Justin Del Vecchio, PhD

Assistant Professor

Justin DelVecchio professor at Canisius College
  • Ph.D. - Computer Science & Engineering - University at Buffalo
  • M.S. - Computer Science & Engineering - University at Buffalo
  • B.A. - Computer Science - University at Buffalo
SH 1048

Justin Del Vecchio, PhD, comes to Canisius college with over 20 years of industry experience. He most recently worked for CUBRC Inc., a local defense contractor - a leader in data fusion and analytics. Del Vecchio was a senior program manager that led a team of engineers and interns to develop software solutions for government and private industry. Some of these organizations include the Office of Naval Research, IARPA, Army Corps of Engineers, and Army I2WD.

His projects primarily focused upon information fusion of cyber data sources using machine learning algorithms, and the translation of multiple disparate data sources into situational awareness. Del Vecchio’s dissertation focused upon Android malware analysis. His research helped identify immutable characteristics of malware useful in the identification of new, unseen cyber threats. He has been an adjunct at Canisius University since Fall 2020 and will be a full time Assistant professor in the Computer Science department in Fall 2022. He lives in Snyder with his wife, and three boys.


Del Vecchio, J.l, Ko, S. Y., & Ziarek, L. (2020). Representing string computations as graphs for classifying malware. Proceedings - 2020 IEEE/ACM 7th International Conference on Mobile Software Engineering and Systems, MOBILESoft 2020, 120–131. https://doi.org/10.1145/3387905.3388595

Del Vecchio, J. M., Perkins, T. K., Tauer, G., Czerniejewski, A., & Logan, J. (2018). Customizable fusion of violent event mentions in heterogeneous data. 32. https://doi.org/10.1117/12.2307047

Del Vecchio, J., Shen, F., Yee, K. M., Wang, B., Ko, S. Y., & Ziarek, L. (2016). String analysis of android applications. Proceedings - 2015 30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015, 680–685. https://doi.org/10.1109/ASE.2015.2