Summary
Overview
Work History
Education
Skills
Timeline
Work Availability
Software
Hobbies
Languages
Hi, I’m

Yuexi(Cici) Zhang

PhD in AI/ML
Boston,MA
Yuexi(Cici) Zhang

Summary

Machine learning expert, specializing in innovative algorithms for Vision and Large Language Model (VLM) applications, generative modeling, pose estimation, video/image analysis, and object detection. Effective communicator, committed to ongoing research and staying updated on latest advancements in computer vision/machine learning and self-motived, proactive at managing multiple projects with precision. Owned publications and served as the reviewer for top AI conferences and journals.

Overview

4
years of professional experience

Work History

Northeastern University
Boston, MA

Machine Learning Research Assistant
12.2020 - Current

Job overview

  • Led the implementation of groundbreaking multimodal architecture for Zero-shot Online Temporal Action Localization in real-time streaming video; achieved precise detections of action start and end points along with accurate class labels for both seen and novel video categories.
  • Fine-tuned Large Language Model (LLM) with structural text descriptions to significantly enhance the action classification results while guiding the model to precisely predict time stamp of the action without accessing the future information and post refinement.
  • Utilized parallel and distributed computing techniques to guarantee the capability of handling the large scale data and the model.

OSI Systems
Boston, MA

Machine Learning Intern
05.2023 - 08.2023

Job overview

  • Developed a novel Object Detector for X-ray Scanning System in Import Cargos to identity unexpected objects (anomaly) on its X-ray images, resulting in significant improvement in detection accuracy from 83.4% to 95.2% of X-ray inspection platforms.
  • Fine-tuned diffusion models for data augmentation techniques and unsupervised anomaly detections, which seamlessly integrate with diverse scan systems and achieved exceptional 91.0% precision and 94.7% recall.
  • Designed an automated pipeline with the MLOps approach by collaborating with cross-functional teams to ensure the efficiency of future deployment and productivity with diverse scan systems, meticulously aligning with and surpassing project specifications.

United Imaging Intelligence
Boston, MA

Computer Vision Intern
05.2022 - 08.2022

Job overview

  • Discovered the challenge of current product: Patients’ Position Guidance for MRI scanner, collaborated with multidisciplinary teams to analyze various screening scenarios and conducted in-depth research to overcome guidance difficulties with occlusions.
  • Led the innovation of generative AI/ML solution (GAN) on 10M validation samples, optimized 2D/3D point-cloud model to obtain the accuracy of 100% when occlusion rate is up to 20% and overall accuracy 96.5% under various occlusion rates.
  • Delivered comprehensive presentations to key stakeholders, effectively illustrating, and highlighting the potential transformative impact of the solution on enhancing MRI screening processes to foster the deep understanding of its significance in the healthcare.

Innopeak Technology (OPPO US)
Palo Alto, CA

Computer Vision Intern
05.2021 - 05.2022

Job overview

  • Investigated comprehensive strategies: Generic Action Start Online Detection for Video Highlighting on edge devices, designed the taxonomy-free architecture with latest advancements to ensure the solution is not limited to pre-defined video categories.
  • Led to achieve the best performance across industry-standard benchmarks, contributed to enhance efficiency of GASD system on current edge devices by implementing one-hot input method to eliminate the reliance on historical decisions or prior knowledge.
  • Demonstrated the revolutionary influence of GASD to the team, covering not just the technical details, but also emphasized its broader implications for future products; successfully filed a patent to secure the innovation together with team members.

Education

Northeastern University
Boston, MA

Ph.D. from Electrical Engineering And Computer Science
06-2024

University Overview

Northeastern University
Boston, MA

Bachelor of Science from Electrical And Computer Engineering
05-2015

University Overview

Skills

Programming Tools: Python, MATLAB, C, OpenCV, SQL, Git, Spark, Docker, CUDA

Deep Learning: PyTorch, TensorFlow, Hugging Face, AWS, Azure VM, GCP, MLOps

Timeline

Machine Learning Intern
OSI Systems
05.2023 - 08.2023
Computer Vision Intern
United Imaging Intelligence
05.2022 - 08.2022
Computer Vision Intern
Innopeak Technology (OPPO US)
05.2021 - 05.2022
Machine Learning Research Assistant
Northeastern University
12.2020 - Current
Northeastern University
Ph.D. from Electrical Engineering And Computer Science
Northeastern University
Bachelor of Science from Electrical And Computer Engineering
Availability
See my work availability
Not Available
Available
monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
swipe to browse

Software

Python

C

PyTorch

SaaS

Hobbies

Hobbies
  • Winter Sport
  • Tennis
  • Skate

Languages

Chinese (Mandarin)
Native language
English
Advanced (C1)
C1
Yuexi(Cici) ZhangPhD in AI/ML