasting contributions in the field of data analysis and who will be within 10 years of having received their PhD degree as of the calendar year prior to the […]
Prof. Zoran Obradovic is co-editing the special issue of Complexity journal
Prof. Zoran Obradovic is co-editing the special issue of Complexity journal devoted to New Methods for Analyzing Complex Biomedical Systems and Signals (co-edited with I. Reljin, M. Popovic and V. Mladenov). Manuscripts are due by May 12, 2017. For more details see here
Prof. Zoran Obradovic is a co-PI for a Big Data Spoke devoted to Smart Grids (joint work with investigators at Texas A&M and at Georgia Tech).
The NSF Press Releases 16-116 of Sept. 28, 2016 reported that $11 million is awarded to 10 Big Data Spokes projects aimed to connect data scientist with regional challenges. Prof. Zoran Obradovic is a co-PI for a Big Data Spoke devoted to Smart Grids (joint work with investigators at Texas A&M and at Georgia Tech). […]
Prof. Zoran Obradovic has been named a Distinguished Speaker for the Association for Computing Machinery (ACM).
In September 2016 Prof. Zoran Obradovic has been named a Distinguished Speaker for the Association for Computing Machinery (ACM). His term as a Distinguished Speaker is for three years. ACM’s Distinguished Speaker Program (DSP) is a highly visible way for ACM members to engage with emerging professionals, students and, in some cases, the public on […]
EurekAlert! Press Release: Obradovic’s Lab collaborates with the Wyss Institute,
EurekAlert! Press Release: Obradovicâs Lab collaborates with the Wyss Institute, Harvard Medical School, the Mayo Clinic, Tuffs University and Boston Childrenâs hospital to uncover underlying causes of tolerance to infection (funded by DARPA THOR program). For more details see EurekAlert .
Prof. Obradovic is elected to another prestigious Academy.
On Nov. 5th Prof. Zoran Obradovic has become a foreign member of the Serbian Academy of Sciences and Arts. The Serbian Academy is founded in 1886 and it has about 250 members who elect new members in a 3 years cycle that involves a rigorous multi-stage review process and a secret ballot. This time 14 domestic […]
Prof. Obradovic is a keynote speaker at the ICMLA 2015
Dr. Zoran Obradovic is a keynote speaker at the 14th IEEE International Conference on Machine Learning and Applications (ICMLA). This conference is held on December 9-11, 2015 in Miami. His talk is entitled Predictive Analytics in Complex Dynamic Networks.
Prof. Obradovic is elected as a member of Academia Europaea.
Prof. Zoran Obradovic become an elected member of Academia Europaea (the Academy of Europe). His nomination was preceded by a rigorous review by class committees and the Council of the Academy. The Informatics section, which he joined, has 226 members where ten were elected this year. The Academia Europaea is London-based Academy of Humanities, Letters and Sciences […]
Prof. Zoran Obradovic is awarded the Office of Naval Research grant to study structured regression in complex networks by fusion of qualitative knowledge and big data.
Prof. Zoran Obradovic is awarded the Office of Naval Research grant to study structured regression in complex networks by fusion of qualitative knowledge and big data. The scope of this project is developing a synergetic platform for predictive modeling of complex dynamic networks that will connect cutting-edge predictive machine learning models and rigorous mathematical methods […]