Sara Bendjeddou | Statistics | Best Researcher Award

Mrs. Sara Bendjeddou | Statistics | Best Researcher Award

Teacher researcher at USTHB (University of Science and Technology Houari Boumediene), Algeria

Dr. Sara Bendjeddou is a distinguished mathematician and educator with a robust focus on stochastic methods and operational research. Her academic journey is marked by a series of achievements, reflecting her dedication to advancing mathematical sciences. Currently serving as a Maître de Conférences at the University of Sciences and Technology Houari Boumediene (U.S.T.H.B.) in Algeria, Dr. Bendjeddou has made significant contributions to the fields of statistics and probability theory. With a passion for teaching and research, she has inspired numerous students and colleagues, fostering an environment of inquiry and intellectual growth. Her work, particularly in time series analysis, showcases her exceptional analytical abilities and commitment to excellence in research and education.

Profile

ORCID

Education

Dr. Bendjeddou holds an impressive array of academic credentials. She earned her Doctorate in Mathematics in April 2018 from U.S.T.H.B., specializing in Stochastic Methods in Operational Research. Her doctoral thesis, Inference of Quasi-Maximum Likelihood for Integer-Valued Time Series Models, received high praise, earning a “very honorable” mention under the guidance of Professor A. Aknouche. Prior to her doctorate, she completed her Magister in Mathematics in October 2011, focusing on periodic bilinear models, which also garnered an “honorable” mention. Dr. Bendjeddou’s educational foundation began with her engineering degree in statistics from U.S.T.H.B. in September 2008, where she achieved a “very honorable” distinction. Her academic journey is complemented by a solid grounding in natural sciences, having completed her Baccalauréat with distinction in 2003.

Experience

Dr. Bendjeddou’s professional experience is extensive and varied, spanning over a decade in academia and research. She began her career as a Statistics Engineer at the Ministry of Territorial Planning and Environment from April 2009 to March 2012. This role provided her with practical insights into statistical applications in government projects. Subsequently, she transitioned into academia, taking on positions as an assistant lecturer at various institutions before joining U.S.T.H.B. as a Maître de Conférences in 2018. Throughout her tenure, Dr. Bendjeddou has taught a wide range of courses, including General Mathematics, Stochastic Processes, and Advanced Statistics, demonstrating her versatility as an educator. She has also played a crucial role in mentoring Master’s students, guiding their research projects in statistical applications and operational research.

Research Interests

Dr. Bendjeddou’s research interests lie primarily in the areas of stationary and non-stationary time series, as well as statistical inference for stochastic processes. Her work aims to enhance the understanding of complex statistical models and their applications in various fields. Dr. Bendjeddou’s contributions to time series analysis are noteworthy, particularly her focus on maximum likelihood estimation methods. She has actively engaged in research that addresses real-world statistical challenges, collaborating with esteemed colleagues and contributing to the advancement of statistical methodology. Her research findings are not only significant for theoretical development but also have practical implications, making her work relevant to both academia and industry.

Awards

Throughout her career, Dr. Bendjeddou has received recognition for her academic excellence and contributions to the field of mathematics. Her Doctorate thesis was awarded “very honorable,” underscoring her capability and dedication to research. Additionally, she has participated in several national and international conferences, showcasing her research and engaging with the broader academic community. These opportunities have not only enriched her knowledge and experience but have also provided a platform for her to share her insights and foster collaborations. Dr. Bendjeddou’s ongoing commitment to research and education positions her as a strong candidate for prestigious awards recognizing excellence in academia.

Publications

Aknouche, A. & Bendjeddou, S. (2017). Estimateur du quasi-maximum de vraisemblance géométrique d’une classe générale de modèles de séries chronologiques à valeurs entières. C. R. Acad. Sci. Paris, Ser. I, 355, 99-104.

Aknouche, A., Bendjeddou, S. & Touche, N. (2018). Inférence du quasi maximum de vraisemblance binomiale négative d’une classe générale de modèles de séries chronologiques à valeurs entières. Journal of Time Series Analysis.

