Chu-Fei Luo
Masters Student at Ingenuity Labs Research Institute- Claim this Profile
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Bio
Credentials
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Machine Learning with Python - Level 1
IBMJun, 2019- Nov, 2024 -
AWS Certified Developer – Associate
Amazon Web Services (AWS)Jun, 2020- Nov, 2024 -
AWS Certified Solutions Architect – Associate
Amazon Web Services (AWS)May, 2020- Nov, 2024
Experience
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Ingenuity Labs Research Institute
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Canada
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Research Services
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1 - 100 Employee
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Masters Student
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Sep 2021 - Present
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Conflict Analytics Lab
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Canada
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Research
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1 - 100 Employee
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Masters Student
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Sep 2021 - Present
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IBM
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United States
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IT Services and IT Consulting
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700 & Above Employee
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Software Developer
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Dec 2020 - Sep 2021
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L2 Support
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Jun 2019 - Dec 2020
- Specialized support for IBM’s QRadar SIEM, used linux command line to diagnose issues- Subject Matter Expert for leading application, User Behaviour Analytics - helped with case analysis, defect tracking, public-facing documentation- Led live troubleshooting sessions between clients and developers, helped identify causes of errors in the system and ensured quick and smooth resolutions- Focus on Python, Docker, Bash, PSQL, REST API queries
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University of Ottawa
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Canada
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Higher Education
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700 & Above Employee
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Software Developer - Motor Function Measurement Lab
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Oct 2019 - Jun 2020
- Helped implement full stack mobile application, including REST API and native frontend - Used Python, Google Firebase NoSQL db, Flutter - Helped implement full stack mobile application, including REST API and native frontend - Used Python, Google Firebase NoSQL db, Flutter
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Queen's Soft Robotics Team
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Canada
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Biotechnology Research
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Electrical Team Member
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Sep 2018 - Jun 2019
- Designed and implemented control systems for pneumatic soft robotics technology - Used Arduino microcontrollers - Designed and implemented control systems for pneumatic soft robotics technology - Used Arduino microcontrollers
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Queen's University
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Canada
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Higher Education
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700 & Above Employee
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Summer Research Student
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May 2018 - Aug 2018
- Funded by NSERC’s USRA scholarship, conducted research on Machine Learning and Deep Learning techniques applied to NLP and Signal Processing - Used Keras, logistic regression to detect multimodal sarcasm - Funded by NSERC’s USRA scholarship, conducted research on Machine Learning and Deep Learning techniques applied to NLP and Signal Processing - Used Keras, logistic regression to detect multimodal sarcasm
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Education
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Queen's University
Bachelor of Applied Science - BASc, Computer Engineering -
Queen's University
Master's degree, Computer Engineering