Stan Peceny

Education and Work Experience

2025 Ph.D. Computer Science
GEORGIA INSTITUTE OF TECHNOLOGY
In May 2025, I earned my PhD in Computer Science from Georgia Tech’s School of Cybersecurity and Privacy, where I completed my dissertation titled "The Cryptographer’s Symphony: Composing Efficient and Secure Computation." I have broad interests across all areas of cryptography, with my doctoral research focused specifically on secure multi-party computation (MPC). I have authored several papers in this area, all aimed at improving the concrete efficiency of MPC protocols. My research advisor was Professor Vlad Kolesnikov.

In addition to my research at Georgia Tech, I have completed two research internships with Visa’s Advanced Cryptography team, mentored by Dr. Peter Rindal and Prof. Srinivasan Raghuraman (Palo Alto, Foster City); three research internships with Google’s Private Computing team, mentored by Prof. Mariana Raykova and Dr. Karn Seth (New York); and one research internship with Inpher, a start-up specializing in MPC, mentored by Dr. Mariya Georgieva (New York).
From 2017 to 2019, I worked as a software engineer at Inpher in New York, under the mentorship of Prof. Dimitar Jetchev (EPFL) and Prof. Nicolas Gama (University of Versailles).
2017 B.S. Computer Science
COLUMBIA UNIVERSITY
I hold a few patents.
Check out my talk on the research I conducted during one of my internships at Google in New York, including the open-sourced implementation. Note that performance has improved significantly since this talk was recorded. See the publication at EuroS&P 2024 for most up-to-date numbers.

Stan Peceny

Education and Work Experience

GEORGIA INSTITUTE OF TECHNOLOGY

COLUMBIA UNIVERSITY

Peer-reviewed Publications & Talks

Cryptography (**authorship is alphabetical in cryptography and theory)

Crypto, 2025 (Santa Barbara, CA)

Kolesnikov, V., Peceny, S., Raghuraman, S., Rindal, P.:
Stationary Syndrome Decoding for Improved PCGs.

ASIACCS, 2025

Agarwal, A., Peceny, S., Raykova, M., Schoppmann, P., Seth, K.:
Prior-Based Label Differential Privacy via Secure Two-Party Computation.

Public Key Cryptography, 2025 (Roros, Norway)

Peceny, S., Raghuraman, S., Rindal, P., Shah, H.:
Efficient Permutation Correlations and Batched Random Access for Two-Party Computation.

IEEE EuroS&P, 2024 (Vienna)

Agarwal, A., Peceny, S., Raykova, M., Schoppmann, P., Seth, K.:
Communication-Efficient Secure Logistic Regression.

CSCML 2023 and extended version in Cryptography & Communications 2024

Kolesnikov, V., Peceny, S., Trieu, N., Wang, X.:
Fast ORAM with Server-aided Preprocessing and Pragmatic Privacy-Efficiency Trade-off.

See my conference talk (will be uploaded soon).

Asiacrypt, 2021 (Singapore)

Heath, D., Kolesnikov, V., Peceny, S.:
Garbling, Stacked and Staggered: Faster k-out-of-n Garbled Function Evaluation.

See my conference talk.

Public Key Cryptography, 2021 (Edinburgh)

Heath, D., Kolesnikov, V., Peceny, S.:
Masked Triples: Amortizing Multiplication Triples across Conditionals.

See my conference talk.

Asiacrypt, 2020 (Daejeon)

Heath, D., Kolesnikov, V., Peceny, S.:
MOTIF: (Almost) Free Branching in GMW via Vector-Scalar Multiplication.

See my conference talk.

Financial Cryptography, 2018 (Curacao)

Boura, C., Chillotti, I., Gama, N., Jetchev, D., Peceny, S., Petric, A.:
High-precision privacy-preserving real-valued function evaluation.

Cryptography & Security

ACM CCS, 2023 (Copenhagen)

Yang, Y., Peceny, S., Heath, D., Kolesnikov, V.:
Towards Generic MPC Compilers via Variable Instruction Set Architectures (VISAs).

Contact Info

Travels

Here are some of my trips in the United States!

Here are some of my international trips!

