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• Ph D in Electrical Engineering/Computer Science, University of Colorado at Boulder (2020)

• Fairness-aware Configuration of Machine Learning Libraries ICSE (in press), Saeid Tizpaz Niari, Ashish Kumar, Gang Tab, Ashutosh Trevidi.
• What Is a Natural Probability Distribution on the Class of All Continuous Functions: Maximum Entropy Approach Leads to Wiener Measure Proceedings of the 15th International Workshop on Constraint Programming and Decision Making CoProD'2022, Halifax, Nova Scotia, Canada, May 30, 2022 (2022), Vladik Y. Kreinovich, Saeid Tizpaz Niari.
• QFuzz: Quantitative Fuzzing for Side Channels ISSTA (2021), Yannic Noller, Saeid Tizpaz-Niari.
• Quantitative Estimation of Side-Channel Leaks with Neural Networks STTT (2021), Saeid Tizpaz Niari.
• Data-Driven Debugging for Functional Side Channels NDSS (2020), Saeid Tizpaz Niari, Pavol Cerny, Ashutosh Trivedi.
• Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries ISSTA (2020), Saeid Tizpaz Niari, \vCern\'y, Pavol, Ashutosh Trivedi.
• Efficient detection and quantification of timing leaks with neural networks RV (2019), Saeid Tizpaz Niari, Pavol Cerny, Sriram Sankaranarayanan, Ashutosh Trivedi.
• Quantitative mitigation of timing side channels CAV (2019), Saeid Tizpaz Niari, Pavol Cerny, Ashutosh Trivedi.
• Differential performance debugging with discriminant regression trees AAAI 32 1 (2018), Saeid Tizpaz Niari, Pavol Cerny, Bor-Yuh E. Chang, Ashutosh Trivedi.
• Discriminating traces with time TACAS (2017), Saeid Tizpaz Niari, Pavol Cerny, Bor-Yuh E. Chang, Sriram Sankaranarayanan, Ashutosh Trivedi.

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