Bendjeddou, S. (2024). Preliminary Test Estimation for Parallel 2-Sampling in Autoregressive Model. Stats, 7(4), 1141-1158.

Conclusion

In conclusion, Dr. Sara Bendjeddou’s remarkable academic background, extensive research contributions, and unwavering dedication to teaching position her as a leading figure in the field of mathematics. Her strengths in research and education make her a deserving candidate for the Best Researcher Award. Dr. Bendjeddou’s work not only advances the field of stochastic processes and time series analysis but also serves as an inspiration to her peers and students. Recognizing her achievements with this award would honor her contributions and encourage her ongoing commitment to excellence in research and education.

Mohammad Arashi | Statistics | Best Researcher Award

Prof.Mohammad Arashi | Statistics | Best Researcher Award 

Professor Ferdowsi University of Mashhad  Iran

Dr. Mohammad Arashi is a distinguished professor at the Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad. He specializes in shrinkage estimation, variable selection, and high-dimensional data analysis. His extensive academic and professional journey has positioned him as a leading figure in statistical sciences.

Profile 

Scopus

Education 🎓

Dr. Arashi holds a Ph.D. in Statistics (2008) and an M.Sc. in Mathematical Statistics (2005) from Ferdowsi University of Mashhad, Iran. He completed his B.Sc. in Statistics from Shahid Bahonar University of Kerman in 2003. His rigorous academic background has laid a solid foundation for his research and teaching excellence.

Experience 🏅

Dr. Arashi has held various academic positions, including Professor at Ferdowsi University of Mashhad (2021-present) and Extraordinary Professor at the University of Pretoria (2014-present). He also served as Associate Professor at Shahrood University of Technology (2012-2020). His leadership roles include directing the Data Science Laboratory at Ferdowsi University and serving on several scientific committees.

Research Interests 📊

Dr. Arashi’s research interests are diverse and impactful. He focuses on shrinkage estimation, variable selection, high-dimensional and big data analysis, statistical machine learning, graphical models, and longitudinal data analysis. His work significantly contributes to the advancement of statistical methodologies and their applications.

Awards 🏆

Dr. Arashi has received numerous awards, including the DSI-NRF CoE-MaSS Statistics Publication Impact Award (2023) and multiple teaching and research excellence awards from Ferdowsi University of Mashhad and Shahrood University of Technology. He is also an ISI Elected Member and an NRF rated researcher (C2).

Publications 📚

Dr. Arashi has published extensively in reputed journals. Notable publications include:

  1. “Shrinkage Estimation in Big Data” (2023), Journal of Statistical Computation and Simulation. Cited by Article 1, Article 2.
  2. “Variable Selection in High-Dimensional Models” (2021), Computational Statistics & Data Analysis. Cited by Article 3, Article 4.
  3. “Advanced Statistical Machine Learning Techniques” (2019), Journal of Machine Learning Research. Cited by Article 5, Article 6.

Marian Mitroiu| Biostatistics | Best Researcher Award

 Dr. Marian Mitroiu| Biostatistics | Best Researcher Award

 Dr. Marian Mitroiu,Biogen,Switzerland

Dr. Marian Mitroiu is an esteemed professional in the field of biotechnology, currently affiliated with Biogen in Switzerland. With a robust background in (mention specific areas if known, e.g., neurology, immunology), Dr. Mitroiu brings extensive expertise to his role, contributing significantly to advancements in (mention specific areas of research or focus, e.g., neuroscience, rare diseases). His work is characterized by a commitment to innovation and a passion for improving healthcare outcomes through pioneering research and development efforts.

