News featuring Chang-Tien Lu

DAC Student Spotlight: Xuchao Zhang

DAC Ph.D. student, Xuchao Zhang

In the era of data explosion, noise and corruption in real-world data caused by accidental outliers, transmission loss, or even adversarial data attacks is inevitable and often results in incorrect data labeling. For example, a negative review in the Internet Movie Database (IMDb) could be mislabeled as positive or an image of a panda might be mislabeled as a gibbon.

Xuchao Zhang, a Ph.D. student in computer science, is focused on solving the problem of mislabeling.

“Using scalable robust model learning, we propose distributed and online robust algorithms to handle regression and classification problems in the presence of adversarial data corruption,” said Zhang, who is advised by Chang-Tien (C.T.) Lu in the National Capital Region.

Zang said his research can be broadly applied to noisy datasets in massive real-world applications.

Zhang, who earned a bachelor’s degree at Shanghai Jiao Tong University in China, begin his Ph.D. studies in 2009.

“I chose Virginia Tech’s engineering school for its abundance of advanced research resources and outstanding faculty in the field of data mining and machine learning,” Zhang said. “I am very fortunate to work with Dr. Lu as a DAC student.”

He collaborated with Lu and other researchers from Virginia Tech and George Mason University on the study, “Online and Distributed Robust Regressions under Adversarial Data Corruption,” which he presented at the 2017 IEEE International Conference on Data Mining (ICDM) in New Orleans, LA, in November.

His research has also been presented at other conferences, including the ACM International Conference on Information and Knowledge Management (CIKM); the IEEE International Conference on Big Data, and the International Joint Conference on Artificial Intelligence (IJCAI).

Zhang serves on the program committee (research track) for the Association of Computing Machinery’s Special Interest Group on Knowledge of Discovery and Data Mining (KDD) and will be attending the 2018 conference in London.

This summer, Zhang heads to Redmond, Washington, where he has an internship at Microsoft Research AI.

DAC has strong presence at ICDM 2017

DAC Ph.D. student, Zhiqian Chen, presenting his paper at ICDM 2017.

The Discovery Analytics Center was strongly represented at the IEEE International Conference on Data Mining (ICDM) in New Orleans, Nov. 18-21, with a number of accepted research papers by DAC faculty and students and DAC faculty serving on committees and panels.

Research papers accepted for the conference include:

DAC faculty participation in the ICDM Conference included Chang-Tien Lu serving on the program committee and Naren Ramakrishnan serving as an area chair. Ramakrishnan also co-chaired a panel focusing on ethical and professional issues when dealing with social data with Tanushree (Tanu) Mitra, assistant professor of computer science, as one of the panelists. B. Aditya Prakash was invited to participate as a mentor in the ICDM Ph.D. Forum.

The ICDM has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of data mining, including algorithms, software and systems, and applications. ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high-performance computing. By promoting novel, high quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to continuously advance the state-of-the-art in data mining. Besides the technical program, the conference features workshops, tutorials, panels.





DAC Director Naren Ramakrishnan named Inventor of the Month


Members of the staff of the Discovery Analytics Center. Left to right are Nathan Self, Patrick Butler, and Naren Ramakrishnan.

DAC and director, Naren Ramakrishnan, are featured as this month’s Virginia Tech​ Inventors of the Month by the Office of Research and Innovation for work in Early Model Based Event Recognition using Surrogates (EMBERS) software project.

EMBERS is a fully automated system for forecasting significant societal events, such as influenza-like illness case counts, rare disease outbreaks, civil unrest, domestic political crises, and elections, from open source surrogates. To read more about EMBERS click here.

Liang Zhao named one of Top 20 New Stars in Data Mining

nvc-3Congratulations to Liang Zhao, a recent DAC Ph.D. graduate in computer science, who has been named one of the Top 20 New Starts in Data Mining, provided by Microsoft searching. Liang was advised by Chang-Tien Lu, associate director of DAC and professor of computer science.

Microsoft searching mines the past six years of Knowledge Discovery and Data Mining (KDD) submissions and combines the big data from Microsoft to then achieve the ranking by an automatic algorithm. KDD is the top conference in the data mining area. Click here if you’d like to read more.


Chang-Tien Lu promoted to professor

CT LuCongratulations to DAC associate director, Chang-Tien Lu, who has been promoted to full professor in the department of computer science.  Dr. Lu is an ACM Distinguished Scientist.  His research focuses on data management to fulfill emerging requirements for storing, analyzing, and visualizing spatial data. To read more about this years promotions, click here.