Vahid Naghashi | Temporal Data Patterns | Best Researcher Award

Mr. Vahid Naghashi | Temporal Data Patterns | Best Researcher Award

Innovation Chair in Animal Welfare and Artificial Intelligence (WELL-E), Canada

Author Profile

Google Scholar

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
    • Authors: V. Naghashi
    • Journal: Optik
    • Year: 2018
Evaluation of dominant and non-dominant hand movements for volleyball action modelling
    • 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
    • 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
    • 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
    • Authors: V. Naghashi, M. Boukadoum, AB Diallo
    • Journal: Scientific Reports
    • Year: 2025

José Cunha Vaz | Temporal Data Patterns | Best Researcher Award

Prof Dr. José Cunha Vaz | Temporal Data Patterns | Best Researcher Award

Association for Innovation and Biomedical Research on Light and Image, Portugal

Professional Profile 👨‍🎓

Scopus Profile

Orcid Profile

Early Academic Pursuits 📚

The journey of a distinguished academic career began with the completion of an MD at the University of Coimbra, followed by groundbreaking work across Europe. This early academic pursuit saw the completion of a PhD from the University of London Worldwide (1965) and another PhD from the University of Coimbra (1966), culminating in a Dr. Medical Science degree from the University of Coimbra in 1967. His academic training laid the foundation for a long and impactful career in medical research and clinical advancements.

Professional Endeavors 💼

Over the years, this expert has held pivotal roles as Principal Investigator (P.I.) on numerous research grants, including those from the National Institute of Health (NIH) and European Union-funded projects. His involvement with high-profile institutions and various international collaborations has made him a leader in retinal disease research, particularly within the realm of diabetic retinopathy and ocular diseases. His extensive consultancy work with industry giants such as Alcon, Novartis, and Merck further attests to his recognition in the professional sphere.

Contributions and Research Focus 🔬

His contributions to ophthalmology are monumental, particularly in the area of the Blood-Retinal Barrier (BRB). His pioneering work in identifying the anatomical location of the BRB and its subsequent breakdown in diseases like diabetes has been widely cited. He introduced vitreous fluorophotometry in 1975, a technique that revolutionized the detection of early diabetic retinopathy. His work on multimodal macular mapping has been a key innovation for the diagnosis and monitoring of retinal conditions, further cementing his legacy as a pioneer in ocular research.

Impact and Influence 🌍

His research has had a profound effect on clinical practices related to retinal diseases, influencing generations of ophthalmologists and researchers. His studies on the BRB, blood-retinal vessel permeability, and the use of imaging technologies in retinal diagnostics have shaped the treatment strategies for conditions like diabetic retinopathy and age-related macular degeneration. Through his pioneering work, he has transformed the understanding of diabetic retinal disease and its progression, particularly in terms of fluid dynamics and vascular permeability.

Academic Citations 📈

With a citation index of 4,713, his work is a cornerstone of modern ophthalmic research. His publications in top-tier journals like Ophthalmologica and The Journal of Physiology continue to be referenced in both basic and clinical research on diabetic retinopathy and retinal diseases. His contributions to high-impact journals have solidified his reputation as a leading figure in the field.

Technical Skills 🛠️

Known for his expertise in advanced imaging technologies, his technical skills include the development and application of innovative diagnostic techniques such as ocular fluorometry, confocal scanning laser fluorophotometry, and OCT-leakage technology. These tools have significantly advanced the detection and understanding of retinal pathologies. His work on multimodal imaging further highlights his technical expertise in integrating multiple diagnostic technologies to map and analyze retinal diseases in real-time.

Teaching Experience 👩‍🏫

Throughout his career, he has shared his extensive knowledge as a professor and mentor, inspiring countless students, researchers, and healthcare professionals. He has been an active participant in various scientific advisory councils and education initiatives, ensuring that his findings reach a broader audience. His editorial roles, including his tenure as Chief Editor for Ophthalmic Research and Ophthalmologica, have provided a platform for the next generation of ophthalmic researchers and clinicians to build upon his work.

