Information Box Group
Timofei Biziaev
CANSTAT Fellow
Mentors: Tolu Sajobi and Michael Hill
Research Interests: Bayesian statistics, prognostic & diagnostic models, adaptive clinical trials
Bio: Tim is a statistical research analyst at the Person-Centered Methods Lab at the University of Calgary. He graduated with a master’s degree in Biostatistics from the University of Calgary in 2023 where he researched configuration of Bayesian variable selection regression models. He obtained his BSc in Mathematics from MacEwan University in Edmonton, Alberta in 2018. He has worked as a research assistant for Alberta Health Services in 2021/22 where he aided in development and performed validation of late-stage cancer risk prediction models.
Timofei Biziaev
CANSTAT Fellow
Yutong Chen
CANSTAT Fellow
Mentors: Monica Taljaard and Daniel McIsaac
Research Interests: Design and analysis of randomized controlled trials, exploring and applying novel methodologies such as machine learning to increase productivity and effectively analyze healthcare data
Bio: Yutong (Betty) Chen completed her MSc in Biostatistics from the University of Toronto and her undergraduate degree in Statistics from York University. During her master’s program, she conducted a practicum project titled “Using Generative Adversarial Networks for Sample Size Calculation” and interned as a Data Scientist at Roche, exploring the duties and responsibilities of a biostatistician. With a strong passion for healthcare data, she is eager to pursue opportunities to further expand her statistical analysis skills and knowledge and contribute to the fields of public health and drug development.
Yutong Chen
CANSTAT Fellow
Peter Greenstreet
CANSTAT Fellow
Mentors: Tim Ramsay and Dean Fergusson
Research Interests: Adaptive clinical trial designs, platform trials
Bio: Peter grew up in England where he did his PhD at Lancaster University. His PhD was in Statistics and Operational Research and was entitled: Design and Analysis of Platform Trials. He is working with the Ottawa Hospital Research Institute (OHRI). He is excited to start his new role, after spending a 6-week placement at the OHRI in January 2023 thanks to the STOR-i research grant. In his spare time Peter enjoys playing Underwater Hockey and is keen to join a team in Ottawa.
Peter Greenstreet
CANSTAT Fellow
Mei Han
CANSTAT Fellow
Mentors: Nick Barrowman and Amy Plint
Research Interests: Clinical trials design and analysis; Comparative effectiveness research
Bio: Mei completed her Master of Science in Biostatistics at the University of Toronto. She is now a methodologist at Children’s Hospital of Eastern Ontario Research Institute. With a focus on leveraging statistical methods to analyze and interpret data in the context of clinical trials and research studies, Mei has contributed to several projects aimed at improving patient outcomes and advancing medical knowledge. In addition to academic pursuits, Mei enjoys swimming.
Mei Han
CANSTAT Fellow
Qirui Hou
CANSTAT Fellow
Mentors: Sameer Parpia and Timothy Whelan
Research Interests: Adaptive clinical trial designs; Randomized trial analysis
Bio: Qirui Hou holds an MSc in Biostatistics from the University of Toronto. He served as a trainee at the Biostatistics Core Services of the Centre for Addiction and Mental Health (CAMH), where he worked on projects involving novel adaptive clinical trial designs. His research primarily focuses on Bayesian and frequentist adaptive trial design. Before coming to Toronto, Qirui completed his BSc in Statistics at the University of British Columbia. Outside of work, he enjoys windsurfing, badminton, and tennis.
