News for the Research Area: Network Science

Bo Ji

Bo Ji is an associate professor in the Department of Computer Science, a College of Engineering Faculty Fellow, and affiliate faculty at the Sanghani Center.

Prior to joining Virginia Tech, he was an associate professor in the Department of Computer and Information Sciences at Temple University. He was also a senior member of Technical Staff at AT&T Labs, San Ramon, California, from January 2013 to June 2014.

He received his B.E. and M.E. degrees in information science and electronic engineering from Zhejiang University, Hangzhou, China, and his Ph.D. degree in electrical and computer engineering from The Ohio State University.

In the early stages of his academic career, his research centered on the design, analysis, control, and optimization of complex networked systems, including wireless and wired communication networks, edge and cloud computing, data centers, information-update systems, and Internet of Things. Over the years, his focus has expanded significantly to include the multidisciplinary intersections of Computing and Networking Systems, Artificial Intelligence and Machine Learning (AI/ML), Security and Privacy, and Extended Reality (XR, including MR/VR/AR).

He has been the general co-chair of IEEE/IFIP WiOpt 2021 and the technical program co-chair of ACM MobiHoc 2023 and ITC 2021, and he has also served on the editorial boards of various IEEE/ACM journals: IEEE/ACM Transactions on Networking; ACM SIGMETRICS Performance Evaluation Review; IEEE Transactions on Network Science and Engineering; IEEE Internet of Things Journal; and IEEE Open Journal of the Communications Society.

Ji is a senior member of the IEEE and the ACM. He was a recipient of the National Science Foundation (NSF) CAREER Award in 2017; the NSF CISE Research Initiation Initiative Award in 2017; the IEEE INFOCOM 2019 Best Paper Award;  the IEEE/IFIP WiOpt 2022 Best Student Paper Award; the IEEE TNSE Excellent Editor Award in 2021 and 2022; and the Dean’s Faculty Fellow Award from the College of Engineering at Virginia Tech in 2023.

 

Jianger Yu

Jianger Yu is a master’s degree student in the Department of Computer Science. His advisor is Chang-Tien Lu.
His research interest lies in the application of advanced artificial intelligence and machine techniques in traditional chemical engineering and material science.
 

Yiqi Su

Yiqi Su is a Ph.D. student in the Department of Computer Science.  Her advisor is Naren Ramakrishnan.
Su’s research interest lies in computational epidemiology, with a particular focus on time-series forecasting to better understand and predict the dynamics of disease spread.

Murat Kantarcioglu

Murat Kantarcioglu is a professor and CCI Faculty Fellow in the Department of Computer Science at Virginia Tech and a core faculty at the Sanghani Center. He is also a faculty associate at Harvard’s Data Privacy Lab. Before joining Virginia Tech, he served as an Ashbel Smith Professor of Computer Science at UT Dallas and was a visiting scholar at UC Berkeley’s RISE Labs.
He earned his Ph.D. in computer science from Purdue University in 2005, where he received the Purdue CERIAS Diamond Award for Academic Excellence. His research centers on integrating cybersecurity, data science, and blockchain technologies to develop secure, privacy-preserving and efficient data analytics and trustworthy AI tools.
His research has been supported by numerous grants from agencies such as NSF, AFOSR, ARO, ONR, NSA, and NIH. He has authored over 180 peer-reviewed papers in top-tier venues including NDSS, CCS, USENIX Security, KDD, NEURIPS, SIGMOD, ICDM, ICDE etc. and several IEEE/ACM Transactions. He has also served as Program Co-Chair for conferences such as IEEE ICDE, ACM SACMAT, IEEE Cloud, IEEE CNS, and ACM CODASPY. His research has been featured by media outlets such as the Boston Globe, ABC News, PBS/KERA, and DFW Television, and he has received multiple best paper awards.  He is also a fellow of IEEE and AAAS.

