📍 Toronto, ON, Canada
🔗 GitHub | ORCID | Google Scholar | Linkedin
Georgia Institute of Technology
M.Sc., Computer Science (Machine Learning Track)
Atlanta, GA, USA | 09/2024 – 08/2026
Boston University
Ph.D., Physical Chemistry
Boston, MA, USA | 09/2017 – 05/2023
University of British Columbia
M.A.Sc, Materials Engineering
Vancouver, BC, Canada | 01/2015 – 05/2017
Fudan University
B.Sc, Applied Physics
Shanghai, China | 09/2009 – 07/2013
Scale AI, USA.
Applied ML Engineer — 01/2026 – Present
I. Research at GenAI Applied ML @ Scale AI:
I authored and co-authored ScaleLab’s blogpost:
II. Product development at GenAI Applied ML @ Scale AI
At Scale AI’s GenAI org and Applied ML team, I primarily focus on data quality eval, failure model analysis, and scale up for autonomous quality control. The followings are the projects that I led and completed.
Developed automate-hillclimb package for automated optimization of quality checks against production data; Led real-time / post-completion checks development and training
Devleoped Video-OCR package for OCR+LLM transcription of text from videos
Built end-to-end pipeline for evaluating contributor justification quality for universe generation.
Developed a container-free pipeline for running SWE-Bench Pro tasks with Mini-SWE-Agent: collecting agentic trajectories, and evaluating them with LLM judge via Inspect AI, including a Streamlite web app with background job execution, live trajectory streaming, and job history tracking.
Built Hil-Dynamics (https://github.com/melfeki-11/HiL-Dynamics; https://arxiv.org/abs/2604.09408): it measures how frontier agents behave when a task is underspecified.
Major developer of Scale’s Lighthouse / Insights platform for benchmark and delivery data analysis and insights generation: led the development of failure mode analysis.
Major developer of AgenticDq platform for on-demand and automated generation of quality checks for production queues.
Built an in-house package for enterprise data anonymization and redaction.
First-author and core developer of Process-verifier / Reward-hacking measurement tool (Manuscript ready for submission).
Builder of E2E autopatcher for benchmark loopholes/hackable surfaces and production data for delivery
Scale AI, USA.
AI Training Consultant — 03/2025 – Present
Develop PhD-level STEM / research datasets to advance next-generation LLMs that can drive rigorous, high-impact scientific discovery.
Scale AI, USA.
Queue Manager — 10/2023 – 03/2025
Project lead for multiple reasoning projects in STEM fields
Mayson Science Inc. (Toronto, ON, Canada)
Founder — 02/2025 – Present
ThinkCX Inc. (Vancouver, BC, Canada)
Data Scientist / Data Engineer (AWS Certified) — 02/2023 – 12/2024
Designed and developed a population-wide wireless churning solution
Signify (Philips Lighting) Research North America. (Burlington, MA, USA)
Machine Learning Research Intern — 05/2022 – 08/2022
Boston University. (Boston, MA, USA)
Research Fellow — 09/2017 – 03/2023
Oak Ridge National Laboratory (Oakridge, TN, USA)
Visiting Researcher, CNMS — 10/2021 – 11/2022
University of British Columbia. (Vancouver, BC, Canada)
Research Assistant — 01/2015 – 04/2017
Dopant diffusion in strained SiGe HBTs
NSF CAREER – Deciphering 2-Dimensional, Crystal-Mediated, Surface-Enhanced Raman Scattering for Quantitative Analysis
https://app.dimensions.ai/details/grant/grant.8966022
2020–2025
NSF ENG – Graphene Plasmonic Nanostructures for Terahertz Light Emission
https://app.dimensions.ai/details/grant/grant.970547
2021–2024