Qirui Hou
CANSTAT Fellow
Mohammed Mujaab Kamso
CANSTAT Fellow
Mentors: George Wells and Glen Hazelwood
Research Interests: Research designs, evidence synthesis; comparative effectiveness research; Adaptive clinical trial designs; Bayesian Analysis; Network Meta-analysis; Evaluation of the Certainty of Evidence using the GRADE framework
Bio: Dr. Mohammed Mujaab Kamso is a Biostatistician trainee at the Cardiovascular Research Methods Centre (CRMC) at the University of Ottawa. He recently earned his Ph.D. and has extensive experience in evidence synthesis. His research focused on developing novel semi-automated methodologies for trial identification and the evaluation of the certainty of evidence in Network Meta-Analyses (NMAs). Utilizing his expertise in R statistical software, Dr. Kamso designed rules, algorithms, and Shiny dashboards to streamline these processes. He is an active member of an international collaborative research group, where he implements innovative strategies to improve the evidence base for various interventions in rheumatoid arthritis (RA). Currently, he plans to integrate his formal education and work experience into the design and analysis of clinical trials. By contributing to the generation of new information via clinical trials, he aims to further refine and optimize methodologies in the critical areas of RA and cardiovascular health research, among others.
Mohammed Mujaab Kamso
CANSTAT Fellow
Graeme Kempf
CANSTAT Fellow
Mentors: Joel Singer and Jim Russell
Research Interests: Multi-state models, pharmacoepidemiology studies, design and analysis of randomized trials
Bio: I completed my MSc in Statistics at the University of British Columbia in 2024. My thesis was titled “The impact of disease-modifying drugs for multiple sclerosis on hospitalizations and mortality in British Columbia: a retrospective study using an illness-death multi-state model”. I previously graduated from Wilfrid Laurier University with two degrees, a BSc in Data Science and a Bachelor of Business Administration.
Graeme Kempf
CANSTAT Fellow
Yutong Lu
CANSTAT Fellow
Mentors: Kevin Thorpe and David Mazer
Research Interests: Clinical trial design and analysis, causal inference, predictive models in healthcare
Bio: Yutong Lu earned her MSc in Biostatistics with an emphasis in Artificial Intelligence and Data Science from the University of Toronto. During her Master’s program, she completed a practicum project titled “Knowledge fusion of large chemical language models for molecular property prediction” under the guidance of Dr. Pingzhao Hu. She also holds a BSc from the University of Toronto, where she pursued a Specialist in Statistical Science: Methods and Practice with a focus on Health and Disease. Moving forward, Yutong aims to further develop her theoretical knowledge and practical skills to contribute to clinical trials and other fields in healthcare.
Yutong Lu
CANSTAT Fellow
Lara Maleyeff
CANSTAT Fellow
Mentors: Shirin Golchi and Marie Hudson
Research Interests: Bayesian adaptive designs, clinical trials, precision medicine, treatment effect heterogeneity
Bio: Lara Maleyeff, PhD is a postdoctoral fellow in biostatistics at McGill University, where she specializes in precision medicine and clinical trial design. Her research focuses on utilizing Bayesian model averaging and adaptive enrichment designs to optimize treatment strategies for chronic conditions like rheumatoid arthritis. Lara completed her PhD at Harvard University, where her dissertation addressed treatment effect heterogeneity in cluster randomized trials.
Lara Maleyeff
CANSTAT Fellow
Myanca Rodrigues
CANSTAT Fellow
Mentors: Lawrence Mbuagbaw and Zainab (Zena) Samaan
Research Interests: Causal inference; Comparative effectiveness research; Mental health
Bio: Myanca Rodrigues holds a MSc in Epidemiology and Biostatistics from Western University and a PhD in Health Research Methodology (Biostatistics specialization) from McMaster University. Her dissertation examined outcome measurement in mental health research, including geriatric depression trials. Myanca is eager to develop her statistical skills in the design and analysis of clinical trials assessing interventions for psychiatric disorders.
Myanca Rodrigues
CANSTAT Fellow
Shabnam Vatanpour
CANSTAT Fellow
Mentors: Tolu Sajobi and Michael Hill
Research Interests: Adaptive clinical trial designs; Statistical and machine-learning methods for advancing precision medicine and digital health; Risk prediction tools
Bio: Dr. Shabnam Vatanpour is a Biostatistician with the Calgary Stroke Program in the Department of Clinical Neurosciences at the University of Calgary. Her expertise lies in developing and applying statistical and machine learning techniques to extract meaningful insights from health data, facilitating evidence-based decision-making. With extensive experience collaborating with clinical investigators and multidisciplinary research teams, she is highly proficient in utilizing administrative health data in the areas of patient outcomes and healthcare services. Dr. Vatanpour collaborates closely with the Stroke Clinical Trials Group, providing support for various innovative clinical trials.
