Toktam Akbari Khalaj | health profession | Research excellence endeavor award

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Mrs.Toktam Akbari Khalaj | health profession | Research excellence endeavor award

Mrs . Toktam Akbari Khalaj Mashhad University of Medical Sciences, Emergency Medical Services Iran

Summary:

Toktam Akbari Khalaj is a dedicated biostatistician and researcher with extensive experience in emergency medical services and public health. With a Master’s degree in Biostatistics from Mashhad University of Medical Sciences, Toktam has focused on forecasting and statistical modeling, particularly in relation to prehospital emergency care and traffic accident analysis. Their research contributions include several publications in reputable journals and presentations at international conferences, emphasizing the impact of various factors on emergency medical response and outcomes.

 

Professional Profile:

   Google Scholar

🎓 Education

M.Sc. in Biostatistics (2017-2021)Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.B.Sc. in Statistics (2000-2004)Department of Science, Azad University of Mashhad, Iran.

📜 Master Thesis

Forecasting the number of dispatches of ambulances for traffic accidents in Mashhad and assessing related factors using the Time Series Regression Model.

🔍 Research Interests

Time Series ,Mathematical and Statistical Modeling ,Biostatistics ,Big Data Analysis ,Count Data ,Machine Learning ,Bioinformatics ,Data Mining ,Statistical Analysis with Missing Data ,Meta-analysis .

📖 Research Background

Researcher at Azad University of Mashhad (2002-2004).Researcher at Mashhad University of Medical Sciences (2018-2022)

💼 Job Experiences

Statistician at Emergency Medical Services (2007-2017)Biostatistician at Emergency Medical Services (2017-Present)Manager at Emergency Medical Services (2021-Present).

💡 Other Experiences and Skills

Proficient in statistical software (SPSS, Stata, R, Minitab) Familiar with computer skills (Office, Photoshop, Excel, Power BI, SharePoint) Proficiency in data visualization tools (e.g., Power BI) Strong communication skills

 Publication:

  • Title: Multiple-scale spatial analysis of paediatric, pedestrian road traffic injuries in a major city in North-Eastern Iran 2015–2019
    Author(s): H. Shabanikiya, S. Hashtarkhani, R. Bergquist, N. Bagheri, R. Vafaei Nejad, …
    Year: 2020

 

  • Title: Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice
    Author(s): A. Azimi, N. Bagheri, S.M. Mostafavi, M.A. Furst, S. Hashtarkhani, F.H. Amin, …
    Year: 2021

 

  • Title: Comparison of GAP, R-GAP, and new trauma score (NTS) systems in predicting mortality of traffic accidents that injure hospitals at Mashhad University of Medical Sciences
    Author(s): T. Kenarangi, F. Rahmani, A. Yazdani, G.D. Ahmadi, M. Lotfi, T.A. Khalaj
    Year: 2024

 

  • Title: Evaluation of Prehospital Emergency Medical Services before and after COVID-19 in Mashhad
    Author(s): T.A. Khalaj, N. Sangsefidi, H. Shafaei, A. Yazdani, H. Mahzoun, G.D. Ahmadi
    Year: 2023

Conclusion:

Toktam Akbari Khalaj exemplifies a commitment to advancing the field of biostatistics and emergency medical services through rigorous research and collaboration. Their work not only contributes to academic knowledge but also provides valuable insights that can enhance the efficiency and effectiveness of emergency medical systems in Iran and beyond. As they continue to engage in innovative research and professional development, Toktam is poised to make significant contributions to the health sciences, addressing critical challenges in emergency care and public health. Their journey reflects the importance of interdisciplinary collaboration in driving meaningful change in healthcare practices.

 

 

Maksym Lupei | Predictive Analytics | Best Paper Award

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Dr. Maksym Lupei | Predictive Analytics | Best Paper Award

Doctorate at The Pennsylvania State University, United States

Summary:

Dr. Maksym Lupei is a dedicated researcher and academic with extensive expertise in machine learning and computational genomics. Holding a Ph.D. in Information Technologies and Machine Learning from Uzhhorod National University, he has contributed significantly to the fields of text mining and artificial intelligence. Currently a Postdoctoral Researcher at The Pennsylvania State University, Dr. Lupei is recognized for his innovative work in developing large language models and optimizing computational frameworks for biomedical data analysis. His career reflects a blend of academic excellence and practical industry experience, underpinned by a strong commitment to advancing technology and data science.

Professional Profile:

👩‍🎓Education:

Ph.D. in Information Technologies and Machine Learning (2021)

  • Institution: Uzhhorod National University
  • Dissertation: Determining the Eligibility of Candidates for a Vacancy Using Artificial Neural Networks

MSc in Applied Mathematics (2013)

  • Institution: Uzhhorod National University
  • Thesis: .NET Websites Optimization

BSc in Applied Mathematics (2012)

  • Institution: Uzhhorod National University
  • Thesis: Modern Methods of Prediction

🏢 Professional Experience:

Dr. Maksym Lupei is currently a Postdoctoral Researcher in Computer Science & Engineering at The Pennsylvania State University (since August 2023), where he leads projects involving large language models for biomedical data fact-checking, computational genomics, and metagenomics. His work includes developing open-source text mining services and optimizing GPU infrastructure. Previously, he served as a Senior Research Fellow at the V. M. Glushkov Institute of Cybernetics of the National Academy of Science of Ukraine, specializing in machine learning and text mining (January 2022 – August 2023). At Uzhhorod National University, Dr. Lupei was an Assistant Professor in the Department of Informative and Operating Systems (December 2019 – January 2023), teaching programming languages and machine learning courses.

Dr. Lupei’s industry experience includes roles as an Engineering Manager at TIBCO Jaspersoft (March 2014 – February 2021), where he led cross-functional teams and established Agile/Scrum processes, and as a Full Stack Developer at JustAnswer (March 2011 – February 2014) and Swan Software Solutions (August 2010 – March 2011).

Research Interests

Dr. Lupei’s research interests encompass machine learning, large language models, computational genomics, metagenomics, and explainable artificial intelligence. His work focuses on processing large information arrays using mathematical methods, particularly in text mining.

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