Stan Peceny

Education and Work Experience

GEORGIA INSTITUTE OF TECHNOLOGY

COLUMBIA UNIVERSITY

Peer-reviewed Publications & Talks

Cryptography (**authorship is alphabetical in cryptography and theory)

Crypto, 2025 (Santa Barbara, CA)

Kolesnikov, V., Peceny, S., Raghuraman, S., Rindal, P.: Stationary Syndrome Decoding for Improved PCGs.

ASIACCS, 2025

Agarwal, A., Peceny, S., Raykova, M., Schoppmann, P., Seth, K.: Prior-Based Label Differential Privacy via Secure Two-Party Computation.

Public Key Cryptography, 2025 (Roros, Norway)

Peceny, S., Raghuraman, S., Rindal, P., Shah, H.: Efficient Permutation Correlations and Batched Random Access for Two-Party Computation.

IEEE EuroS&P, 2024 (Vienna)

Agarwal, A., Peceny, S., Raykova, M., Schoppmann, P., Seth, K.: Communication-Efficient Secure Logistic Regression.

CSCML 2023 and extended version in Cryptography & Communications 2024

Kolesnikov, V., Peceny, S., Trieu, N., Wang, X.: Fast ORAM with Server-aided Preprocessing and Pragmatic Privacy-Efficiency Trade-off.

See my conference talk (will be uploaded soon).

Asiacrypt, 2021 (Singapore)

Heath, D., Kolesnikov, V., Peceny, S.: Garbling, Stacked and Staggered: Faster k-out-of-n Garbled Function Evaluation.

See my conference talk.

Public Key Cryptography, 2021 (Edinburgh)

Heath, D., Kolesnikov, V., Peceny, S.: Masked Triples: Amortizing Multiplication Triples across Conditionals.

See my conference talk.

Asiacrypt, 2020 (Daejeon)

Heath, D., Kolesnikov, V., Peceny, S.: MOTIF: (Almost) Free Branching in GMW via Vector-Scalar Multiplication.

See my conference talk.

Financial Cryptography, 2018 (Curacao)

Boura, C., Chillotti, I., Gama, N., Jetchev, D., Peceny, S., Petric, A.: High-precision privacy-preserving real-valued function evaluation.

Cryptography & Security

ACM CCS, 2023 (Copenhagen)

Yang, Y., Peceny, S., Heath, D., Kolesnikov, V.: Towards Generic MPC Compilers via Variable Instruction Set Architectures (VISAs).

Contact Info

Travels

Here are some of my trips in the United States!

Here are some of my international trips!

Non-contiguous

Trains

South

West

Americas

Africa

Europe

Middle East

Asia

Kolesnikov, V., Peceny, S., Raghuraman, S., Rindal, P.:
Stationary Syndrome Decoding for Improved PCGs.

Agarwal, A., Peceny, S., Raykova, M., Schoppmann, P., Seth, K.:
Prior-Based Label Differential Privacy via Secure Two-Party Computation.

Peceny, S., Raghuraman, S., Rindal, P., Shah, H.:
Efficient Permutation Correlations and Batched Random Access for Two-Party Computation.

Agarwal, A., Peceny, S., Raykova, M., Schoppmann, P., Seth, K.:
Communication-Efficient Secure Logistic Regression.

Kolesnikov, V., Peceny, S., Trieu, N., Wang, X.:
Fast ORAM with Server-aided Preprocessing and Pragmatic Privacy-Efficiency Trade-off.

Heath, D., Kolesnikov, V., Peceny, S.:
Garbling, Stacked and Staggered: Faster k-out-of-n Garbled Function Evaluation.

Heath, D., Kolesnikov, V., Peceny, S.:
Masked Triples: Amortizing Multiplication Triples across Conditionals.

Heath, D., Kolesnikov, V., Peceny, S.:
MOTIF: (Almost) Free Branching in GMW via Vector-Scalar Multiplication.

Boura, C., Chillotti, I., Gama, N., Jetchev, D., Peceny, S., Petric, A.:
High-precision privacy-preserving real-valued function evaluation.

Yang, Y., Peceny, S., Heath, D., Kolesnikov, V.:
Towards Generic MPC Compilers via Variable Instruction Set Architectures (VISAs).