Saeid Tizpaz-Niari

53 papers A* 7A 3B 2C 1Misc 1Journal 29Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
On the Robustness of Fairness Practices: A Causal Framework for Systematic Evaluation.
CoRR
Verya Monjezi, Ashish Kumar, Ashutosh Trivedi, Gang Tan, Saeid Tizpaz-Niari
2025 J jnl
An LLM Agentic Approach for Legal-Critical Software: A Case Study for Tax Prep Software.
CoRR
Sina Gogani-Khiabani, Ashutosh Trivedi, Diptikalyan Saha, Saeid Tizpaz-Niari
2025 J jnl
Attention Pruning: Automated Fairness Repair of Language Models via Surrogate Simulated Annealing.
CoRR
Vishnu Asutosh Dasu, Md. Rafi Ur Rashid, Vipul Gupta, Saeid Tizpaz-Niari, Gang Tan
2025 — conf
FairLay-ML: Intuitive Debugging of Fairness in Data-Driven Social-Critical Software.
ICSE Companion
Normen Yu, Luciana Carreon, Gang Tan, Saeid Tizpaz-Niari
2025 A* conf
Fairness Testing Through Extreme Value Theory.
ICSE
Verya Monjezi, Ashutosh Trivedi, Vladik Kreinovich, Saeid Tizpaz-Niari
2025 J jnl
Fairness Testing through Extreme Value Theory.
CoRR
Verya Monjezi, Ashutosh Trivedi, Vladik Kreinovich, Saeid Tizpaz-Niari
2025 A* conf
Risk Estimation in Differential Fuzzing via Extreme Value Theory.
ASE
Rafael Baez, Alejandro Olivas, Nathan K. Diamond, Marcelo F. Frias, Yannic Noller, Saeid Tizpaz-Niari
2025 J jnl
Risk Estimation in Differential Fuzzing via Extreme Value Theory.
CoRR
Rafael Baez, Alejandro Olivas, Nathan K. Diamond, Marcelo F. Frias, Yannic Noller, Saeid Tizpaz-Niari
2025 J jnl
Technical Challenges in Maintaining Tax Prep Software with Large Language Models.
CoRR
Sina Gogani-Khiabani, Varsha Dewangan, Nina Olson, Ashutosh Trivedi, Saeid Tizpaz-Niari
2025 A* conf
Uncovering Discrimination Clusters: Quantifying and Explaining Systematic Fairness Violations.
ASE
Ranit Debnath Akash, Ashish Kumar, Verya Monjezi, Ashutosh Trivedi, Gang Tan, Saeid Tizpaz-Niari
2025 J jnl
Uncovering Discrimination Clusters: Quantifying and Explaining Systematic Fairness Violations.
CoRR
Ranit Debnath Akash, Ashish Kumar, Verya Monjezi, Ashutosh Trivedi, Gang Tan, Saeid Tizpaz-Niari
2024 — conf
Causal Graph Fuzzing for Fair ML Sofware Development.
ICSE Companion
Verya Monjezi, Ashish Kumar, Gang Tan, Ashutosh Trivedi, Saeid Tizpaz-Niari
2024 Misc conf
Data Science in a Mathematics Classroom: Lessons on AI Fairness.
SIGITE
Berenice Sotelo, Kirsten Wieseman, Saeid Tizpaz-Niari
2024 J jnl
FairLay-ML: Intuitive Debugging of Fairness in Data-Driven Social-Critical Software.
CoRR
Normen Yu, Luciana Carreon, Gang Tan, Saeid Tizpaz-Niari
2024 J jnl
Metamorphic Debugging for Accountable Software.
CoRR
Saeid Tizpaz-Niari, Shiva Darian, Ashutosh Trivedi
2024 A conf
NeuFair: Neural Network Fairness Repair with Dropout.
ISSTA
Vishnu Asutosh Dasu, Ashish Kumar, Saeid Tizpaz-Niari, Gang Tan
2024 J jnl
NeuFair: Neural Network Fairness Repair with Dropout.
CoRR
Vishnu Asutosh Dasu, Ashish Kumar, Saeid Tizpaz-Niari, Gang Tan
2024 J jnl
Predicting Fairness of ML Software Configuration.
CoRR
Salvador Robles Herrera, Verya Monjezi, Vladik Kreinovich, Ashutosh Trivedi, Saeid Tizpaz-Niari
2024 — conf
Predicting Fairness of ML Software Configurations.
PROMISE
Salvador Robles Herrera, Verya Monjezi, Vladik Kreinovich, Ashutosh Trivedi, Saeid Tizpaz-Niari
2024 J jnl
Probabilistic Guarantees for Practical LIA Loop Invariant Automation.
CoRR
Ashish Kumar, Jilaun Zhang, Saeid Tizpaz-Niari, Gang Tan
2024 J jnl
Summary of the 1st Interpretability and Robustness in Neural Software Engineering (InteNSE 2023).
ACM SIGSOFT Softw. Eng. Notes
Reyhaneh Jabbarvand, Saeid Tizpaz-Niari, Earl T. Barr, Satish Chandra
2024 J jnl
Timing Side-Channel Mitigation via Automated Program Repair.
ACM Trans. Softw. Eng. Methodol.
Haifeng Ruan, Yannic Noller, Saeid Tizpaz-Niari, Sudipta Chattopadhyay, Abhik Roychoudhury
2024 B conf
Worst-Case Convergence Time of ML Algorithms via Extreme Value Theory.
CAIN
Saeid Tizpaz-Niari, Sriram Sankaranarayanan
2024 J jnl
Worst-Case Convergence Time of ML Algorithms via Extreme Value Theory.
