new faculty

Dr. Gopolang Mohlabeng

Asst. Prof., Dept. of Physics

Phenomenology of New Physics Beyond the Standard Model: Dr. Mohlabeng’s research program encompasses the model building and experimental verification of new particles that lie beyond the standard model of particle physics. The standard model explains all the matter and fundamental forces (except gravity) that we can see and touch and feel in the Universe. However, there are some fundamental puzzles it cannot explain, like why is there more matter than anti-matter in the Universe, what are dark matter and dark energy made of, among others. Dr. Mohlabeng builds models of new particles and compares them with data from current experiments on Earth as well as astrophysical and cosmological probes. His research is mainly focused on discovering the underlying nature of dark matter.

Read more: Dr. Mohlabeng's profile on the Department of Physics website.

Dr. Samira Siahrostami

Asst. Prof., Dept. of Chemistry

Digital Chemistry for Catalyst Design: Dr. Siahrostami’s research program leverages advanced computational methodologies to engineer the next generation of materials tailored for catalysis in clean energy conversion and storage applications (e.g. batteries, fuel cells and electrolyzers). Her work revolves around modeling reactions occurring at solid surfaces, offering a profound understanding of the kinetics and thermodynamics of surface reactions. Her approach provides insight into the intricate details of how reactions unfold on the surfaces of catalysts which not only enhances our comprehension of the fundamental processes governing catalysis but also provides invaluable insights for designing materials that exhibit superior performance in clean energy applications. 

Read more: Dr. Siahrostami's profile on the Department of Chemistry website.

Dr. Lin Zhang

Asst. Prof., Dept. of Statistics and Actuarial Science

Statistical Genetics and Computational Biology: Dr. Zhang’s research program connects statistical theory and machine learning (ML) methods to solve real-life problems, particularly in the fields of biomedicine and public health. With the ever-growing availability of large-scale omics and health outcome data, efficient and interpretable computational methods are in great demand and are vital to unveil biological processes and disease pathogenesis. Equipped with rich research experiences in statistical genetics and computational biology, Dr. Zhang is well-positioned to develop her unique line of integrative research that finds a common ground between the traditional statistical methods and state-of-the-art ML algorithms for the analyses of complex, high-dimensional, large-scale biomedical data. 

Read more: Dr. Zhang's profile on the Department of Statistics and Actuarial Science website.

Dr. Alexandra Coates

Asst. Prof., Dept. of Biomedical Physiology and Kinesiology

Exercise Physiology and Performance: Dr. Coates' research program explores adaptive and maladaptive physiological responses to exercise stress. Her research aims to determine the optimal exercise prescription for peak health and athletic performance, while avoiding conditions including overtraining, injuries, and low energy availability. By performing intense exercise training interventions, Dr. Coates is able to characterize the physiological responses to optimal or excessive exercise stress, and develop monitoring techniques to prevent maladaptive training responses. 

Read more: Dr. Coates' lab page.

Dr. Dheva Setiaputra

Asst. Prof., Dept. of Molecular Biology and Biochemistry

Cancer DNA repair mechanisms: Dr. Setiaputra’s research program explores how cancer cells repair DNA damage induced by anticancer drugs. Cancer cells are often defective in DNA repair, enabling them to accumulate oncogenic mutations that drive disease progression. This defect is leveraged by genotoxic cancer therapy that purposely induces DNA damage that kills cancerous cells and sparing healthy ones. The Setiaputra lab is investigating fundamental DNA repair mechanisms through an interdisciplinary approach integrating biochemistry, cell biology, and computational biology with the ultimate goal of developing new therapeutic approaches targeting specific cancer repair defects.

Read more: Dr. Setiaputra's profile on the Department of Molecular Biology and Biochemistry website.

Dr. Reza Karamad

Asst. Prof., Dept. of Chemistry

Computational Materials Science: Dr. Karamad's research focuses on the synergy between computational materials science and machine learning. At the forefront of recent advancements in quantum-mechanical methods, including density functional theory (DFT) and high-throughput calculations, his work aims to deepen our understanding of materials properties and enable predictive capabilities. The research extends to the application of machine learning, providing insights into the vast phase space of materials and leading to breakthroughs in materials discovery. His primary emphasis is on leveraging these approaches for the development of advanced energy materials pertinent to clean energy technologies, such as hydrogen storage and catalysis.

Read more: Dr. Karamad's profile on the Department of Chemistry website.

Dr. Dustin King

Asst. Prof., Dept. of Molecular Biology and Biochemistry

Microbial metabolite sensing: Dr. King’s research program explores how bacteria sense and respond to metabolites, with the goal of uncovering fundamental insights into how bacteria communicate. To decipher these chemical messages, the King laboratory employs a unique interdisciplinary approach that involves first developing innovative methods to discover protein-metabolite interactions on a proteome-wide scale, and then conducting detailed biochemical experiments to elucidate the molecular basis of sensing. Understanding this communication will contribute to the development of next-generation antibiotics and enable us to harness bacterial metabolism to produce value-added products for green industry.  

Read more:  Dr. King's profile on the Department of Molecular Biology and Biochemistry website.

Dr. Jessica Stockdale

Asst. Prof., Dept. of Mathematics

Infectious disease modelling and genomic epidemiology: Dr. Stockdale’s research program explores mathematical modelling and statistical analysis of infectious disease outbreaks, with the goal of understanding disease transmission and its population impacts. Her research aims to inform public health strategies for infectious disease prevention and control. Using modelling and Bayesian statistics, Dr. Stockdale is interested in how we can use pathogen genomic data to make predictions about the dynamics of pathogen-host interactions.

Read more:  Dr. Stockdale's profile on the Department of Mathematics website.

