Ming Gong

Ming Gong

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Ming Gong

Pittsburgh, PA | Full CV →

ECE PhD student at CMU specializing in digital VLSI and computer architecture, with hands-on RTL-to-GDSII and post-silicon validation experience and three peer-reviewed publications in hardware, signal processing, and ML.

Education

2026 – present Carnegie Mellon University
PhD in Electrical and Computer Engineering

2024 – 2026 Columbia University
BS in Computer Engineering, Summa Cum Laude · GPA 4.26/4.33

2021 – 2024 Bard College at Simon’s Rock
BA in Physics, Summa Cum Laude · GPA 3.99/4.0

Experience

Jul. 2026 – present Graduate Research Assistant
VLSI Design Group, CMU

  • Built a PyTorch fault-injection framework for YOLOv8n to size the trusted partition for a secure-FPGA + Jetson deployment. Identified a 448-weight critical set (1% of FLOPs) at the network’s input and output boundaries.
  • Exploring heterogeneous eFPGA architectures and routing fabric configs to improve interconnect efficiency.
  • Building a PyVISA-based automated post-silicon testing framework to extract ASIC operating margins.

Jan. 2025 – May 2026 Teaching Assistant
Columbia University

  • TA for Embedded Systems
  • Head TA for Fundamentals of Computer Systems
  • CSEE ODS notetaker

Jan. 2025 – May 2026 Research Assistant with Dr. Xia Zhou
Mobile X Lab, Columbia University

  • Designed hybrid FPCB electrodes with a capacitive motion-reference channel and driven bias for a loose-shirt ECG; 92.7% full-waveform detection at rest (r = 0.89) and 4.58 bpm HR error while walking.
  • Built multichannel impedance-monitoring PCBs (schematic to bring-up) for impedance plethysmography (IPG) of fingertip blood flow.
  • Designed, fabricated, and tested fabric sensors integrated into SoftSleep orthopedic pillows.

Jun. – Aug. 2025 Algorithms Intern
Alibaba Group

  • Built deep-search LLM agents for large-scale business web scraping, raising business-development contact email search success from 20% to 60%.
  • Fine-tuned Qwen multilingual LLMs with supervised fine-tuning (SFT) to improve translation quality across 92 languages.

Jun. 2022 – Jun. 2025 Physics Intern with Dr. Michael Bergman
Bard College at Simon’s Rock

  • Cast directionally solidified and fine-grained Zn-alloy samples (0.2 to >30 mm grains) and ran ultrasonic pulse-echo experiments at 1–10 MHz across 90 measurement spots on 4 samples.
  • Developed an echo-detection algorithm defining a new scattering quality factor; first-author paper (PEPI 2025).
  • Presented a poster at the 2024 SEDI Conference.

Mar. 2022 – Jul. 2024 Research Assistant with Dr. Xi Chen
Zhejiang University

  • Benchmarked DNN, CNN, and decision tree architectures to model nonlinear pure component properties.
  • Co-authored a peer-reviewed paper on ML-based pure component property estimation (Engineering, 2024).

Publications

Awards and Honors

Skills

  • EDA: Cadence Genus, Innovus, Virtuoso; Synopsys Design Compiler; AMD Vitis; Intel Quartus; VTR; SPICE
  • Languages & Tools: SystemVerilog, Chisel/Scala, Tcl, Python, C/C++, MATLAB, Java, Git, Linux
  • Digital Design: RTL, Logic Synthesis, Place & Route, Static Timing Analysis, Timing Closure, FPGA Prototyping, eFPGA Architecture, Hardware Accelerators, Fault Injection
  • Hardware & Mixed-Signal: Analog Design, PCB Design, Post-Silicon Validation, PyVISA, Signal Processing
  • ML for Hardware: PyTorch, TensorFlow, CNN Fault Injection, LLM Fine-Tuning

Selected Projects