Shabnam Vatanpour
CANSTAT Fellow
Timofei Biziaev
CANSTAT Fellow
Mentors: Tolu Sajobi and Michael Hill
Research Interests: Bayesian statistics, prognostic & diagnostic models, adaptive clinical trials
Bio: Tim is a statistical research analyst at the Person-Centered Methods Lab at the University of Calgary. He graduated with a master’s degree in Biostatistics from the University of Calgary in 2023 where he researched configuration of Bayesian variable selection regression models. He obtained his BSc in Mathematics from MacEwan University in Edmonton, Alberta in 2018. He has worked as a research assistant for Alberta Health Services in 2021/22 where he aided in development and performed validation of late-stage cancer risk prediction models.
Timofei Biziaev
CANSTAT Fellow
Mentors: Tolu Sajobi and Michael Hill
Research Interests: Bayesian statistics, prognostic & diagnostic models, adaptive clinical trials
Bio: Tim is a statistical research analyst at the Person-Centered Methods Lab at the University of Calgary. He graduated with a master’s degree in Biostatistics from the University of Calgary in 2023 where he researched configuration of Bayesian variable selection regression models. He obtained his BSc in Mathematics from MacEwan University in Edmonton, Alberta in 2018. He has worked as a research assistant for Alberta Health Services in 2021/22 where he aided in development and performed validation of late-stage cancer risk prediction models.
Yutong Chen
CANSTAT Fellow
Mentors: Monica Taljaard and Daniel McIsaac
Research Interests: Design and analysis of randomized controlled trials, exploring and applying novel methodologies such as machine learning to increase productivity and effectively analyze healthcare data
Bio: Yutong (Betty) Chen completed her MSc in Biostatistics from the University of Toronto and her undergraduate degree in Statistics from York University. During her master’s program, she conducted a practicum project titled “Using Generative Adversarial Networks for Sample Size Calculation” and interned as a Data Scientist at Roche, exploring the duties and responsibilities of a biostatistician. With a strong passion for healthcare data, she is eager to pursue opportunities to further expand her statistical analysis skills and knowledge and contribute to the fields of public health and drug development.
Yutong Chen
CANSTAT Fellow
Mentors: Monica Taljaard and Daniel McIsaac
Research Interests: Design and analysis of randomized controlled trials, exploring and applying novel methodologies such as machine learning to increase productivity and effectively analyze healthcare data
Bio: Yutong (Betty) Chen completed her MSc in Biostatistics from the University of Toronto and her undergraduate degree in Statistics from York University. During her master’s program, she conducted a practicum project titled “Using Generative Adversarial Networks for Sample Size Calculation” and interned as a Data Scientist at Roche, exploring the duties and responsibilities of a biostatistician. With a strong passion for healthcare data, she is eager to pursue opportunities to further expand her statistical analysis skills and knowledge and contribute to the fields of public health and drug development.
Peter Greenstreet
CANSTAT Fellow
Mentors: Tim Ramsay and Dean Fergusson
Research Interests: Adaptive clinical trial designs, platform trials
Bio: Peter grew up in England where he did his PhD at Lancaster University. His PhD was in Statistics and Operational Research and was entitled: Design and Analysis of Platform Trials. He is working with the Ottawa Hospital Research Institute (OHRI). He is excited to start his new role, after spending a 6-week placement at the OHRI in January 2023 thanks to the STOR-i research grant. In his spare time Peter enjoys playing Underwater Hockey and is keen to join a team in Ottawa.