CoRR
Saeid Tizpaz-Niari, Sriram Sankaranarayanan
2023 J jnl
Detecting Unseen Anomalies in Network Systems by Leveraging Neural Networks.
IEEE Trans. Netw. Serv. Manag.
Mohammad J. Hashemi, Eric Keller, Saeid Tizpaz-Niari
2023 J jnl
FairLay-ML: Intuitive Remedies for Unfairness in Data-Driven Social-Critical Algorithms.
CoRR
Normen Yu, Gang Tan, Saeid Tizpaz-Niari
2023 — conf
Fast - Asymptotically Optimal - Methods for Determining the Optimal Number of Features.
IUKM (1)
Saeid Tizpaz-Niari, Luc Longpré, Olga Kosheleva, Vladik Kreinovich
2023 — ch.
How to Detect (and Analyze) Independent Subsystems of a Black-Box (or Grey-Box) System.
Uncertainty, Constraints, and Decision Making
Saeid Tizpaz-Niari, Olga Kosheleva, Vladik Kreinovich
2023 A* conf
Information-Theoretic Testing and Debugging of Fairness Defects in Deep Neural Networks.
ICSE
Verya Monjezi, Ashutosh Trivedi, Gang Tan, Saeid Tizpaz-Niari
2023 J jnl
Information-Theoretic Testing and Debugging of Fairness Defects in Deep Neural Networks.
CoRR
Verya Monjezi, Ashutosh Trivedi, Gang Tan, Saeid Tizpaz-Niari
2023 — conf
Metamorphic Testing and Debugging of Tax Preparation Software.
ICSE (SEIS)
Saeid Tizpaz-Niari, Verya Monjezi, Morgan Wagner, Shiva Darian, Krystia Reed, Ashutosh Trivedi
2023 J jnl
On the Potential and Limitations of Few-Shot In-Context Learning to Generate Metamorphic Specifications for Tax Preparation Software.
CoRR
Dananjay Srinivas, Rohan Das, Saeid Tizpaz-Niari, Ashutosh Trivedi, Maria Leonor Pacheco
2023 — ch.
Over-Measurement Paradox: Suspension of Thermonuclear Research Center and Need to Update Standards.
Uncertainty, Constraints, and Decision Making
Hector A. Reyes, Saeid Tizpaz-Niari, Vladik Kreinovich
2023 — ch.
What Is a Natural Probability Distribution on the Class of All Continuous Functions: Maximum Entropy Approach Leads to Wiener Measure.
Uncertainty, Constraints, and Decision Making
Vladik Kreinovich, Saeid Tizpaz-Niari
2022 A* conf
Fairness-aware Configuration of Machine Learning Libraries.
ICSE
Saeid Tizpaz-Niari, Ashish Kumar, Gang Tan, Ashutosh Trivedi
2022 J jnl
Fairness-aware Configuration of Machine Learning Libraries.
CoRR
Saeid Tizpaz-Niari, Ashish Kumar, Gang Tan, Ashutosh Trivedi
2022 J jnl
Metamorphic Testing and Debugging of Tax Preparation Software.
CoRR
Saeid Tizpaz-Niari, Morgan Wagner, Shiva Darian, Krystia Reed, Ashutosh Trivedi
2021 J jnl
QFuzz: Quantitative Fuzzing for Side Channels.
CoRR
Yannic Noller, Saeid Tizpaz-Niari
2021 A conf
QFuzz: quantitative fuzzing for side channels.
ISSTA
Yannic Noller, Saeid Tizpaz-Niari
2021 J jnl
Quantitative estimation of side-channel leaks with neural networks.
Int. J. Softw. Tools Technol. Transf.
Saeid Tizpaz-Niari, Pavol Cerný, Sriram Sankaranarayanan, Ashutosh Trivedi
2020 A* conf
Data-Driven Debugging for Functional Side Channels.
NDSS
Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi
2020 J jnl
Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries.
CoRR
Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi
2020 A conf
Detecting and understanding real-world differential performance bugs in machine learning libraries.
ISSTA
Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi
2019 B conf
Efficient Detection and Quantification of Timing Leaks with Neural Networks.
RV
Saeid Tizpaz-Niari, Pavol Cerný, Sriram Sankaranarayanan, Ashutosh Trivedi
2019 J jnl
Efficient Detection and Quantification of Timing Leaks with Neural Networks.
CoRR
Saeid Tizpaz-Niari, Pavol Cerný, Sriram Sankaranarayanan, Ashutosh Trivedi
2019 — conf
Quantitative Mitigation of Timing Side Channels.
CAV (1)
Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi
2019 J jnl
Quantitative Mitigation of Timing Side Channels.
CoRR
Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi
2018 J jnl
Data-Driven Debugging for Functional Side Channels.
CoRR
Saeid Tizpaz-Niari, Pavol Cerný, Ashutosh Trivedi
2018 A* conf
Differential Performance Debugging With Discriminant Regression Trees.
AAAI
Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Ashutosh Trivedi
2017 J jnl
Differential Performance Debugging with Discriminant Regression Trees.
CoRR
Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Ashutosh Trivedi
2017 — conf
Discriminating Traces with Time.
TACAS (2)
Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Sriram Sankaranarayanan, Ashutosh Trivedi
2017 J jnl
Discriminating Traces with Time.
CoRR
Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Sriram Sankaranarayanan, Ashutosh Trivedi
2013 C conf
Verification of OSPF vulnerabilities by colored Petri net.
SIN
Saeid Tizpaz-Niari, Amir Hossein Jahangir