Publications & Patents

My research contributions to the field of machine learning and artificial intelligence, including peer-reviewed publications and intellectual property.

Journal202445 citations

Transformer-Based Multi-Variate Time Series Forecasting with Attention Mechanisms

Your Name, Jane Smith, Robert Johnson

Journal of Machine Learning Research 25 (1-28)

We propose a novel transformer architecture specifically designed for multi-variate time series forecasting. Our approach incorporates temporal attention mechanisms and achieves state-of-the-art performance on multiple benchmark datasets.

Time SeriesTransformersAttentionForecasting
DOI: 10.1234/jmlr.2024.001
Conference202423 citations

Federated Learning with Differential Privacy for Healthcare Applications

Your Name, Alice Chen, Michael Brown, Sarah Davis

International Conference on Machine Learning (ICML) (2156-2167)

This paper presents a federated learning framework that preserves patient privacy while enabling collaborative model training across healthcare institutions. We demonstrate significant improvements in diagnostic accuracy while maintaining strict privacy guarantees.

Federated LearningPrivacyHealthcareDifferential Privacy
DOI: 10.1234/icml.2024.256
Journal2022127 citations

Multi-Modal Deep Learning for Medical Image Analysis

Your Name, David Wilson, Emily Rodriguez

Nature Machine Intelligence 4 (892-905)

We develop a multi-modal deep learning approach that combines medical imaging with clinical text data for improved diagnostic accuracy. Our method shows 12% improvement in early disease detection across multiple conditions.

Medical ImagingMulti-ModalDeep LearningDiagnostics
DOI: 10.1038/s42256-022-00567-8
Conference202289 citations

Real-Time Anomaly Detection in IoT Sensor Networks Using Ensemble Methods

Your Name, Kevin Lee, Maria Garcia

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (1234-1243)

We present a scalable ensemble-based approach for real-time anomaly detection in IoT sensor networks. Our system processes over 100K events per second with sub-millisecond latency while maintaining high accuracy.

Anomaly DetectionIoTReal-timeEnsemble Methods
DOI: 10.1145/3534678.3539123
Preprint202412 citations

Large Language Models for Code Generation: A Comprehensive Evaluation

Your Name, Lisa Wang, James Thompson

arXiv preprint

This work provides a comprehensive evaluation of large language models for automated code generation across multiple programming languages and domains. We introduce new benchmarks and evaluation metrics.

Large Language ModelsCode GenerationEvaluationBenchmarks
DOI: arXiv:2024.1234.5678

Research Impact

5
Publications
296
Total Citations
3
Patents
59
Avg. Citations