Peter Greenstreet
CANSTAT Fellow
Mentors: Tim Ramsay and Dean Fergusson
Research Interests: Adaptive clinical trial designs, platform trials
Bio: Peter grew up in England where he did his PhD at Lancaster University. His PhD was in Statistics and Operational Research and was entitled: Design and Analysis of Platform Trials. He is working with the Ottawa Hospital Research Institute (OHRI). He is excited to start his new role, after spending a 6-week placement at the OHRI in January 2023 thanks to the STOR-i research grant. In his spare time Peter enjoys playing Underwater Hockey and is keen to join a team in Ottawa.
Mei Han
CANSTAT Fellow
Mentors: Nick Barrowman and Amy Plint
Research Interests: Clinical trials design and analysis; Comparative effectiveness research
Bio: Mei completed her Master of Science in Biostatistics at the University of Toronto. She is now a methodologist at Children’s Hospital of Eastern Ontario Research Institute. With a focus on leveraging statistical methods to analyze and interpret data in the context of clinical trials and research studies, Mei has contributed to several projects aimed at improving patient outcomes and advancing medical knowledge. In addition to academic pursuits, Mei enjoys swimming.
Mei Han
CANSTAT Fellow
Mentors: Nick Barrowman and Amy Plint
Research Interests: Clinical trials design and analysis; Comparative effectiveness research
Bio: Mei completed her Master of Science in Biostatistics at the University of Toronto. She is now a methodologist at Children’s Hospital of Eastern Ontario Research Institute. With a focus on leveraging statistical methods to analyze and interpret data in the context of clinical trials and research studies, Mei has contributed to several projects aimed at improving patient outcomes and advancing medical knowledge. In addition to academic pursuits, Mei enjoys swimming.
Qirui Hou
CANSTAT Fellow
Mentors: Sameer Parpia and Timothy Whelan
Research Interests: Adaptive clinical trial designs; Randomized trial analysis
Bio: Qirui Hou holds an MSc in Biostatistics from the University of Toronto. He served as a trainee at the Biostatistics Core Services of the Centre for Addiction and Mental Health (CAMH), where he worked on projects involving novel adaptive clinical trial designs. His research primarily focuses on Bayesian and frequentist adaptive trial design. Before coming to Toronto, Qirui completed his BSc in Statistics at the University of British Columbia. Outside of work, he enjoys windsurfing, badminton, and tennis.
Qirui Hou
CANSTAT Fellow
Mentors: Sameer Parpia and Timothy Whelan
Research Interests: Adaptive clinical trial designs; Randomized trial analysis
Bio: Qirui Hou holds an MSc in Biostatistics from the University of Toronto. He served as a trainee at the Biostatistics Core Services of the Centre for Addiction and Mental Health (CAMH), where he worked on projects involving novel adaptive clinical trial designs. His research primarily focuses on Bayesian and frequentist adaptive trial design. Before coming to Toronto, Qirui completed his BSc in Statistics at the University of British Columbia. Outside of work, he enjoys windsurfing, badminton, and tennis.
Mohammed Mujaab Kamso
CANSTAT Fellow
Mentors: George Wells and Glen Hazelwood
Research Interests: Research designs, evidence synthesis; comparative effectiveness research; Adaptive clinical trial designs; Bayesian Analysis; Network Meta-analysis; Evaluation of the Certainty of Evidence using the GRADE framework
Bio: Dr. Mohammed Mujaab Kamso is a Biostatistician trainee at the Cardiovascular Research Methods Centre (CRMC) at the University of Ottawa. He recently earned his Ph.D. and has extensive experience in evidence synthesis. His research focused on developing novel semi-automated methodologies for trial identification and the evaluation of the certainty of evidence in Network Meta-Analyses (NMAs). Utilizing his expertise in R statistical software, Dr. Kamso designed rules, algorithms, and Shiny dashboards to streamline these processes. He is an active member of an international collaborative research group, where he implements innovative strategies to improve the evidence base for various interventions in rheumatoid arthritis (RA). Currently, he plans to integrate his formal education and work experience into the design and analysis of clinical trials. By contributing to the generation of new information via clinical trials, he aims to further refine and optimize methodologies in the critical areas of RA and cardiovascular health research, among others.
