Jun-Chau Chien received the B.S. and M.S. degrees in Electrical Engineering from National Taiwan University in 2004 and 2006, respectively, and the Ph.D. degree in Electrical Engineering and Computer Sciences from University of California, Berkeley, in 2015. He is currently a post-doctoral research associate at Stanford University. He has held industrial positions at InvenSense, Xilinx, and HMicro working on mixed-signal integrated circuits for inertial sensors and wireline/wireless transceivers. He is broadly interested in innovative biotechnology for point-of-care diagnostics and medical imaging with emphasis on silicon-based approaches.

Academic Appointments

  • Research Engineer, Electrical Engineering

Honors & Awards

  • Predoctoral Achievement Award, IEEE Solid-State Circuits Society (SSC) (2014)
  • Outstanding Graduate Student Instructor Award, University of California, Berkeley (2014)
  • ADI Outstanding Student Designer Award, Analog Device Inc. (2014)
  • Co-recipient of Best Student Paper Award, 2nd place, Radio Frequency Integrated Circuits Symposium (RFIC) (2012)
  • Outstanding Student Design Award, Xilinx Inc., Xilinx Inc. (2012)
  • Co-recipient of Jack Kilby Outstanding Student Paper Award, International Solid-State Circuits Conference (ISSCC) (2010)
  • Silkroad Award, International Solid-State Circuits Conference (ISSCC) (2007)
  • Special ISSCC Award, National Chip Implementation Center, Taiwan (2007)
  • Annual Best Thesis Award, Graduate Institute of Electronic Engineering, National Taiwan University (2006)
  • 1st Prize, Graduate Student Thesis Contest, Chinese Institute of Electrical Engineering (2006)
  • Honorable Mention, Macronix Golden Silicon Award, 6th Competition (2006)
  • Master Thesis Award, Graduate Student Thesis Contest of Taiwan IC Design Society (2006)
  • Winner of Master Thesis Contest, Mixed Signal and RF Consortium (2006)

Professional Education

  • PhD, University of California, Berkeley, Electrical Engineering and Computer Science (2015)
  • MS, National Taiwan University, Electronics Engineering (2006)
  • BS, National Taiwan University, Electrical Engineering (2004)

All Publications

  • A high-throughput flow cytometry-on-a-CMOS platform for single-cell dielectric spectroscopy at microwave frequencies LAB ON A CHIP Chien, J., Ameri, A., Yeh, E., Killilea, A. N., Anwar, M., Niknejad, A. M. 2018; 18 (14): 2065–76


    This work presents a microfluidics-integrated label-free flow cytometry-on-a-CMOS platform for the characterization of the cytoplasm dielectric properties at microwave frequencies. Compared with MHz impedance cytometers, operating at GHz frequencies offers direct intracellular permittivity probing due to electric fields penetrating through the cellular membrane. To overcome the detection challenges at high frequencies, the spectrometer employs on-chip oscillator-based sensors, which embeds simultaneous frequency generation, electrode excitation, and signal detection capabilities. By employing an injection-locking phase-detection technique, the spectrometer offers state-of-the-art sensitivity, achieving a less than 1 aFrms capacitance detection limit (or 5 ppm in frequency-shift) at a 100 kHz noise filtering bandwidth, enabling high throughput (>1k cells per s), with a measured cellular SNR of more than 28 dB. With CMOS/microfluidics co-design, we distribute four sensing channels at 6.5, 11, 17.5, and 30 GHz in an arrayed format whereas the frequencies are selected to center around the water relaxation frequency at 18 GHz. An issue in the integration of CMOS and microfluidics due to size mismatch is also addressed through introducing a cost-efficient epoxy-molding technique. With 3-D hydrodynamic focusing microfluidics, we perform characterization on four different cell lines including two breast cell lines (MCF-10A and MDA-MB-231) and two leukocyte cell lines (K-562 and THP-1). After normalizing the higher frequency signals to the 6.5 GHz ones, the size-independent dielectric opacity shows a differentiable distribution at 17.5 GHz between normal (0.905 ± 0.160, mean ± std.) and highly metastatic (1.033 ± 0.107) breast cells with p ≪ 0.001.

    View details for DOI 10.1039/c8lc00299a

    View details for Web of Science ID 000438244100009

    View details for PubMedID 29872834

  • A CMOS Single-Cell Deformability Analysis using 3D Hydrodynamic Stretching in a GHz Dielectric Flow Cytometry Chien, J., Anwar, M., Niknejad, A. M., IEEE IEEE. 2017: 857–60