Daniel Zhang Email and Phone Number
👋🏽 Hi, my name is Daniel🎓 A recent graduate in Statistics and Computer Science, with a Bachelor's of Mathematics, from the University of Waterloo (Apr 2023). Incoming MMath Statistics Candidate, also at the University of Waterloo🌇 Toronto Native, with a passion for leveraging machine learning and analytics to derive insights.📚 I have had the opportunity to complete internships in a wide variety of fields. Previously, I interned at the NRC, Intact Financial Corporation, TD Bank, and Blue Lion Labs. My prior experience ranges from Machine Learning Research to deriving insights from analytics to assist initiatives to building data pipelines for data modeling teams. In the upcoming term, I will be continuing my research in Federated Learning as a URA at the University of Waterloo VIP Lab, as well as completing my internship as a Data Scientist in the Intact Data Lab. I am very excited and eager to start both. 💻 As for my future, I hope to one day pursue a graduate degree in the field of statistics/machine learning and/or work as a machine learning engineer/data scientist with a diverse team. 🏔 In my free time, you can find me at the gym or playing badminton. 💪🏽 Machine Learning, Analytics, Data Visualization, Statistics, Big Data, Federated Learning
Intact
View- Website:
- intactfc.com
- Employees:
- 10937
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Data ScientistIntact Jun 2023 - Present -
Head Teaching AssistantUniversity Of Waterloo Jan 2024 - Apr 2024Waterloo, Ontario, CanadaHead TA for: STAT 442/842: Data Visualization and STAT 940: Deep Learning -
Teaching AssistantUniversity Of Waterloo Sep 2023 - Dec 2023Waterloo, Ontario, CanadaSTAT 231: Statistics STAT 442/842: Data Visualization -
Data ScientistIntact Sep 2022 - Dec 2022Toronto, Ontario, Canada -
Undergraduate Research AssistantUniversity Of Waterloo Sep 2022 - Dec 2022- Under the supervision of Prof. Alexander Wong, Dr. Jason Deglint, and Vikram Voleti- Federated Learning for Phytoplankton Image Classification- Paper titled "Plankton-FL: Exploration of Federated Learning for Privacy-Preserving Training of Deep Neural Networks for Phytoplankton Classification" won the Best AI paper award at CVIS 2022 -
Data Science & Advanced AnalyticsTd May 2022 - Aug 2022 -
Data ScientistIntact Sep 2021 - Dec 2021Toronto, Ontario, Canada -
Machine Learning Research AssistantNational Research Council Canada / Conseil National De Recherches Canada Jan 2021 - Apr 2021Toronto, Ontario, Canada• Under the supervision of Dr. Sajjad Ghaemi and Dr. James Ooi• Conducted research on various applications of Transfer Learning and shared the findings with the research team.• Established a Transfer Learning framework that involved initially training an MLP neural network with Influenza patient data,followed by fine‑tuning and assessing its performance on COVID‑19 clinical, patient data.• Evaluated the effectiveness of Transfer Learning against a standard MLP neural network model, trained from scratch on theCOVID‑19 data, resulting in a 25% enhancement in the AUROC score.• Processed biological data and created synthetic samples through synthetic minority oversampling. -
Teaching AssistantSpirit Of Math Schools Inc. Sep 2015 - Apr 2016
Daniel Zhang Skills
Daniel Zhang Education Details
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Master Of Mathematics, Statistics -
Statistics Major, Computer Science Minor -
North Toronto Collegiate InstituteHigh School Diploma
Frequently Asked Questions about Daniel Zhang
What company does Daniel Zhang work for?
Daniel Zhang works for Intact
What is Daniel Zhang's role at the current company?
Daniel Zhang's current role is MMath Statistics @ UWaterloo | Data Scientist I @ IntactLab.
What schools did Daniel Zhang attend?
Daniel Zhang attended University Of Waterloo, University Of Waterloo, North Toronto Collegiate Institute.
What skills is Daniel Zhang known for?
Daniel Zhang has skills like Leadership, Public Speaking, Data Science, Business, Node.js, Mongodb, Student Leadership, Microsoft Powerpoint, Report Writing, Linear Regression, Data Analysis, Communication.
Who are Daniel Zhang's colleagues?
Daniel Zhang's colleagues are Natalie Torus, Pooja Agarwal, Mithuna Kusalakumar, Tristan Adey, Elvin Zachariah, Brett Wethmar, Denisse Macaraig, Cip®, Cspo®.
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