Mohammed Mujaab Kamso
CANSTAT Fellow
Mentors: George Wells and Glen Hazelwood
Research Interests: Research designs, evidence synthesis; comparative effectiveness research; Adaptive clinical trial designs; Bayesian Analysis; Network Meta-analysis; Evaluation of the Certainty of Evidence using the GRADE framework
Bio: Dr. Mohammed Mujaab Kamso is a Biostatistician trainee at the Cardiovascular Research Methods Centre (CRMC) at the University of Ottawa. He recently earned his Ph.D. and has extensive experience in evidence synthesis. His research focused on developing novel semi-automated methodologies for trial identification and the evaluation of the certainty of evidence in Network Meta-Analyses (NMAs). Utilizing his expertise in R statistical software, Dr. Kamso designed rules, algorithms, and Shiny dashboards to streamline these processes. He is an active member of an international collaborative research group, where he implements innovative strategies to improve the evidence base for various interventions in rheumatoid arthritis (RA). Currently, he plans to integrate his formal education and work experience into the design and analysis of clinical trials. By contributing to the generation of new information via clinical trials, he aims to further refine and optimize methodologies in the critical areas of RA and cardiovascular health research, among others.
Graeme Kempf
CANSTAT Fellow
Mentors: Joel Singer and Jim Russell
Research Interests: Multi-state models, pharmacoepidemiology studies, design and analysis of randomized trials
Bio: I completed my MSc in Statistics at the University of British Columbia in 2024. My thesis was titled “The impact of disease-modifying drugs for multiple sclerosis on hospitalizations and mortality in British Columbia: a retrospective study using an illness-death multi-state model”. I previously graduated from Wilfrid Laurier University with two degrees, a BSc in Data Science and a Bachelor of Business Administration.
Graeme Kempf
CANSTAT Fellow
Mentors: Joel Singer and Jim Russell
Research Interests: Multi-state models, pharmacoepidemiology studies, design and analysis of randomized trials
Bio: I completed my MSc in Statistics at the University of British Columbia in 2024. My thesis was titled “The impact of disease-modifying drugs for multiple sclerosis on hospitalizations and mortality in British Columbia: a retrospective study using an illness-death multi-state model”. I previously graduated from Wilfrid Laurier University with two degrees, a BSc in Data Science and a Bachelor of Business Administration.
Yutong Lu
CANSTAT Fellow
Mentors: Kevin Thorpe and David Mazer
Research Interests: Clinical trial design and analysis, causal inference, predictive models in healthcare
Bio: Yutong Lu earned her MSc in Biostatistics with an emphasis in Artificial Intelligence and Data Science from the University of Toronto. During her Master’s program, she completed a practicum project titled “Knowledge fusion of large chemical language models for molecular property prediction” under the guidance of Dr. Pingzhao Hu. She also holds a BSc from the University of Toronto, where she pursued a Specialist in Statistical Science: Methods and Practice with a focus on Health and Disease. Moving forward, Yutong aims to further develop her theoretical knowledge and practical skills to contribute to clinical trials and other fields in healthcare.
Yutong Lu
CANSTAT Fellow
Mentors: Kevin Thorpe and David Mazer
Research Interests: Clinical trial design and analysis, causal inference, predictive models in healthcare
Bio: Yutong Lu earned her MSc in Biostatistics with an emphasis in Artificial Intelligence and Data Science from the University of Toronto. During her Master’s program, she completed a practicum project titled “Knowledge fusion of large chemical language models for molecular property prediction” under the guidance of Dr. Pingzhao Hu. She also holds a BSc from the University of Toronto, where she pursued a Specialist in Statistical Science: Methods and Practice with a focus on Health and Disease. Moving forward, Yutong aims to further develop her theoretical knowledge and practical skills to contribute to clinical trials and other fields in healthcare.
