Innovation Chair in Animal Welfare and Artificial Intelligence (WELL-E), Canada
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Early Academic Pursuits 📚
Mr. Vahid Naghashi is currently a Ph.D. candidate, focusing on forecasting dairy income during future lactations using deep learning models. His academic journey reflects a strong foundation in time series forecasting, machine learning, and deep learning. Throughout his academic career, he has excelled in advancing knowledge in computational models and applied artificial intelligence.
Professional Endeavors 💼
Mr. Naghashi’s career has also been shaped by professional industry experience, including an internship at a multimedia company. During his internship, he worked on projects involving Large Language Models (LLMs) and audio processing with foundation models. His exposure to real-world applications of deep learning models has broadened his expertise in both academic and industry settings.
Contributions and Research Focus 🔬
Mr. Naghashi’s research primarily focuses on time series forecasting using deep learning techniques. His major research project involves the prediction of milk profits in future lactations, an area of great relevance to the dairy industry. One of his notable contributions is the development of a multiscale model for multivariate time series forecasting, which has applications across various fields, published in Nature Scientific Reports.
Impact and Influence 🌍
The impact of Mr. Naghashi’s work extends beyond academia. His contributions to the field of deep learning for time series forecasting can significantly transform industries like dairy farming. His work in forecasting and data analytics has proven to be useful in real-world scenarios, with a growing citation index, indicating the broader influence of his research.
Academic Cites 📑
His work has been recognized in several prestigious journals, including his recent article published in Nature Scientific Reports, which has been widely cited. Additionally, his research article “A multiscale model for multivariate time series forecasting” is a key example of his contributions to the academic community, helping to shape future research directions in time series analysis and forecasting.
Technical Skills 🧑💻
Mr. Naghashi possesses extensive technical expertise in deep learning, machine learning, and time series forecasting. He has proficiency in advanced data science tools and techniques, including large-scale machine learning models, deep neural networks, and predictive analytics, which are crucial in his research and consultancy projects.
Teaching Experience 👨🏫
While there is no direct mention of formal teaching roles, Mr. Naghashi’s research and consultancy work undoubtedly involve mentoring and knowledge sharing within his academic collaborations and industry projects. His involvement with the Innovation Chair in Animal Welfare and Artificial Intelligence (WELL-E) demonstrates his commitment to educating others in his field.
Legacy and Future Contributions 🔮
Looking forward, Mr. Naghashi aims to further advance deep learning methodologies, particularly in forecasting applications across industries such as agriculture, healthcare, and finance. His future research goals include enhancing predictive models and working on larger-scale applications that have a lasting impact on both academic and professional communities.
Top Noted Publications 📖
Co-occurrence of adjacent sparse local ternary patterns: A feature descriptor for texture and face image retrieval
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- Authors: V. Naghashi
- Journal: Optik
- Year: 2018
Evaluation of dominant and non-dominant hand movements for volleyball action modelling
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- Authors: F. Haider, F. Salim, V. Naghashi, SBY Tasdemir, I. Tengiz, K. Cengiz, …
- Journal: Adjunct of the 2019 International Conference on Multimodal Interaction
- Year: 2019
Volleyball action modelling for behavior analysis and interactive multi-modal feedback
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- Authors: FA Salim, F. Haider, SBY Tasdemir, V. Naghashi, I. Tengiz, K. Cengiz, …
- Journal: eNTERFACE’19: 15th International Summer Workshop on Multimodal Interfaces
- Year: 2020
A searching and automatic video tagging tool for events of interest during volleyball training sessions
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- Authors: F. Salim, F. Haider, SBY Tasdemir, V. Naghashi, I. Tengiz, K. Cengiz, …
- Journal: 2019 International Conference on Multimodal Interaction
- Year: 2019
A multiscale model for multivariate time series forecasting
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- Authors: V. Naghashi, M. Boukadoum, AB Diallo
- Journal: Scientific Reports
- Year: 2025