May
高级技术咨询
Capgemini Japan · 7年经验
日薪：
￥700/8h
地点：
海外 全区
时间：
可工作日远程
信用行为
0
接单数
0
评价数
0
收藏数
技术能力
SKILLS
• Programming: Python (Proficient), SQL, Java, R
• Machine Learning: Supervised/Unsupervised Learning, Neural Networks, Transformers, XGBoost,
Hyperparameter Tuning, Model Evaluation (AUC-ROC, F1-Score)
• Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Spark MLlib
• Tools: Docker, Git, AWS (SageMaker, Glue), Apache Spark, MATLAB, EEGLab
• Data Engineering: ETL, Data Pipelines, Time-Series Analysis, Signal Processing
• Languages: English (Fluent), Japanese (Business Proficiency), Chinese (Native)
• Programming: Python (Proficient), SQL, Java, R
• Machine Learning: Supervised/Unsupervised Learning, Neural Networks, Transformers, XGBoost,
Hyperparameter Tuning, Model Evaluation (AUC-ROC, F1-Score)
• Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Spark MLlib
• Tools: Docker, Git, AWS (SageMaker, Glue), Apache Spark, MATLAB, EEGLab
• Data Engineering: ETL, Data Pipelines, Time-Series Analysis, Signal Processing
• Languages: English (Fluent), Japanese (Business Proficiency), Chinese (Native)
项目经验
PROJECTS
Cognitive Load & Emotion State Classification | Illinois Institute of Technology (Jan 2024 – Present)
• Built LSTM and CNN models using TensorFlow to classify cognitive states (e.g., attention, “Aha!
moments”) from multi-modal biosensor data (EEG, EDA, pupil response).
• Preprocessed EEG signals with ICA decomposition in EEGLab, removing noise and improving model
accuracy by 15%.
• Engineered time-series features (3s/5s windows) and trained XGBoost, SVM, and EEGNet
architectures, achieving 0.9 F1-score in emotion state classification.
PROFESSIONAL EXPERIENCE
Research Assistant | Illinois Institute of Technology, Chicago, IL (Jan 2024 – Present)
(See Projects section for details)
Senior Salesforce Developer | Salesforce-to-Financial System Integration | THS Inc., Tokyo (Jan 2018 –
Jun 2022)
• Led end-to-end development of 12 Salesforce pages using Apex, Visualforce, and SOQL, improving
user workflow efficiency by 25%.
• Automated data transactions between Salesforce and external systems by developing 20+ batch
processes in Apex, reducing manual effort by 30%.
• Designed unit test cases with 85% coverage, ensuring system reliability for financial operations.
Cognitive Load & Emotion State Classification | Illinois Institute of Technology (Jan 2024 – Present)
• Built LSTM and CNN models using TensorFlow to classify cognitive states (e.g., attention, “Aha!
moments”) from multi-modal biosensor data (EEG, EDA, pupil response).
• Preprocessed EEG signals with ICA decomposition in EEGLab, removing noise and improving model
accuracy by 15%.
• Engineered time-series features (3s/5s windows) and trained XGBoost, SVM, and EEGNet
architectures, achieving 0.9 F1-score in emotion state classification.
PROFESSIONAL EXPERIENCE
Research Assistant | Illinois Institute of Technology, Chicago, IL (Jan 2024 – Present)
(See Projects section for details)
Senior Salesforce Developer | Salesforce-to-Financial System Integration | THS Inc., Tokyo (Jan 2018 –
Jun 2022)
• Led end-to-end development of 12 Salesforce pages using Apex, Visualforce, and SOQL, improving
user workflow efficiency by 25%.
• Automated data transactions between Salesforce and external systems by developing 20+ batch
processes in Apex, reducing manual effort by 30%.
• Designed unit test cases with 85% coverage, ensuring system reliability for financial operations.
May
高级技术咨询 · 7年经验 · Capgemini Japan
0
累计接单
0
用户评价
0
被收藏
信用行为
0
接单数
0
评价数
0
收藏数
技术能力
SKILLS
• Programming: Python (Proficient), SQL, Java, R
• Machine Learning: Supervised/Unsupervised Learning, Neural Networks, Transformers, XGBoost,
Hyperparameter Tuning, Model Evaluation (AUC-ROC, F1-Score)
• Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Spark MLlib
• Tools: Docker, Git, AWS (SageMaker, Glue), Apache Spark, MATLAB, EEGLab
• Data Engineering: ETL, Data Pipelines, Time-Series Analysis, Signal Processing
• Languages: English (Fluent), Japanese (Business Proficiency), Chinese (Native)
• Programming: Python (Proficient), SQL, Java, R
• Machine Learning: Supervised/Unsupervised Learning, Neural Networks, Transformers, XGBoost,
Hyperparameter Tuning, Model Evaluation (AUC-ROC, F1-Score)
• Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Spark MLlib
• Tools: Docker, Git, AWS (SageMaker, Glue), Apache Spark, MATLAB, EEGLab
• Data Engineering: ETL, Data Pipelines, Time-Series Analysis, Signal Processing
• Languages: English (Fluent), Japanese (Business Proficiency), Chinese (Native)
项目经验
PROJECTS
Cognitive Load & Emotion State Classification | Illinois Institute of Technology (Jan 2024 – Present)
• Built LSTM and CNN models using TensorFlow to classify cognitive states (e.g., attention, “Aha!
moments”) from multi-modal biosensor data (EEG, EDA, pupil response).
• Preprocessed EEG signals with ICA decomposition in EEGLab, removing noise and improving model
accuracy by 15%.
• Engineered time-series features (3s/5s windows) and trained XGBoost, SVM, and EEGNet
architectures, achieving 0.9 F1-score in emotion state classification.
PROFESSIONAL EXPERIENCE
Research Assistant | Illinois Institute of Technology, Chicago, IL (Jan 2024 – Present)
(See Projects section for details)
Senior Salesforce Developer | Salesforce-to-Financial System Integration | THS Inc., Tokyo (Jan 2018 –
Jun 2022)
• Led end-to-end development of 12 Salesforce pages using Apex, Visualforce, and SOQL, improving
user workflow efficiency by 25%.
• Automated data transactions between Salesforce and external systems by developing 20+ batch
processes in Apex, reducing manual effort by 30%.
• Designed unit test cases with 85% coverage, ensuring system reliability for financial operations.
Cognitive Load & Emotion State Classification | Illinois Institute of Technology (Jan 2024 – Present)
• Built LSTM and CNN models using TensorFlow to classify cognitive states (e.g., attention, “Aha!
moments”) from multi-modal biosensor data (EEG, EDA, pupil response).
• Preprocessed EEG signals with ICA decomposition in EEGLab, removing noise and improving model
accuracy by 15%.
• Engineered time-series features (3s/5s windows) and trained XGBoost, SVM, and EEGNet
architectures, achieving 0.9 F1-score in emotion state classification.
PROFESSIONAL EXPERIENCE
Research Assistant | Illinois Institute of Technology, Chicago, IL (Jan 2024 – Present)
(See Projects section for details)
Senior Salesforce Developer | Salesforce-to-Financial System Integration | THS Inc., Tokyo (Jan 2018 –
Jun 2022)
• Led end-to-end development of 12 Salesforce pages using Apex, Visualforce, and SOQL, improving
user workflow efficiency by 25%.
• Automated data transactions between Salesforce and external systems by developing 20+ batch
processes in Apex, reducing manual effort by 30%.
• Designed unit test cases with 85% coverage, ensuring system reliability for financial operations.
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