Dr. Anna Lawniczak received her PhD in Mathematics from Southern Illinois University, USA. She has been a professor at Louisiana State University (Baton Rouge, LA, USA) and at the University of Toronto. Lawniczak joined the Department of Mathematics and Statistics at the University of Guelph in 1989 where she is now a full professor, an affiliate member of the Centre for Advancing Responsible and Ethical Artificial Intelligence (CARE-AI) and an affiliate member of One Health Institute.
Lawniczak has held several visiting positions, including at the Center for Nonlinear Studies of Los Alamos National Laboratory in the USA and at The Fields Institute for Research in Mathematical Sciences. Lawniczak has also been a program fellow at the Institute for Pure and Applied Mathematics (IPAM), University of California, Los Angeles, USA and a Principal Investigator in Mathematics at the Energenius Centre for Advanced Nanotechnology, University of Toronto an "Affiliate researcher– External" of the Waterloo Institute For Complexity & Innovation.
Lawniczak’s research is multidisciplinary in nature and can be described over both the methodology domain and the application domain. Her work requires abstraction and model development of either engineering or natural complex systems, software development, simulation, visualization and analysis of simulation data via a variety of statistical and machine learning techniques. Her most recent research is in cognitive agents able to learn from their dynamical changing environment and from other agents. This research entails development of models and extensive analysis of their simulation data via various statistical and machine learning techniques. In this line of research she received with her co-authors Theoretical Award, Best Paper, of Complex Adaptive Systems, November 04, 2014. Also, with the onset of COVID-19 pandemic she has worked on development of individually based simulation model of spread of COVID-19 in a virtual city with realistic population distribution and applied this model to study effectiveness of implementation of different non-pharmaceutical intervention strategies.
In the methodology domain Lawniczak’s research has been in cognitive agents, multi-agent simulation systems, cellular automata, lattice gas cellular automata, techniques of computational and artificial intelligence, and statistical and machine learning techniques. She is one of the pioneers of the field of lattice gas cellular automata modeling of reactive systems. Lawniczak has been applying the above methodologies to study dynamics and or performance of complex systems in many diverse areas including natural and engineered systems, such as cognitive agents modeling autonomous robots, data communication networks, highway traffic, spread of epidemics, pattern formation in chemically reacting systems, formation of nanostructures and homoepitaxial growth.