Vasanth Reddy Baddam is a Ph.D. student in the Department of Computer Science. His advisor is Hoda Eldardiry.     Baddam’s research interests are artificial intelligence, reinforcement learning, and control systems. He is particularly interested in developing a reinforcement learning control method informed by knowledge of the system’s physics models while leveraging system structure by modeling interactions between system components to […]

Si Chen is a Ph.D. student in the Bradley Department of Electrical and Computer Engineering. Her advisor is Ruoxi Jia. Chen’s research focuses primarily on privacy in machine learning (privacy attacks and defense), and data utility learning.  

Jie Bu was a Ph.D. student in the Department of Computer Science.  His advisor was Anuj Karpatne.   Bu’s research interest lies in machine learning, particularly in science-guided machine learning,  representation learning, and  network pruning.   

With restrictions to working in physical office space still in effect, graduate students at the Sanghani Center are working remotely this summer for companies, labs, and programs from coast to coast. Students are not only gaining real-world experience from internships and other opportunities but, in many cases, they are also able to advance their own […]

Shuaicheng Zhang is a Ph.D. student in the Department of Computer Science. He is advised by Dawei Zhou.   Zhang’s research focuses on deep learning-based natural language processing and information extractions, especially targeting transformer-based relation extraction and temporal relation extraction.

M. Maruf is a Ph.D. student in the Department of Computer Science. His advisor is Anuj Karpatne.   Maruf’s research interests are in the broad domains of Science-Guided Machine Learning and its applications, focusing on integrating domain knowledge into machine learning models to obtain generalized solutions consistent with scientific knowledge. In particular, he is developing new algorithms for […]

Lei Zhang, Liang Zhao, Xuchao Zhang, Wenmo Kong, Zitong Sheng , Chang-Tien Lu: Situation-Based Interpretable Learning for Personality Prediction in Social Media. IEEE BigData 2018: 1554-1562

Kaiqun Fu, Zhiqian Chen, Chang-Tien Lu: StreetNet: preference learning with convolutional neural network on urban crime perception.SIGSPATIAL/GIS 2018: 269-278

Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu:Robust Regression via Online Feature Selection Under Adversarial Data Corruption. ICDM 2018: 1440-1445