Rashed Shelim

Rashed Shelim is a postdoctoral research associate working jointly at the Sanghani Center and in the Bradley Department of Electrical and Computer Engineering under the supervision of Naren Ramakrishnan and Walid Saad, respectively.
He is currently developing artificial intelligence-native 6G networks that can properly generalize to dynamic environments and to unseen use cases. His research interests include resilient and generalizable wireless communications for 6G and beyond; geometric machine learning; and vehicular communications.
Previously, he was a senior lecturer in the Department of Electrical and Computer Engineering at North South University, Bangladesh. His professional experience includes a summer internship at Nokia Bell Labs, USA, and a position as Core Network Engineer (Packet Switching) at Huawei Technologies Bangladesh LTD. Additionally, he worked as a research assistant at P3 Communication GmbH, Germany.
Shelim received a bachelor of science degree in electronics and telecommunication engineering from the North South University, Bangladesh; a master of science degree in electrical engineering, information technology, and computer engineering from the RWTH Aachen University, Germany, and his Ph.D. degree in electrical and computer engineering from Florida International University.
 

Sumin Kang

Sumin Kang is a Ph.D. student in the Grado Department of Industrial and Systems Engineering.  His advisor is
Manish Bansal.

Kang’s research interest is in optimization with uncertainty, especially with applications to network optimization problems and their vulnerability analysis. In particular, he aims to develop efficient algorithms for large-scale optimization problems within distributionally robust optimization and stochastic integer programming frameworks.-

Weijie Guan

Weijie Guan is a Ph.D. student in the Department of Computer Science.  He is advised by Dawei Zhou.
His research mainly focuses on novelty detection and anomaly detection from graph machine learning to general machine learning to enable artificial intelligence systems to recognize unknown classes.

Manish Bansal

Manish Bansal is an associate professor; Grado Early Career Faculty Fellow; Operations Research Program Area lead with the Grado Department of Industrial and Systems Engineering at Virginia Tech; and core faculty at the Sanghani Center.

He earned a bachelor’s degree in electrical engineering from the National Institute of Technology in India, and a master’s degree with a thesis and Ph.D. in operations research from the Department of Industrial and Systems Engineering at Texas A&M University. Prior to joining Virginia Tech, he was a postdoctoral fellow in the Department of Industrial Engineering and Management Sciences at Northwestern University.

Bansal’s research is focused on the theory of integer/stochastic/robust optimization, game theory, machine learning, and location science along with their applications in homeland defense, cybersecurity, logistics, and supply chain management. He has received multiple grants from National Science Foundation, Department of Defense, and the Cyber Commonwealth Initiative.

He has served as president of INFORMS Junior Faculty Interest Group and Engineering Faculty Organization at Virginia Tech and is a member of INFORMS, SIAM, and the Mathematical Optimization Society.

Melike Yildiz Aktas

Melike Yildiz Aktas is a Ph.D. student in the Department of Computer Science.  Her advisor is Chang-Tien Lu.

Her research interests lie in urban computing, social networks, and humanitarian logistics.  She would like to contribute to the development of smart cities, playing an active role in their advancement.

Dawei Zhou

Dawei Zhou is an assistant professor in the Virginia Tech Department of Computer Science; director of the VirginiaTech Learning on Graphs (VLOG) Lab; and core faculty at the Sanghani Center.

Zhou’s prior research is on rare category detection, graph mining, curriculum learning, and algorithmic fairness, with applications in financial fraud detection, cyber security, financial forecasting, social media analysis, and healthcare. He earned his Ph.D. degree from the Computer Science Department at the University of Illinois Urbana-Champaign.

Zhou has authored more than 30 publications in premier academic venues across AI, data mining, and information retrieval (e.g., AAAI, IJCAI, KDD, ICDM, SDM, TKDD, DMKD, WWW, CIKM) and has served as senior program committee and session chairs in various top ML and AI conferences (e.g., NeurIPS, ICML, KDD, WWW, SIGIR, ICLR, AAAI, IJCAI).

He has been the key contributor and team leader in several DARPA projects. His work on rare category detection with human-AI intelligence was selected by the Computing Research Association (CRA) to showcase at the 24th CNSF Capitol Hill Science Exhibition.