Olive Franzese

About Me

• PhD Candidate in applied cryptography at Northwestern, defending Dec 2024 (advisor: Xiao Wang)
• Former Visiting Professor at Reed College (1-semester appointment Spring 2023)
• Postdoc at University of Toronto, starting Jan 2025 (advisor: Nicolas Papernot)
• Google Scholar.

Research

My research is at the intersection of concretely efficient cryptography and machine learning. I am primarily interested in designing methods that use zero-knowledge proofs and secure multiparty computation to audit and verify the trustworthyness of machine learning models.

Cryptographic verification creates an avenue of accountability for ML service providers, even in the presence of misaligned incentives and/or adversarial behavior. It also allows service providers build trust by actively attesting that their models are trustworthy, without revealing any information about user data or proprietary model parameters. My published works in this line include methods for cryptographic verification of fairness using zero-knowledge proofs (ICLR ’23, Alan Turing Institute Top 10 Research Highlight of 2022-23), verified confidentiality and robustness in distributed model training via secure multiparty computation (NeuRIPS ’23), and efficient zero-knowledge proof building blocks (CCS ’21).

I have also worked in data-driven computational biology. I designed an ML method to improve clinical accessibility of mutational-signature-based cancer diagnostics (RECOMB ’21), algorithms for extracting signaling pathways from protein-protein interaction data (PLoS Comp Biol 2019), and analyzed a method for systematic experiment planning (Bioinformatics 2018).

I am an NSF GRFP fellow, and a National Cancer Institute CRTA recipient.

Teaching

Teaching is the thing that drives me to be an academic. The quality of my teaching is extremely important to me. Below are some of my experiences in undergraduate teaching and mentorship.

Visiting Professor, Reed College

• CSCI 221: COMPUTER SCIENCE FUNDAMENTALS II
  • an introductory systems-level programming course in C, MIPS Assembly, and C++.
  • selected student comments (full course evaluation here):

    • “I loved the energy of the lectures and the learning environment, the professor’s enthusiasm in providing help in lab, and the effectiveness of the assignment material at both closely matching the subjects discussed in lecture while providing sufficient practice to reinforce learning. The midterm exam was also extremely well-designed and well- structured - in fact, it felt like one of the most accurately balanced exams I have taken at Reed. I would retain the majority of the course structure and policies - I feel that the course accomplished exactly what it is meant to, with the appropriate scope at all steps of the process, and with effective measures in place to ensure students have a good experience.”

    • “I liked Olive’s teaching style! She was always super prepared, organized, cheerful, and engaged during lectures and labs. The policy of going and offering help unsolicited during labs was very helpful for folks such as I who struggle asking for help for any reason ever. Asking questions unsolicited during lecture helped for this exact same reason, it never felt like being singled out or stressful as the answer “I don’t know” was never punished. It was clear that she cares, not just whether the students learned the material, but also whether we [were] generally mentally well. I felt respected and appreciated every day I showed up to class, and though I’ve stopped going out of my way to give a 110 percent in college, this class was the one exception.”

Research Advisees

• Elle Wen (Undergraduate Thesis 2023-24) - Fuzzy private set intersection for satellite collision detection
• Lydia Longfritz (Summer 2023) - Secure multiparty computation for privacy-preserving mutational signature analysis
• John Poole (Undergraduate Thesis 2022-23) - Cellular automata simulation of cancer ecology

Graduate TA, Northwestern & University of Maryland

• CS 307: INTRODUCTION TO CRYPTOGRAPHY (2021)
• CMSC 132: OBJECT-ORIENTED PROGRAMMING II (2019)
• CMSC 131: OBJECT-ORIENTED PROGRAMMING I (2018)

Undergraduate Teaching Assistant, Reed College

• MATH 121: INTRODUCTION TO COMPUTING (2017-2019)

Publications

1. Olive Franzese, Adam Dziedzic, Christopher Choquette-Choo, Mark R Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang. Doubly Robust Peer-To-Peer Learning Protocol. NeurIPS 2023.
   
2. Ali Shahin Shamsabadi, Sierra Calanda Wyllie, Olive Franzese, Natalie Dullerud, Sébastien Gambs, Nicolas Papernot, Xiao Wang, Adrian Weller. Confidential-PROFITT: Confidential PROof of FaIr Training of Trees. ICLR 2023. Notable Top 5% Paper. Alan Turing Institute Top 10 Research Project 2022-23.
   
3. Olive Franzese, Jason Fan, Roded Sharan, Mark D. M. Leiserson. ScalpelSig Designs Targeted Genomic Panels from Data to Detect Activity of Mutational Signatures. J. Comput. Biol. 29(1): 56-73 (2022).
   
4. Olive Franzese, Jonathan Katz, Steve Lu, Rafail Ostrovsky, Xiao Wang, Chenkai Weng. Constant-Overhead Zero-Knowledge for RAM Programs. CCS 2021: 178-191.
   
5. Olive Franzese, Adam Groce, T. M. Murali, Anna M. Ritz. Hypergraph-based connectivity measures for signaling pathway topologies. PLoS Comput. Biol. 15(10) (2019).
   
6. Aditya Pratapa, Neil Adames, Pavel K. Brazhnik, Olive Franzese, John J. Tyson, Jean Peccoud, T. M. Murali. CrossPlan: systematic planning of genetic crosses to validate mathematical models. Bioinformatics. 34(13): 2237-2244 (2018).
   
7. Seongjin Yu, Naoki Tajiri, Olive Franzese, Max Franzblau, Eunkyung Bae, Simon Platt, Yuji Kaneko, Cesar V Borlongan. Stem cell-like dog placenta cells afford neuroprotection against ischemic stroke model via heat shock protein upregulation. PLoS One. 2013 Sep 25;8(9):e76329. doi: 10.1371/journal.pone.0076329.
   
8. Yuji Kaneko, Naoki Tajiri, SeongJin Yu, Takuro Hayashi, Christine E Stahl, Eunkyung Bae, Humberto Mestre, Olive Franzese, Antonio Rodrigues Jr, Maria C Rodrigues, Hiroto Ishikawa, Kazutaka Shinozuka, Whitney Hethorn, Nathan Weinbren, Loren E Glover, Jun Tan, Anilkumar Harapanahalli Achyuta, Harry Van Loveren, Paul R Sanberg, Sundaram Shivsankar, Cesar V Borlongan. Nestin overexpression precedes caspase-3 upregulation in rats exposed to controlled cortical impact traumatic brain injury. Cell Medicine. 2012 Jul;4(2):55-63.
   
9. Hiroto Ishikawa, Mathew Caputo, Olive Franzese, Nathan L Weinbren, Adam Slakter, Milan Patel, Christine E Stahl, Maria Alejandra Jacotte, Sandra Acosta, Giorgio Franyuti, Kazutaka Shinozuka, Naoki Tajiri, Harry van Loveren, Yuji Kaneko, Cesar V Borlongan. Stroke in the Eye of the Beholder. Medical Hypotheses. 2013 Apr 1;80(4):411-5.