About

Adam Smith is a Professor of Computer Science and Engineering at Boston University. His research interests lie in data privacy and cryptography, and their connections to machine learning, statistics, information theory, and quantum computing. He obtained his Ph.D. from MIT in 2004 and has held visiting positions at the Weizmann Institute of Science, UCLA, and Harvard. He previously was a Professor of Computer Science and Engineering at Penn State. He has received several awards, including a Presidential Early Career Award for Scientists and Engineers (PECASE) in 2009, the 2016 Theory of Cryptography Test of Time award, the 2019 Eurocrypt Test of Time award, and the 2017 Gödel Prize.

Research topics

• Computer Science
• Physics
• Quantum mechanics
• Mathematics
• Artificial Intelligence
• Thermodynamics
• Statistics
• Theoretical physics
• Psychology

Selected publications

• Data for "Realizing topologically ordered states on a quantum processor"

  Science · 2021 · 463 citations

  • Physics
  • Quantum mechanics
  • Theoretical physics

  Data and code used in "Realizing topologically ordered states on a quantum processor," Satzinger et al. (2021), preprint at https://arxiv.org/abs/2104.01180

  DOI

• Real- and Imaginary-Time Evolution with Compressed Quantum Circuits

  PRX Quantum · 2021 · 199 citations

  • Computer Science
  • Computer Science
  • Physics

  The current generation of noisy intermediate-scale quantum computers introduces new opportunities to study quantum many-body systems. In this paper, we show that quantum circuits can provide a dramatically more efficient representation than current classical numerics of the quantum states generated under nonequilibrium quantum dynamics. For quantum circuits, we perform both real- and imaginary-time evolution using an optimization algorithm that is feasible on near-term quantum computers. We benchmark the algorithms by finding the ground state and simulating a global quench of the transverse-field Ising model with a longitudinal field on a classical computer. Furthermore, we implement (classically optimized) gates on a quantum processing unit and demonstrate that our algorithm effectively captures real-time evolution.

  DOI

• Reusable Fuzzy Extractors for Low-Entropy Distributions

  Journal of Cryptology · 2020 · 50 citations

  Senior authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Mathematics
  PublisherOA PDFDOI

Recent grants

• Algorithms for Private Data Analysis

  NSF · $282k · 2007–2011

• CAREER: Rigorous Foundations for Data Privacy

  NSF · $400k · 2008–2014

• BIGDATA: F: DKA: Scalable, Private Algorithms for Continual Data Analysis

  NSF · $21k · 2017–2018

• BIGDATA: F: DKA: Scalable, Private Algorithms for Continual Data Analysis

  NSF · $500k · 2014–2018

• AF: Medium: Collaborative Research: Foundations of Adaptive Data Analysis

  NSF · $260k · 2018–2022

Frequent coauthors

• Frank Pollmann

  Munich Center for Quantum Science and Technology

  59 shared

• Elza Erkip

  49 shared

• Marc Apter

  Institute of Electrical and Electronics Engineers

  49 shared

• Information Technology

  Conference Board

  49 shared

• Shannon Theory

  Rutgers, The State University of New Jersey

  49 shared

• Aylin Yener

  49 shared

• Eileen Lach

  University of Nottingham

  49 shared

• Patrick Mahoney

  University of Kent

  49 shared

Education

• Ph.D.

  MIT

  2004

Awards & honors

• Presidential Early Career Award for Scientists and Engineers…
• Theory of Cryptography Test of Time award (2016)
• Eurocrypt Test of Time award (2019)
• Gödel Prize (2017)

Similar researchers at Boston University

• Alexa S. Beiserh-188
• David Boash-156
• Benjamin Sovacoolh-143
• Kathryn L. Lunettah-132
• Ranga Mynenih-130