Lara Maleyeff
CANSTAT Fellow
Mentors: Shirin Golchi and Marie Hudson
Research Interests: Bayesian adaptive designs, clinical trials, precision medicine, treatment effect heterogeneity
Bio: Lara Maleyeff, PhD is a postdoctoral fellow in biostatistics at McGill University, where she specializes in precision medicine and clinical trial design. Her research focuses on utilizing Bayesian model averaging and adaptive enrichment designs to optimize treatment strategies for chronic conditions like rheumatoid arthritis. Lara completed her PhD at Harvard University, where her dissertation addressed treatment effect heterogeneity in cluster randomized trials.
Lara Maleyeff
CANSTAT Fellow
Mentors: Shirin Golchi and Marie Hudson
Research Interests: Bayesian adaptive designs, clinical trials, precision medicine, treatment effect heterogeneity
Bio: Lara Maleyeff, PhD is a postdoctoral fellow in biostatistics at McGill University, where she specializes in precision medicine and clinical trial design. Her research focuses on utilizing Bayesian model averaging and adaptive enrichment designs to optimize treatment strategies for chronic conditions like rheumatoid arthritis. Lara completed her PhD at Harvard University, where her dissertation addressed treatment effect heterogeneity in cluster randomized trials.
Myanca Rodrigues
CANSTAT Fellow
Mentors: Lawrence Mbuagbaw and Zainab (Zena) Samaan
Research Interests: Causal inference; Comparative effectiveness research; Mental health
Bio: Myanca Rodrigues holds a MSc in Epidemiology and Biostatistics from Western University and a PhD in Health Research Methodology (Biostatistics specialization) from McMaster University. Her dissertation examined outcome measurement in mental health research, including geriatric depression trials. Myanca is eager to develop her statistical skills in the design and analysis of clinical trials assessing interventions for psychiatric disorders.
Myanca Rodrigues
CANSTAT Fellow
Mentors: Lawrence Mbuagbaw and Zainab (Zena) Samaan
Research Interests: Causal inference; Comparative effectiveness research; Mental health
Bio: Myanca Rodrigues holds a MSc in Epidemiology and Biostatistics from Western University and a PhD in Health Research Methodology (Biostatistics specialization) from McMaster University. Her dissertation examined outcome measurement in mental health research, including geriatric depression trials. Myanca is eager to develop her statistical skills in the design and analysis of clinical trials assessing interventions for psychiatric disorders.
Shabnam Vatanpour
CANSTAT Fellow
Mentors: Tolu Sajobi and Michael Hill
Research Interests: Adaptive clinical trial designs; Statistical and machine-learning methods for advancing precision medicine and digital health; Risk prediction tools
Bio: Dr. Shabnam Vatanpour is a Biostatistician with the Calgary Stroke Program in the Department of Clinical Neurosciences at the University of Calgary. Her expertise lies in developing and applying statistical and machine learning techniques to extract meaningful insights from health data, facilitating evidence-based decision-making. With extensive experience collaborating with clinical investigators and multidisciplinary research teams, she is highly proficient in utilizing administrative health data in the areas of patient outcomes and healthcare services. Dr. Vatanpour collaborates closely with the Stroke Clinical Trials Group, providing support for various innovative clinical trials.
Shabnam Vatanpour
CANSTAT Fellow
Mentors: Tolu Sajobi and Michael Hill
Research Interests: Adaptive clinical trial designs; Statistical and machine-learning methods for advancing precision medicine and digital health; Risk prediction tools
Bio: Dr. Shabnam Vatanpour is a Biostatistician with the Calgary Stroke Program in the Department of Clinical Neurosciences at the University of Calgary. Her expertise lies in developing and applying statistical and machine learning techniques to extract meaningful insights from health data, facilitating evidence-based decision-making. With extensive experience collaborating with clinical investigators and multidisciplinary research teams, she is highly proficient in utilizing administrative health data in the areas of patient outcomes and healthcare services. Dr. Vatanpour collaborates closely with the Stroke Clinical Trials Group, providing support for various innovative clinical trials.