Toktam Akbari Khalaj | Data Science and Analytics | Excellence in Research Award

Mrs Toktam Akbari Khalaj, Mashhad University of Medical Sciences, Iran

Mrs. Toktam Akbari Khalaj is a distinguished Iranian biostatistician known for her rigorous research in traffic injury prediction, prehospital emergency care, and health data modeling. With over two decades of professional experience and a dynamic academic career, she has significantly contributed to public health research, especially in North-Eastern Iran. Her publications, presented in reputed journals like Heliyon and BMC Public Health, emphasize the application of advanced statistical and machine learning techniques to address real-world health challenges. She serves as a project manager and biostatistician at Emergency Medical Services, and her proactive approach to forecasting health emergencies during crises like COVID-19 has drawn national attention. Fluent in both Persian and English, Mrs. Akbari Khalaj combines analytical excellence with outstanding communication and leadership skills. Her interdisciplinary approach and practical contributions make her an exceptional nominee for the Excellence in Research Award.

Publication Profile

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Education

Mrs. Akbari Khalaj holds a Master of Science (M.Sc.) in Biostatistics from Mashhad University of Medical Sciences (2017–2021), where she conducted a thesis on forecasting ambulance dispatches for traffic accidents using time series regression models. Prior to that, she earned a Bachelor of Science (B.Sc.) in Statistics from Azad University of Mashhad (2000–2004). Her academic background provided a solid foundation in statistical modeling, data mining, and biostatistical applications in health systems. Her postgraduate training enabled her to develop specialized expertise in predictive analytics and epidemiological modeling, particularly in trauma and emergency settings. Her advanced research skills have led her to publish and collaborate across multiple health domains. She also holds a TOEFL iBT score of 101, reflecting strong English proficiency. These academic credentials, combined with her practical research, reflect her dedication to applying theoretical insights into meaningful public health solutions.

Experience

Mrs. Akbari Khalaj brings a wealth of professional experience in statistical analysis and healthcare research. She began as a statistician at Emergency Medical Services (EMS) in 2007, transitioning into a biostatistician role in 2017. Since 2021, she has served as a project manager at EMS, overseeing data-driven projects in health surveillance, prehospital care, and trauma analytics. She has also worked as a researcher at Azad University (2002–2004) and Mashhad University of Medical Sciences (2018–2022), contributing to both academic and operational research. Her expertise in handling large datasets, implementing time series and logistic regression models, and her proficiency in R, Stata, SPSS, and Power BI, make her a cornerstone in data-informed decision-making. Beyond technical prowess, she is known for her leadership in emergency response analytics and evidence-based planning, especially during mass gatherings and pandemic crises. Her multidisciplinary involvement makes her an ideal candidate for research distinction.

Awards and Honors

While specific awards or formal recognitions are not explicitly listed, Mrs. Akbari Khalaj’s academic and professional contributions reflect honor-worthy distinction. Her co-authored and first-authored publications in high-impact journals such as BMC Public Health and Heliyon indicate peer recognition and scholarly influence. She has presented at prestigious events like the International Congress on Health in Arbaeen and the International Congress on Prehospital Emergency Innovation, signifying academic acknowledgment. Her long-standing role as project manager at EMS and her collaborative research with top Iranian health institutions underscore her leadership and credibility. Notably, her involvement in managing and modeling public health emergencies, such as during COVID-19, highlights the real-world impact of her work. These accomplishments reflect an ongoing trajectory of professional recognition that aligns with the spirit of the Excellence in Research Award.

Research Focus

Mrs. Akbari Khalaj’s research is rooted in biostatistics and emergency health systems, with a core focus on time series modeling, logistic regression, and big data analytics in traffic and trauma-related health incidents. She has applied innovative statistical methods to predict ambulance dispatches, assess injury mortality, and evaluate prehospital emergency trends in urban Iran. Her work addresses the intersection of public health, emergency response, and predictive modeling, often exploring the effects of external factors like COVID-19. Additionally, she is engaged in meta-analysis, count data modeling, machine learning, and data visualization for public health monitoring. Her research is both preventive and responsive, aiming to enhance policy decisions and emergency service planning. By integrating advanced computational tools with field data, Mrs. Akbari Khalaj’s work significantly contributes to predictive healthcare and operational efficiency. Her research output supports a data-driven approach to public health crisis management.

Publication Top Notes

Multiple-scale spatial analysis of paediatric, pedestrian road traffic injuries in a major city in North-Eastern Iran 2015–2019

Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice

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

An exploration of occupational violence among emergency medical staff of a major medical university; 2020

Evaluation of Prehospital Emergency Medical Services before and after COVID-19 in Mashhad

GENERAL WIEW OF COMPARISON BETWEEN SMART BOARD & BLACK BOARD IN GENERAL MATHEMATHICS BOOK 1 & 2 AMONG IRANIAN HIGH SCHOOL

Analysis of the Patterns of Mortality Causes in Traffic Accident Injuries Using Logistic Regression Model in Northeastern Iran

Muhammad Qaiser Shafi | Quantitative Hypotheses | Best Researcher Award

Mr Muhammad Qaiser Shafi, FAST National University of Computer & Emerging Sciences, Islamabad, Pakistan, Pakistan

