Benjamin Tan ,
Ph.D.

Research Assistant Professor

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Benjamin Tan

Bio

I am currently working as a Research Assistant Professor at the New York University Center for Cybersecurity. My current research work involves hardware security and robustness of deep learning systems. I have also taught Computer Architecture and Organization. 

I was awarded a Ph.D. degree by the University of Auckland in 2019. My thesis features work in the space of security in heterogeneous multiprocessor systems.

I have research interests in embedded systems and computer architecture in general. I'm currently working on dealing with the trade-offs between performance, complexity, and security in the design of complex embedded systems on heterogeneous platforms. I also have interests in real-time issues (like time predictability). I'm also interested in the concept of hardware/software co-design.

I also have a passion for teaching and learning and have been fortunate to have been involved in undergraduate and graduate-level teaching activities, fronting labs, assisting with projects/assessment, in the delivery of tutorials, and as an instructor. I firmly believe in fostering independent thinking, and genuine interest in technology, and I've been trying to convince undergraduates to think "beyond the exam" and merely reducing courses to a list of content to memorize. I've also been working to encourage students in looking at their learning in early undergraduate years as providing them the toolbox for effective communication of technical ideas. 

Research Interests: Hardware security, electronic design automation, and machine learning

University of Auckland

Doctor of Philosophy, Computer Systems Engineering

Bachelors of Engineering (Hons), 1st Class, Computer Systems Engineering


K. Liu*, B. Tan*, R. Karri, S. Garg, "Training Data Poisoning in ML-CAD: Backdooring DL-based Lithographic Hotspot Detectors”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD)

B. Tan, R. Elnaggar, J. Fung, R. Karri, K. Chakrabarty, "Towards Hardware-based IP Monitoring for Run-time Vulnerability Detection and Mitigation in Systems-On-Chip", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD),

K. Liu, H. Yang, Y. Ma, B. Tan, B. Yu, E. F. Y. Young, R. Karri, S. Garg. 2020. Adversarial Perturbation Attacks on ML-based CAD: A Case Study on CNN-based Lithographic Hotspot Detection. ACM Trans. Des. Autom. Electron. Syst. (ACM TODAES) 25, 5, Article 48 (August 2020), 31 pages.


Current Projects, Research Labs, and Groups