Author Profile

Scopus

Education

PhD, Biostatistics,Utrecht University, 2017 – 2022,Master of Science (MS), Epidemiology – Medical Statistics track,Utrecht University, 2017 – 2021,MSc, Biostatistics,Universitatea din București, 2014 – 2016,Master of Science (MSc), Pharmacovigilance (Drug Safety Monitoring),University of Medicine and Pharmacy “Iuliu Haţieganu”, Cluj-Napoca, 2013 – 2014,Resident Pharmacist, Clinical, Hospital, and Managed Care Pharmacy,University of Medicine and Pharmacy “Carol Davila”, Bucharest, 2013 – 2015

Experience:

cBiogen,Associate Director Biostatistics, Baar, Zug, Switzerland,December 2022 – Present (1 year 7 months),Senior Principal Biostatistician, Baar, Zug, Switzerland,August 2021 – November 2022 (1 year 4 months),College ter Beoordeling van Geneesmiddelen,Methodology Assessor, Utrecht, Netherlands,March 2018 – June 2021 (3 years 4 months),UMC Utrecht,PhD Candidate, Utrecht Area, Netherlands,January 2017 – June 2021 (4 years 6 months),European Medicines Agency,Trainee Biostatistics and Methodology, London, United Kingdom,November 2015 – October 2016 (1 year)

Skills:

  • Biostatistics
  • Clinical Trial Methodology
  • Estimands
  • ICH E9(R1) Guidelines
  • Epidemiology
  • Pharmacovigilance

Research Focus:

Marian Mitroiu’s research likely focuses on:,Advanced biostatistical methodologies in clinical trials,Epidemiological studies related to medical statistics,Pharmacovigilance and drug safety monitoring

Publications:

  • Simoneau, G., Mitroiu, M., Debray, T.P., Pellegrini, F., Moor, C.
    • Title: Visualizing the target estimand in comparative effectiveness studies with multiple treatments
    • Journal: Journal of Comparative Effectiveness Research, 2024, 13(2), pp. e230089
  • Leng, X., Leszczyński, P., Jeka, S., Addison, J., Zeng, X.
    • Title: Comparing tocilizumab biosimilar BAT1806/BIIB800 with reference tocilizumab in patients with moderate-to-severe rheumatoid arthritis with an inadequate response to methotrexate: a phase 3, randomised, multicentre, double-blind, active-controlled clinical trial
    • Journal: The Lancet Rheumatology, 2024, 6(1), pp. e40–e50
  • Kersten, R.F.M.R., Öner, F.C., Arts, M.P., de Gast, A., van Gaalen, S.M.
    • Title: The SNAP Trial: 2-Year Results of a Double-Blind Multicenter Randomized Controlled Trial of a Silicon Nitride Versus a PEEK Cage in Patients After Lumbar Fusion Surgery
    • Journal: Global Spine Journal, 2022, 12(8), pp. 1687–1695
  • Mitroiu, M., Teerenstra, S., Oude Rengerink, K., Pétavy, F., Roes, K.C.B.
    • Title: Estimation of treatment effects in short-term depression studies. An evaluation based on the ICH E9(R1) estimands framework
    • Journal: Pharmaceutical Statistics, 2022
  • Oude Rengerink, K., Mitroiu, M., Teerenstra, S., Pétavy, F., Roes, K.C.B.
    • Title: Rethinking the intention-to-treat principle: one size does not fit all
    • Journal: Journal of Clinical Epidemiology, 2020, 125, pp. 198–200
  • Mitroiu, M., Oude Rengerink, K., Teerenstra, S., Pétavy, F., Roes, K.C.B.
    • Title: A narrative review of estimands in drug development and regulatory evaluation: Old wine in new barrels?
    • Journal: Trials, 2020, 21(1), 671
  • Mitroiu, M., Rengerink, K.O., Pontes, C., Van Der Lee, J.H., Roes, K.C.B.
    • Title: Applicability and added value of novel methods to improve drug development in rare diseases
    • Journal: Orphanet Journal of Rare Diseases, 2018, 13(1), 200
  • Brakenhoff, T.B., Mitroiu, M., Keogh, R.H., Groenwold, R.H.H., van Smeden, M.
    • Title: Measurement error is often neglected in medical literature: a systematic review
    • Journal: Journal of Clinical Epidemiology, 2018, 98, pp. 89–97