Daniel (Bochen) Tan

Brief CV

  • Ph.D. Computer Science, UCLA, in pursuit now
  • Advisor: Dr. Jason Cong, PI of VAST Lab
  • B.S. Electrical Engineering, Peking University, 2019
  • Exchange to the University of Melbourne, 2018
  • Exchange to Stanford University, 2017
  • Extended CV on LinkedIn
  • Video Channels on YouTube and bilibili
  • Email bctan AT cs.ucla.edu

Research

Sept. 2019 -
Now
Architecture and Design Automation for Quantum Computing
Quantum computing (QC) has been shown, in theory, to hold huge advantage over classical computing. However, there remains many engineering challenges in the implementation of real-world QC applications. The topics that we are particularly interested in are those concerning QC architecture and design automation, which connect algorithms and devices. The task is to transform the quantum program to be executable on actual quantum hardware and, at the same time, overcome some limitations of near-term devices, e.g. volatile qubits and error-prone quantum gates.

Media

Aug. 2020 UCLA Computer Scientists Set Benchmarks to Optimize Quantum Computer Performance
News article about our paper Optimality Study of Existing Quantum Computing Layout Synthesis Tools, where we constructed quantum mapping examples with known optimal, i.e., QUEKO benchmarks, and revealed large optimality gaps of a few leading quantum computing compilers.

Publications

In ACM Reference Format

Nov. 2020 Bochen Tan and Jason Cong. 2020. Optimal Layout Synthesis for Quantum Computing. In 2020 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), November 2 - 5, 2020, Virtual Event, USA. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3400302.3415620 arXiv:cs.AR/2007.15671
Sept. 2020 Daniel Bochen Tan and Jason Cong. 2020. Layout Synthesis for Quantum Computing: Measure, then Improve. In 4th International Workshop on Quantum Computation (IWQC), September 23 – 24, 2020, Virtual Event. [video]
July 2020 Bochen Tan and Jason Cong. 2020. Optimality Study of Existing Quantum Computing Layout Synthesis Tools. IEEE Trans. Comput. DOI: https://doi.org/10.1109/TC.2020.3009140 arXiv:quant-ph/2002.09783

Talks

Sept. 2020 Layout Synthesis for Quantum Computing: Gap Analysis and Optimal Solutions.
In Quantum Economic Development Consortium (QED-C) Student e-Poster Session IV, September 22, 2020. [video]
Sept. 2020 Layout Synthesis for Quantum Computing: Gap Analysis and Optimal Solutions.
Talk given at Keio University on invitation from Dr. Rodney Van Meter, September 21, 2020.
July 2020 Layout Synthesis for Quantum Computing
Talk given at School of Computer Science and Technology, University of Science and Technology of China
Summary by Yuhao Meng and Dr. Yu Zhang

Teaching Experience

Awards and Grants

Aug. 2020 Microgrant (at $4k)
From Unitary Fund to 'develop and open source the Optimal Layout Synthesizer for Quantum Computing, OLSQ. This compiler beats other benchmarks on optimal layout of computational qubits onto physical qubits.'
Aug. 2020 Best Poster Award (< 5% among Young Fellows)
In Young Fellow Program, 2020 57th ACM/IEEE Design Automation Conference (DAC) [Two-minute poster video]
Dec. 2016 China National Scholarship, 2015-2016 (~ 0.2% among all undergraduates)
Awarded by Ministry of Education of People's Republic of China