Dr. Shree Krishna Acharya, University College Dublin, Ireland
Dr. Shree Krishna Acharya is a distinguished Research Scientist at University College Dublin, Ireland 🎓. He holds a Ph.D. in Electronics Engineering, specializing in short-term forecasting using artificial intelligence for distributed energy resources (DERs) in power systems, and a Master’s focusing on uncertainty analysis and short-term forecasting of residential energy consumption 📜. Dr. Acharya’s professional experience includes leading AI-based projects at UCD, such as live streaming marine vessel detection and anomaly detection in vessel tracking 🔬. His previous roles include postdoctoral research at Mokpo National University, where he enhanced forecasting models and developed reinforcement learning systems. Proficient in AI programming, containerized solutions, and statistical analysis, Dr. Acharya’s research interests span AI-based forecasting, energy resource management, wireless communication systems, and data science 💻.
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🎓 Education
- Ph.D. in Electronics Engineering: Specialized in short-term forecasting using artificial intelligence, focusing on distributed energy resources (DERs) in power systems. (2017-2022)
- Master’s in Electronics Engineering: Focused on uncertainty analysis and short-term forecasting of residential energy consumption. (2015-2017)
📜 Certification
- IBM Data Science Professional Certificate: Certified expertise in data science methodologies and tools.
🔬 Professional Experience
- Research Scientist at University College Dublin (UCD), Dublin, Ireland (02/2023 – Present): Leading AI-based projects including live streaming marine vessel detection, anomaly detection in vessel tracking, and developing geo-spatial tracking systems. Proficient in AI frameworks, containerized solutions, and data processing with significant contributions to network efficiency and consortium collaborations.
- Postdoctoral Researcher/PhD Researcher at Mokpo National University, Mokpo, South Korea (09/2015 – 02/2023): Enhanced forecasting models and accuracy in energy consumption and PV systems, developed reinforcement learning models, and improved wireless communication systems. Published research findings and contributed to advancements in AI and statistical models.
💻 Technical Skills
- Proficient in AI programming (CNN, Keras, TensorFlow, PyTorch)
- Experienced in developing and deploying containerized solutions (Docker)
- Skilled in REST API deployment, MQTT, WebRTC, and Python scripting
- Expertise in statistical analysis and machine learning models for energy forecasting
🔍 Research Interests
- AI-based short-term forecasting
- Energy resource management
- Wireless communication systems
- Data science and machine learning applications
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