Dr. Owen Ward

Asst. Prof., Dept. of Statistics and Actuarial Science

Statistical and machine learning models for network data: Dr. Ward’s research program explores complex structures in diverse network data, from online social networks to interacting animals. The generation of such data is a result of complex latent processes, and Dr. Ward develops statistical models to capture these dynamics, along with Bayesian inference procedures and machine learning tools to infer these models. These innovative techniques can be used to identify and understand social dynamics, such as social hierarchy and community structure across multiple application disciplines, including animal behavior and sociology.

Read more:  Dr. Ward's profile on the Department of Statistics and Actuarial Science website.

Dr. Chris Napier

Asst. Prof., Dept. of Biomedical Physiology and Kinesiology

Performance and injury prevention in running: Dr. Napier’s research program explores the use of laboratory- and field-based biomechanical measures to quantify aspects of running, with the goal of improving performance and reducing the risk of injury. Running is one of the most popular and accessible activities worldwide, yet half of runners are injured every year. Dr. Napier’s research employs a causal framework approach combining biomechanics and training load factors to predict future performance and to prevent injuries. His novel approach builds on his background as a sport physiotherapist and biomechanist, and attempts to quantify risk using a dynamic systems model.

Read more:  Dr. Napier's profile on the Department website.

Dr. Ben Ashby

Assoc. Prof., Dept. of Mathematics

Mathematical ecology, epidemiology and evolution: Dr. Ashby’s research program explores the ecological and evolutionary dynamics of hosts and pathogens, with the goal of understanding how traits such as resistance and virulence evolve. Host-pathogen relationships are found throughout the natural world and are a key driver of many biological phenomena, including spatiotemporal patterns of genetic and phenotypic diversity. He uses a variety of techniques to model host-pathogen systems, such as population genetics, quantitative genetics, and adaptive dynamics. His research group seeks to understand how pathogens evolve and co-evolve with their hosts, from sexually transmitted infections and mating dynamics to microbiome evolution.

Read more:  Dr. Ashby's profile on the Department of Mathematics website.

Dr. Randy McIntosh

Prof., Dept. of Biomedical Physiology and Kinesiology

Computational & cognitive neuroscience: Dr. McIntosh’s research program involves computational modeling and neuroimaging to explore changes in cognition across the lifespan and changes in the face of brain damage or disease. The program builds on an international collaboration that developed TheVirtualBrain, and integrates research efforts between labs to accelerate research and translation. The goal of this work is to incorporate the modeling platform into the standard workflow for clinical decision support, and develop a cloud-based system where brain models can be created by anyone for research, clinical use or education.

Read more:  Dr. McIntosh's profile on the Department of Biomedical Physiology and Kinesiology website.

Dr. Katrina Honigs

Asst. Prof., Dept. of Mathematics

Algebraic and arithmetic geometry: Dr. Honigs’ research program explores solution sets of systems of polynomial equations, called varieties, with the goal of classifying them and answering questions like whether they contain points whose coordinates are integers. Dr. Honigs uses an object called the derived category of coherent sheaves to compare and gain insight into arithmetic questions about varieties. She is particularly interested in varieties of Kodaira dimension 0, which include elliptic curves.

Read more:  Dr. Honigs' profile on the Department of Mathematics website.

Dr. Ailene MacPherson

Asst. Prof., Dept. of Mathematics

Theoretical evolutionary epidemiology: Dr. MacPherson’s research program examines the impact of infectious diseases on biological diversity using mathematical and statistical approaches. Her research program is characterized by two complementary aims. First, using theoretical population genetics, Dr. MacPherson explores how host-pathogen coevolution contributes to the astounding biological diversity of life on earth. Second, her research group develops phylodynamic (phylogenetics + epidemiological dynamics) methods to help us understand disease spread and therefore how to design effective conservation measures to rescue species at risk of extinction from infectious disease.

Read more:  Dr. MacPherson's profile on the Department of Mathematics website.

Dr. Nadish de Silva

Asst. Prof., Dept. of Mathematics

Quantum algorithms: Dr. de Silva's research program explores foundational questions of quantum computation using a mathematical methodology, with the goal of understanding precisely how, and for which problems, quantum computers outperform conventional computers. He is helping to develop an exciting emerging hypothesis that contextuality and nonlocality (notions of quantum foundations) are key resources for driving computational advantage. This involves applying novel logical techniques to questions of quantum information theory. The impact of deeper fundamental understanding of quantum computers will be to hasten their arrival and maximize the class of problems to which they could be fruitfully applied.

Read more:  Dr. de Silva's profile on the Department of Mathematics website.

Dr. Sergio Sepúlveda

Assoc. Prof., Dept. of Earth Sciences

Rock slope failure and catastrophic landslides: Dr. Sepúlveda’s research program explores the failure mechanisms, conditioning and triggering factors of large landslides in rock slopes, with the goal of identifying those geological, geotechnical and geophysical controls on catastrophic landslides in natural locations and resource industry sites. The results can be applied in landslide hazard assessment for improved design of mitigation and disaster risk reduction strategies. His team uses a combination of engineering geological, geotechnical and geomorphological field and laboratory methods as well as remote sensing and modelling tools. The research incorporates the impacts of climate change and earthquakes in mountain regions.  

Read more:  Dr. Sepúlveda's profile on the Department of Earth Sciences website.

Dr. Tanya Brown

Asst. Prof., Dept. of Biological Sciences

Read more: Dr. Brown's profile on the Department of Biological Sciences website.

Dr. Darren Grant

Prof., Dept. of Physics

Read more: Dr. Grant's profile on the Department of Physics website.

Dr. Daniel Higginbottom

Asst. Prof., Dept. of Physics

Read more:  Dr. Higginbottom's profile on the Department of Physics website.