Saeid Tizpaz-Niari
Assistant Professor
Department of Computer Science
Pronouns: He/Him/His
Contact
Building & Room:
SEO 1309
Address:
851 S. Morgan St., Chicago, IL 60607
Office Phone:
Email:
Related Sites:
About
Saeid Tizpaz-Niari is an Assistant Professor of Computer Science at the University of Illinois Chicago. He received his PhD in Computer Engineering from University of Colorado Boulder. His research interests are at the intersection of SE, AI, and cybersecurity. His research group builds debugging tools and techniques for safety-critical and socio-critical problems. His findings help discover multiple performance bugs in popular ML libraries, fairness bugs in the training process of ML algorithms, and timing side-channel vulnerabilities in critical Java libraries. Tizpaz-Niari has received two NSF awards from Secure and Trustworthy Cyberspace (SaTC) and Designing Accountable Software Systems (DASS) programs, a Gold Research Award from the ECEE department at CU Boulder, and the second prize for his submission to the First Microsoft Open-Source Challenge.
Selected Grants
NSF, DASS: Assessing Accountability of Tax Preparation Software Systems, PI
NSF, SaTC: CORE: Small: Detecting and Localizing Non-Functional Vulnerabilities in Machine Learning Libraries, PI
Selected Publications
Fairness Testing through Extreme Value Theory, Verya Monjezi*, Ashutosh Trivedi, Vladik Kreinovich, and Saeid Tizpaz-Niari, In IEEE/ACM 47th International Conference on Software Engineering (ICSE’25).
NeuFair: Neural Network Fairness Repair with Dropout, Vishnu Asutosh Dasu*, Ashish Kumar*, Saeid Tizpaz-Niari, and Gang Tan, In The ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA’24, acceptance rate: 20.6%).
Timing Side-Channel Mitigation via Automated Program Repair ,Haifeng Ruan*, Yannic Noller, Saeid Tizpaz-Niari, Sudipta Chattopadhyay, and Abhik Roychoudhury, In ACM Transactions on Software Engineering and Methodology, 2024 (TOSEM’24).
Information-Theoretic Testing and Debugging of Fairness Defects in Deep Neural Networks , Verya Monjezi*, Ashutosh Trivedi, Gang Tan, Saeid Tizpaz-Niari, In IEEE/ACM 45th International Conference on Software Engineering (ICSE’23, acceptance rate 26.1%).
Metamorphic Testing and Debugging of Tax Preparation Software , Saeid Tizpaz-Niari, Verya Monjezi*, Morgan Wagner*, Shiva Darian*, Krystia Reed, and Ashutosh Trivedi, In IEEE/ACM 45th International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS’23, acceptance rate 25%).
Fairness-aware Configuration of Machine Learning Libraries , Saeid Tizpaz-Niari, Ashish Kumar*, Gang Tan, and Ashutosh Trivedi, In IEEE/ACM 44th International Conference on Software Engineering (ICSE’22, acceptance rate 26%).
QFuzz: Quantitative Fuzzing for Side Channels , Yannic Noller and Saeid Tizpaz-Niari, In 30th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA’21, acceptance rate 21.8%).
Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries, Saeid Tizpaz-Niari, Pavol Cerny, and Ashutosh Trivedi, In the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA’20, acceptance rate 26%).
Data-driven Debugging for Functional Side Channels, Saeid Tizpaz-Niari, Pavol Cerny, and Ashutosh Trivedi, In 2020 ISOC Network and Distributed System Security Symposium (NDSS’20, acceptance rate 17.4%).
Quantitative Mitigation of Timing Side Channels , Saeid Tizpaz-Niari, Pavol Černý, and Ashutosh Trivedi, In Computer-Aid Verification (CAV’19). (acceptance rate: 26%).
Service to Community
- Mentoring Middle- and High- School during Summer as a part of NSF RET program: Dr. Tizpaz-Niari has mentored 7 teachers from the El Paso's local schools in the two years. The teachers have developed curriculums for their students to teach concepts through Responsible AI values. A publication, led by K-12 teachers has been accepted to he 25th Annual Conference on Information Technology Education.
- Mentoring Undergraduate Students as a part of NSF REU program: Dr. Tizpaz-Niari has mentored multiple Hispanic UG students through CAHSI institution, supported by NSF REU. REU students have published multiple research (e.g., PROMISE'24) and tool (ICSE'25) papers.
- Volunteer Tax Preparer: Dr. Tizpaz-Niari holds an advanced IRS certification to assist low-income families with their tax returns. and has since served Native-American community at El Paso (Ysleta del Sur Pueblo) as a volunteer tax preparer.
Education
Ph D in Electrical Engineering/Computer Science, University of Colorado Boulder (2020).