News featuring B. Aditya Prakash

DAC Student Spotlight: Sorour Ekhtiari Amiri

Sorour Ekhtiari Amiri, DAC Ph.D. student in computer science

Sorour Ekhtiari Amiri developed an interest in machine learning during her senior year of college. After earning a bachelor’s degree in computer engineering from Beheshti University, she worked on machine learning applications while getting a master’s in computer engineering at the University of Tehran.

Amiri then decided to pursue a Ph.D. in computer science.

“I chose Virginia Tech and the Discovery Analytics Center,” Amiri said, “because of the great opportunity to collaborate with high impact researchers in the areas of data mining and machine learning.”

Amiri’s research is focused on summarizing large graphs and graph sequences based on a given task. She targets the task-based graph summarization problem, looks at various types of graphs, and uses deterministic and learning based approaches to generate high-quality graph summaries.

“Large graphs — also referred to as network — appear everywhere, as they very well capture the relation between objects,” Amiri said.

“For example, social networks, co-purchased product networks, people contact networks, and protein interaction graphs are instances of large graphs in the real world. Analyzing these graphs and solving various tasks on them has many applications in different fields such as cybersecurity, recommendation systems, sociology, and biology. However, the increasingly large size of such networks makes it challenging to visualize and analyze them, highlight their important characteristics, and perform fast computations on them,” said Amiri, whose DAC faculty advisor is B. Aditya Prakash.

Results of her research while a DAC student have been presented at a number of national and international conferences, including the IEEE International Conference on Data Mining series (ICDM); European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (PKDD); and the Association for the Advancement of Artificial Intelligence (AAAI) conference.

Her work has also appeared in journals such as the IEEE Transactions on Knowledge and Data Engineering (TDKE) and Data Mining and Knowledge Discovery (DAMI).

Amiri spent this past summer as an intern with Google’s “search ad” team, developing and training machine learning models and generating a new signal for using in search ads auction. She also analyzed machine learning models and other search ads signals.

Amiri expects to graduate in spring 2019


DAC and UrbComp actively participating at KDD 2018 with conference organization and research presentations

KDD Logo

The Discovery Analytics Center and the Urban Computing Certificate Program (funded through a National Science Foundation traineeship grant and administered through DAC) will be well represented at the 24th Annual  Association for Computing Machinery Special Interest Knowledge Discovery and Data Mining (KDD 2018) conference in London, August 19-23.

The overall theme of this year’s conference is data mining for social good.

Chandan Reddy, associate professor of computer science and DAC faculty, served as a poster co-chair for the KDD conference.

Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and DAC director, served on the senior program committee for the KDD research track.

Aditya Prakash, assistant professor of computer science and DAC faculty, served on the committee for Health Day at KDD, held in conjunction with the conference, and is one of four organizers for epiDAMIK: Epidemiology meets Data Mining and Knowledge discovery, a Health Day workshop.

This workshop serves as a forum to discuss new insights into how data mining can play a bigger role in epidemiology and public health research. While the integration of data science methods into epidemiology has significant potential, it remains understudied, Prakash said.

The goal of the workshop is to raise the profile of this emerging research area of data-driven and computational epidemiology and create a venue for presenting state-of-the-art and in-progress results — in particular, results that would otherwise be difficult to present at a major data mining conference, including lessons learned in the “trenches.”

The paper, “Forecasting the Flu: Designing Social Network Sensors for Epidemics,” (B. Aditya Prakash; Naren Ramakrishnan; Huijuan Shao, K.S.M. Tozammel Hossain and Hao Wu, all DAC Ph.D. alumni; Madhav Marathe, professor of computer science and director of the Network Dynamics and Simulation Science Lab (NDSSL) at Virginia Tech; Anil Vullikanti, associate professor of computer science at NDSSL and Maleq Khan, assistant professor at Texas A&M University) will be presented at the epiDAMIK workshop by Prakash and Vullikanti.

An Urban Computing workshop is also scheduled in conjunction with KDD2018. The objective of this workshop is to provide professionals, researchers, and technologists with a single forum where they can discuss and share the state-of-the-art of the development and applications related to urban computing, present their ideas and contributions, and set future directions in innovative research for urban computing. It is particularly targeted to people who are interested in sensing/mining/understanding urban data so as to tackle challenges in cities and help better formulate the future of cities.

The following posters from DAC have been accepted for presentation at the workshop:

Additionally, a DAC alumnus, Prithwish Chakraborty, is running a third workshop taking place during the conference, Machine Learning for Medicine and Healthcare (MLMH).


B. Aditya Prakash on IEEE magazine’s list of 10 young stars to watch in artificial intelligence

B. Aditya Prakash, DAC faculty member and assistant professor of computer science.

B. Aditya Prakash, an assistant professor of computer science in the College of Engineering, is being celebrated as one of 10 young stars in the field of artificial intelligence by IEEE Intelligent Systems.

The technical magazine named Prakash, who is also a faculty member at the Discovery Analytics Center, to the prestigious AI’s 10 to Watch list for his contributions to understanding, reasoning, and mining the phenomenon of propagation over networks in diverse real-world systems.  Click here to read more about the AI’s 10 to Watch list.


B. Aditya Prakash receives prestigious NSF CAREER Award

B. Aditya Prakash, assistant professor in The Department of Computer Science has received the prestigious Faculty Early Career Development (CAREER) Award from the National Science Foundation to find data-driven network strategies to enhance national security and public health. Click here to read ore about Aditya’s award.


DAC’s Aditya Prakash co-authored a book titled “The Global Cyber-Vulnerability Report”

Prakash-updatedDAC faculty member, Aditya Prakash has co-authored a book titled “The Global Cyber-Vulnerability Report,” in collaboration with the University of Maryland Institute for Advanced Computer Studies.

This book establishes metrics to measure cyber-vulnerability of countries and quantify the cyber-vulnerability of countries. In addition, it offers useful data-driven policy advice for law-makers and policy-makers in each country. It is also the first that uses cyber-vulnerability data to explore the vulnerability of over four million machines per year, covering a two-year period as reported by Symantec. Analyzing more than 20 billion telemetry reports comprising malware and binary reputation reports, this book quantifies the cyber-vulnerability of 44 countries for which at least 500 hosts were monitored.

Click here for more info about “The Global Cyber-Vulnerability Report.”