Introduction to Professor Wenjia Li and His Lab at New York Institute of Technology
1. Could you briefly introduce yourself (and your University/Lab)?
Wenjia Li received the Ph.D. degree in computer science from the University of Maryland Baltimore County (UMBC), Baltimore, MD, USA, in 2011. In 2014, he joined the Department of Computer Science, New York Institute of Technology, New York, NY, USA as a tenure-track assistant professor, and he has been a tenured associate professor since September 2020. Prior to that, he was a tenure-track Assistant Professor of computer science with Georgia Southern University, Statesboro, GA, USA, from 2011 to 2014. He has authored or co-authored over 80 peer-reviewed publications in various journals and conference proceedings. His current research interests include cyber security, mobile computing, and wireless networking, particularly security, trust, and policy issues for wireless networks, cyber-physical systems, Internet of Things, and intelligent transportation systems. His research has been supported by the National Institute of Health (NIH) and the U.S. Department of Transportation Region 2 University Transportation Research Center (UTRC). He was the recipient of the 2019 IEEE Region 1 Technological Innovation (Academic) Award, and he was the recipient of the 2020 NYIT Presidential Excellence Award for Student Engagement in Research, Scholarship, or Creative Activities. He has been a senior member of IEEE since 2020.
Dr. Li has served as the Organizing Committee member for many international conferences such as ACM WiSec, IEEE DySPAN, IEEE MDM, IEEE IPCCC, and IEEE Sarnoff, and he also served as a Reviewer for many prestigious journals such as IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, and the IEEE IoT Journal.
2. What have been your most significant research contributions up to now?
So far, my primary research focus has been centered around the interplay between machine learning and cyber security. On one hand, I have been exploring different ways to apply machine learning algorithms to help better secure wireless networks and its applications, such as connected vehicles, smart health, and so on. For example, I have proposed an attack-resistant trust management scheme (ART) for vehicular networks that could cope with different types of cyber attacks and manage the trust of both vehicles and data in an effective and accurate manner, which is published in IEEE Transactions on Intelligent Transportation Systems in 2016. This research work has been cited for over 260 times within five years of publication. More recently, I have explored to use both deep learning algorithm and the emerging blockchain technology to help identify malicious vehicles together with my Master’s thesis advisee at NYIT, and this work has been published in IEEE Internet of Things (IoT) Journal in 2021, which is a high impact journal in the IoT research domain with impact factor of 9.936 according to JCR’20.
On the other hand, I am also curious to find out how machine learning based mechanisms would react and handle security challenges that are targeting them. In this direction, I worked with a group of undergraduate students at NYIT on the topic of building a robust malware detection mechanism for the Android system in the presence of adversarial example attacks.
3. What problems in your research field deserve more attention (or what problems will you like to solve) in the next few years, and why?
In the next few years, I would like to continue looking at the research challenges brought by rapid growth of the autonomous and connected vehicles, especially the security and trust issues. According to the National Highway Traffic Safety Administration, vehicle-to-vehicle communications technology is a promising way to combat vehicular accidents, reduce road congestions, and improve the environment by alerting drivers of potential hazards such as a crash. By 2025, it has been estimated that there will be more than 470 million connected vehicles on the roads in the United States, Europe, and China. However, while the open nature of connected vehicular networks could increase the delivery and timeliness of the messages, it will also increase the likelihood that the message may not be trustworthy, or even be a security threat. Thus, it is essential to properly evaluate the trustworthiness of both traffic related messages and vehicles which share them in vehicular networks.
4. What advice would you like to give to the young generation of researchers/engineers?
As a “young” researcher myself, I would like to share some of my thoughts, rather than giving advice, with the “younger” generation of researchers and engineers. One thought I would like to share is to stay focused yet still be open-minded. Sometimes, it is challenging to achieve both at the same time. It would be beneficial to focus on a specific research topic and try to find different ways to address it, so that you would not be easily distracted. However, it is also important to be open-minded and be aware of what is happening in the research domain recently, so that you are assured that the topic that you are researching on is still up to date.