Legacy and Future Contributions 🌟

His work has already left a lasting imprint on the field of ophthalmology. As a trailblazer in ocular imaging technologies and diabetic retinopathy research, his legacy will continue to shape clinical practices. With ongoing projects like the EuroVisionNet and EuroCONDOR, and new advancements in genetic polymorphisms related to retinal diseases, his contributions to understanding retinal disease progression remain vital. His continued research efforts promise to improve treatments for diabetic retinopathy, age-related macular degeneration, and other retinal conditions in the years to come.

 

Top Noted Publications 📖

  • Retinal neurodegeneration in eyes with NPDR risk phenotypes: A two‐year longitudinal study
    • Authors: Débora Reste‐Ferreira, Inês Pereira Marques, Torcato Santos, Maria Luísa Ribeiro, Luís Mendes, Ana Rita Santos, Conceição Lobo, José Cunha‐Vaz
    • Journal: Acta Ophthalmologica
    • Year: 2024
  • Characterization of central-involved diabetic macular edema using OCT and OCTA
    • Authors: Débora Reste-Ferreira, Torcato Santos, Inês Pereira Marques, Maria Luísa Ribeiro, Ana Rita Santos, António Cunha-Vaz Martinho, Conceição Lobo, José Cunha-Vaz
    • Journal: European Journal of Ophthalmology
    • Year: 2024
  • Central and Peripheral Involvement of the Retina in the Initial Stages of Diabetic Retinopathy
    • Authors: Ana Rita Santos, Ana Catarina Almeida, Ana Cláudia Rocha, Débora Reste-Ferreira, Inês Pereira Marques, António Cunha-Vaz Martinho, Luís Mendes, Torcato Santos, Warren Lewis, José Cunha-Vaz
    • Journal: Retina
    • Year: 2023
  • Serum glial fibrillary acidic protein and neurofilament light chain as biomarkers of retinal neurodysfunction in early diabetic retinopathy: results of the EUROCONDOR study
    • Authors: Hernández C, Olga Simó-Servat, Massimo Porta, Jakob Grauslund, Simon P. Harding, Ulrik Frydkjaer-Olsen, José García-Arumí, Luísa Ribeiro, Peter Scanlon, José Cunha-Vaz et al.
    • Journal: Acta Diabetologica
    • Year: 2023
  • Different Risk Profiles for Progression of Nonproliferative Diabetic Retinopathy: A 2-Year Study
    • Authors: Inês P. Marques, Maria L. Ribeiro, Torcato P. Santos, Luis G. Mendes, Débora Reste-Ferreira, Ana R. Santos, Conceição L. Lobo, José G. Cunha-Vaz
    • Journal: Ophthalmology and Therapy
    • Year: 2023
  • Perspectives of diabetic retinopathy—challenges and opportunities
    • Authors: Sobha Sivaprasad, Sagnik Sen, José Cunha-Vaz
    • Journal: Eye
    • Year: 2022
  • Characterization of 2-Year Progression of Different Phenotypes of Nonproliferative Diabetic Retinopathy
    • Authors: Luísa Ribeiro, Inês Marques, Torcato Santos, Sara Carvalho, Ana Rita B M Santos, Luís Mendes, Conceição Lobo, José Cunha-Vaz
    • Journal: Ophthalmic Research
    • Year: 2022
  • Common and rare genetic risk variants in age‐related macular degeneration and genetic risk score in the Coimbra eye study
    • Authors: Cláudia Farinha, Patricia Barreto, Rita Coimbra, Maria Luz Cachulo, Joana Barbosa Melo, José Cunha‐Vaz, Yara Lechanteur, Carel B. Hoyng, Silva R.
    • Journal: Acta Ophthalmologica
    • Year: 2022