Mr. Muhammad Qaiser Shafi is a dedicated academic and HR professional, currently serving as a Lecturer at FAST School of Management, FAST-NUCES, Islamabad, Pakistan. He is pursuing a PhD in Human Resource Management (HR/People Analytics) from COMSATS University Islamabad. With over 9 years of extensive experience in both academia and the corporate sector, Mr. Shafi has significantly contributed to the fields of HRM, leadership, green HRM, and employee behavior. He has published 20 research papers in top-tier journals and has presented at numerous local and international conferences. A versatile trainer and mentor, he has conducted workshops on HR Analytics, AI Tools for Literature, and data analysis software, demonstrating a deep commitment to education and research. His profound expertise and continuous academic excellence make him a distinguished candidate for the Best Researcher Award.

Education

Mr. Muhammad Qaiser Shafi’s academic journey reflects excellence and dedication. He is currently enrolled in a PhD program specializing in Human Resource Management (HR/People Analytics) at COMSATS University Islamabad, having completed his coursework with a CGPA of 3.6 and progressing towards his thesis. He earned his MS in HRM from Quaid-i-Azam University Islamabad, graduating with an impressive CGPA of 4.4. His undergraduate education, a BBA Hons (HRM) also from Quaid-i-Azam University, was completed with a CGPA of 3.7. Before his university education, he secured top grades during his Intermediate (I.Com) from Punjab College of Information Technology and Matriculation in Computer Science, securing A+ distinctions. His educational background forms a solid foundation for his academic and research achievements, reflecting a consistent pursuit of knowledge and skill enhancement.

Experience

Mr. Muhammad Qaiser Shafi brings over 9 years of diversified experience across academia and the corporate world. He is currently a Lecturer at FAST School of Management, FAST-NUCES, Islamabad, where he teaches HRM, Strategic Management, and Advanced Research Methods, while also mentoring students and supervising research projects. Prior to this, he served at Riphah International University as a Senior Lecturer and PhD Focal Person, leading academic discussions, coordinating PhD programs, and implementing research initiatives. His corporate experience includes working as an HR Officer at the National Logistics Cell (NLC) and an HR Trainee at Oil & Gas Development Company Limited (OGDCL), where he developed expertise in training, recruitment, data analysis, and HR operations. His rich blend of teaching, research, and corporate HR experience uniquely positions him as a dynamic academic and HR professional.

Awards and Honors

Mr. Muhammad Qaiser Shafi has received several accolades that underscore his excellence and dedication. He was awarded “Best Employee/Faculty Member” for two consecutive years (2020-2021 and 2021-2022). He secured an international research grant worth USD 3000 from the International Institute of Islamic Thought (IIIT), USA. His scholarly contributions are recognized through certifications for presenting papers at prestigious conferences hosted by LUMS, NUST, UMT, Riphah University, and JWU. Mr. Shafi is also a certified HR Analytics professional from the University of California, Irvine (via Coursera) and serves as a reviewer for notable journals like the Journal of Organizational Effectiveness: People and Performance and Journal of Islamic Business and Management. These honors reflect his commitment to research excellence and continuous professional development.

Research Focus

Mr. Muhammad Qaiser Shafi’s research interests lie primarily in Human Resource Analytics, Green HRM, leadership behaviors, employee personality traits, and organizational citizenship behavior. He explores contemporary themes such as the impact of inclusive leadership on project success, linking HR practices with sustainable employee behavior, and the mediating roles of employee engagement and project citizenship behavior. His work often combines behavioral theories with statistical analysis tools like SmartPLS and SPSS, offering actionable insights for academia and industry. His focus on People Analytics represents a modern, data-driven approach to HRM research, while his publications on topics like project management and green behavior address current global business challenges. Mr. Shafi’s research blends theoretical depth with practical relevance, aiming to enhance both organizational performance and employee well-being.

Publication Top Notes

1. From Inclusion to Action: Does Project Manager’s Inclusive Leadership Drive Team Member’s Project Citizenship Behavior? — International Journal of Project Management (IF 7.4, 2025)
2. Predicting Required and Voluntary Employee Green Behavior Using the Theory of Planned Behavior — Corporate Social Responsibility and Environmental Management (IF 8.7, 2022)
3. The Mediating Role of Project Citizenship Behavior in the Relationship Between Organizational Justice Dimensions and Project Success — Project Management Journal (IF 4.9, 2021)
4. Job Crafting and Innovative Behaviour: Examining Mediation and Moderation Mechanism — International Journal of Technological Learning, Innovation and Development (X category, 2021)

Conclusion

Given Mr. Muhammad Qaiser Shafi’s outstanding academic background, diverse professional experience, impressive research portfolio, and numerous accolades, he is exceptionally well-suited for the Best Researcher Award. His continuous contributions to the academic community through impactful research, mentoring, training, and active participation in conferences and journal reviews demonstrate his unwavering commitment to advancing knowledge and practice in Human Resource Management. His blend of practical HR experience and high-impact research sets him apart as a leading academician and makes him a deserving candidate for this prestigious honor.

Muhammad Qaiser Shafi | Quantitative Hypotheses | Best Researcher Award