Guangyu Wang

Data Scientist | Machine Learning Engineer | Researcher

Dalian, CN.

About

Highly accomplished Data Science and Big Data Technology student with a 3.61 GPA, specializing in advanced machine learning, spatiotemporal analysis, and big data management. Proven ability to conduct impactful research, develop innovative models, and publish in top-tier journals, including Applied Soft Computing and Applied Energy. Eager to leverage expertise in deep learning, graph neural networks, and data-driven problem-solving to excel in a challenging data science or machine learning engineering role.

Work

New York University Shanghai

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Research Internship

Shanghai, Shanghai, China

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Summary

Engaged in a research internship at NYU Shanghai, focusing on advanced topics in data science and machine learning to contribute to ongoing academic studies.

Highlights

Conducted in-depth literature reviews and experimental design for research initiatives in spatiotemporal analysis and machine learning.

Developed and refined data processing pipelines for complex datasets, ensuring accuracy and efficiency for research objectives.

Contributed to the analysis and interpretation of research findings, preparing preliminary reports and presentations for faculty.

Key Laboratory of Big Data Management Optimization and Decision

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Student Member

Dalian, Liaoning, China

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Summary

Contributed to cutting-edge research and development initiatives within a leading big data laboratory, focusing on optimizing data management and decision-making processes.

Highlights

Assisted in the development and implementation of advanced data analytics models, supporting key research projects in big data optimization.

Collaborated with senior researchers on data collection, processing, and analysis tasks, enhancing project efficiency and data integrity.

Gained practical experience in applying theoretical knowledge to real-world big data challenges, contributing to the lab's research output.

Education

Dongbei University of Finance and Economics

Dalian, Liaoning, China
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Bachelor Data Science and Big Data Technology Grade: GPA: 3.61

Courses

Data Scraping and Data Cleaning (97/100)

Mathematical Modeling (97/100)

Natural Language Processing (97/100)

Machine Learning and Financial Modeling (98/100)

Deep Learning (96/100)

Awards

National Project Grant

College Student Innovation and Entrepreneurship Project

Awarded as a Team Leader for a national-level project grant.

National First Prize

National College Student Market Research and Analysis Competition

Achieved top 0.43% in a national competition for market research and analysis.

Honorable Mention

Mathematical Contest in Modeling (MCM)

Received honorable mention for outstanding performance in the Mathematical Contest in Modeling.

National Bronze Medal

China International College Students Innovation Contest

Awarded a national bronze medal in a prestigious innovation contest.

National Bronze Medal

9th National Innovation and Entrepreneurship Competition for Financial and Economic Institutions

Received a national bronze medal in a competition focused on financial and economic innovation.

Publications

Frequency as identity: A Fourier hypernetwork for spatiotemporal forecasting

Applied Soft Computing

Co-authored a manuscript on Fourier hypernetworks for spatiotemporal forecasting, published in a JCR Q1 journal (IF=6.6).

RoseNet: A Cross-Modal Incongruity Adaptive Graph Learning Network in Multimodal Sentiment Recognition

International Joint Conference on Neural Networks (IJCNN)

Co-authored a manuscript on RoseNet for cross-modal sentiment recognition, published in a CCF-C conference.

Enhancing PV power forecasting accuracy through nonlinear weather correction based on multi-task learning

Applied Energy

Co-authored a manuscript on enhancing PV power forecasting accuracy using multi-task learning, published in a JCR Q1 journal (IF=10.1).

IMMA: Incident-aware Momentum and Memory Adaptation on Streaming Traffic Data under Compound Drift

Working paper

Co-authored a working paper introducing IMMA for adaptive analysis of streaming traffic data with compound drift.

Languages

English (IELTS 6.5)

Mandarin Chinese (Native)

Certificates

Software Copyright: Multimodal Interactive Robot Platform V1.0

China National Copyright Administration

Software Copyright: Multi-Sensor Fusion Robot Platform V1.0

China National Copyright Administration

Software Copyright: Service Robot Management Platform V1.0

China National Copyright Administration

Software Copyright: Multimodal Speech Audio Adjustment System V1.0

China National Copyright Administration

Patent: A Deep Multimodal Sentiment Analysis Method Based on Graphic-Text Interaction Information and Multimodal Sentiment Influence Factors

China National Intellectual Property Administration

Skills

Programming Languages

Python, Java, R.

Web Technologies

HTML, Vue, Streamlit.

Database Systems

SQL, Spark, DASK.

Data Science & Machine Learning

Python, Torch, Deep Learning, Natural Language Processing, Machine Learning, Spatiotemporal Analysis, Graph Neural Networks, Pattern Recognition, Knowledge Distillation, Multimodal Sentiment Recognition, Traffic Forecasting.

DevOps & Version Control

Git.

Mathematical & Statistical Tools

SPSS, R, Mathematical Modeling, Data Scraping, Data Cleaning.

Projects

Multi-Source Spatiotemporal Analysis with Graph-based Temporal Modeling

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Summary

Developed a novel graph signal processing framework for dynamic spatiotemporal data analysis, integrating advanced architectures to enhance pattern recognition and optimize information flow in sensor networks.

Compound Drift Adaptation for Urban Traffic Forecasting

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Summary

Formalized the concept of compound drift in streaming traffic data and engineered an adaptive framework to reduce adaptation latency for transient anomalies while maintaining prediction accuracy.