Dr. Maliik Singh Sura brings an exceptional combination of advanced statistical training, biostatistical research, clinical-trial analysis, and computational expertise to the evaluation and interpretation of complex research data. He holds a Ph.D. in Mathematics and Statistics from the University of Massachusetts Amherst, complemented by a Master’s degree in Artificial Intelligence from the University of Rochester and a Master’s degree in Proteomics from the University of Chinese Academy of Sciences.
His research and professional experience spans biostatistics, clinical research, neurodegeneration, machine learning, and biomedical data analysis. As an Associate Research Fellow at Columbia University Irving Medical Center, Dr. Sura worked on modeling biomarker trajectories in patients with Alzheimer’s disease, addressing complex statistical challenges involving left truncation and informative censoring. This work reflects his ability to apply sophisticated statistical methodology to real-world biomedical and longitudinal research questions.
His experience also includes biostatistical work in the biotechnology sector, where he performed interim analyses and modeled the predicted probability of success of Phase II/III clinical trials involving personalized vaccines. He further applied real-world evidence methodologies to investigate approaches for reducing the number of patients required for Phase III clinical trials. Earlier experience in data science involved applying machine-learning and deep-learning techniques to complex scientific datasets.
Dr. Sura brings this breadth of quantitative expertise to statistical research support, helping researchers move confidently from raw data through appropriate statistical methodology, analysis, interpretation, and defensible reporting. His expertise is particularly valuable for dissertations, quantitative research studies, clinical and biomedical research, and systematic reviews requiring rigorous statistical analysis and evidence synthesis.
With a foundation spanning theoretical statistics, biostatistics, artificial intelligence, and biomedical science, Dr. Sura is equipped to address both conventional and advanced analytical challenges. His approach emphasizes methodological rigor, appropriate model selection, transparent interpretation, and clear communication of statistical findings, ensuring that complex analyses can be translated into results that are both technically defensible and accessible to researchers and readers.