Saeid Tizpaz-Niari

According to our database, Saeid Tizpaz-Niari authored at least 31 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Timing Side-Channel Mitigation via Automated Program Repair.

Haifeng Ruan, Yannic Noller, Saeid Tizpaz-Niari, Sudipta Chattopadhyay, Abhik Roychoudhury

ACM Trans. Softw. Eng. Methodol., November, 2024

Summary of the 1st Interpretability and Robustness in Neural Software Engineering (InteNSE 2023).

Reyhaneh Jabbarvand, Saeid Tizpaz-Niari, Earl T. Barr, Satish Chandra

ACM SIGSOFT Softw. Eng. Notes, January, 2024

Probabilistic Guarantees for Practical LIA Loop Invariant Automation.

Ashish Kumar, Jilaun Zhang, Saeid Tizpaz-Niari, Gang Tan

CoRR, 2024

Metamorphic Debugging for Accountable Software.

Saeid Tizpaz-Niari, Shiva Darian, Ashutosh Trivedi

CoRR, 2024

FairLay-ML: Intuitive Debugging of Fairness in Data-Driven Social-Critical Software.

Normen Yu, Luciana Carreon, Gang Tan, Saeid Tizpaz-Niari

CoRR, 2024

Predicting Fairness of ML Software Configuration.

Salvador Robles Herrera, Verya Monjezi, Vladik Kreinovich, Ashutosh Trivedi, Saeid Tizpaz-Niari

CoRR, 2024

Data Science in a Mathematics Classroom: Lessons on AI Fairness.

Berenice Sotelo, Kirsten Wieseman, Saeid Tizpaz-Niari

Proceedings of the 25th Annual Conference on Information Technology Education, 2024

Predicting Fairness of ML Software Configurations.

Salvador Robles Herrera, Verya Monjezi, Vladik Kreinovich, Ashutosh Trivedi, Saeid Tizpaz-Niari

Proceedings of the 20th International Conference on Predictive Models and Data Analytics in Software Engineering, 2024

NeuFair: Neural Network Fairness Repair with Dropout.

Vishnu Asutosh Dasu, Ashish Kumar, Saeid Tizpaz-Niari, Gang Tan

Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2024

Causal Graph Fuzzing for Fair ML Sofware Development.

Verya Monjezi, Ashish Kumar, Gang Tan, Ashutosh Trivedi, Saeid Tizpaz-Niari

Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings, 2024

Worst-Case Convergence Time of ML Algorithms via Extreme Value Theory.

Saeid Tizpaz-Niari, Sriram Sankaranarayanan

Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering, 2024

2023

Detecting Unseen Anomalies in Network Systems by Leveraging Neural Networks.

Mohammad J. Hashemi, Eric Keller, Saeid Tizpaz-Niari

IEEE Trans. Netw. Serv. Manag., September, 2023

On the Potential and Limitations of Few-Shot In-Context Learning to Generate Metamorphic Specifications for Tax Preparation Software.

Dananjay Srinivas, Rohan Das, Saeid Tizpaz-Niari, Ashutosh Trivedi, Maria Leonor Pacheco

CoRR, 2023

FairLay-ML: Intuitive Remedies for Unfairness in Data-Driven Social-Critical Algorithms.

Normen Yu, Gang Tan, Saeid Tizpaz-Niari

CoRR, 2023

Fast - Asymptotically Optimal - Methods for Determining the Optimal Number of Features.

Saeid Tizpaz-Niari, Luc Longpré, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2023

Metamorphic Testing and Debugging of Tax Preparation Software.

Saeid Tizpaz-Niari, Verya Monjezi, Morgan Wagner, Shiva Darian, Krystia Reed, Ashutosh Trivedi

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: Software Engineering in Society, 2023

Information-Theoretic Testing and Debugging of Fairness Defects in Deep Neural Networks.

Verya Monjezi, Ashutosh Trivedi, Gang Tan, Saeid Tizpaz-Niari

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

How to Detect (and Analyze) Independent Subsystems of a Black-Box (or Grey-Box) System.

Saeid Tizpaz-Niari, Olga Kosheleva, Vladik Kreinovich

Proceedings of the Uncertainty, Constraints, and Decision Making, 2023

Over-Measurement Paradox: Suspension of Thermonuclear Research Center and Need to Update Standards.

Hector A. Reyes, Saeid Tizpaz-Niari, Vladik Kreinovich

Proceedings of the Uncertainty, Constraints, and Decision Making, 2023

What Is a Natural Probability Distribution on the Class of All Continuous Functions: Maximum Entropy Approach Leads to Wiener Measure.

Vladik Kreinovich, Saeid Tizpaz-Niari

Proceedings of the Uncertainty, Constraints, and Decision Making, 2023

2022

Metamorphic Testing and Debugging of Tax Preparation Software.

Saeid Tizpaz-Niari, Morgan Wagner, Shiva Darian, Krystia Reed, Ashutosh Trivedi

CoRR, 2022

Fairness-aware Configuration of Machine Learning Libraries.

Saeid Tizpaz-Niari, Ashish Kumar, Gang Tan, Ashutosh Trivedi

Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

2021

Quantitative estimation of side-channel leaks with neural networks.

Saeid Tizpaz-Niari, Pavol Cerný, Sriram Sankaranarayanan, Ashutosh Trivedi

Int. J. Softw. Tools Technol. Transf., 2021

QFuzz: quantitative fuzzing for side channels.

Yannic Noller, Saeid Tizpaz-Niari

Proceedings of the ISSTA '21: 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2021

2020

Data-Driven Debugging for Functional Side Channels.

Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi

Proceedings of the 27th Annual Network and Distributed System Security Symposium, 2020

Detecting and understanding real-world differential performance bugs in machine learning libraries.

Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi

Proceedings of the ISSTA '20: 29th ACM SIGSOFT International Symposium on Software Testing and Analysis, 2020

2019

Efficient Detection and Quantification of Timing Leaks with Neural Networks.

Saeid Tizpaz-Niari, Pavol Cerný, Sriram Sankaranarayanan, Ashutosh Trivedi

Proceedings of the Runtime Verification - 19th International Conference, 2019

Quantitative Mitigation of Timing Side Channels.

Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi

Proceedings of the Computer Aided Verification - 31st International Conference, 2019

2018

Differential Performance Debugging With Discriminant Regression Trees.

Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Ashutosh Trivedi

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Discriminating Traces with Time.

Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Sriram Sankaranarayanan, Ashutosh Trivedi

Proceedings of the Tools and Algorithms for the Construction and Analysis of Systems, 2017

2013

Verification of OSPF vulnerabilities by colored Petri net.

Saeid Tizpaz-Niari, Amir Hossein Jahangir

Proceedings of the 6th International Conference on Security of Information and Networks, 2013