Suman Jana is an assistant professor in the department of computer science at Columbia University since January 2016. His primary research interest is in the field of computer security and privacy. His research has won six best paper awards including one at the Symposium on Operating Systems Principles (SOSP) 2017 and two at the IEEE Symposiums on Security and Privacy (S&P) 2014 and 2016. His work has led to reporting and fixing of around 250 high-impact security vulnerabilities across a wide range of software. His research software has also been incorporated as part of Google's malware detection infrastructure, Mozilla Firefox, and Apache Cordova.
Prof. Jana is specifically interested in the security issues that result from deploying Machine Learning (ML) systems in security- and safety-critical domains such as self-driving cars, automated passenger screening, and medical diagnosis. Despite significant progress in ML techniques like deep learning, ML systems often make dangerous and even potentially fatal mistakes, especially for rare corner case inputs. For example, a Tesla autonomous car was recently involved in a fatal crash that resulted from the system’s failure to detect a white truck against a bright sky with white clouds. Such incidents demonstrate the need for rigorous testing and veriﬁcation of ML systems under different rare settings (e.g., different lighting conditions for self-driving cars) to ensure the security and safety of ML systems. Prof. Jana is working on creating effective tools and techniques to detect and eliminate corner-case vulnerabilities through systematic testing and verification of ML systems.