Dr. Rukhsana Kausar currently holds the position of Assistant Professor in the Department of Mathematics at the esteemed University of Punjab. Her association with the University of Punjab began in 2008 when she started as a Lecturer at PUCIT. Subsequently, she served as an Assistant Professor (Adhoc) in the Department of Data Science.
Dr. Kausar pursued her Master of Science degree in Scientific Computing, specializing in modeling with Partial Differential Equations, from TU Kaiserslautern in Germany. During her Master's thesis, she engaged in research within the field of Biomathematics, focusing on modeling the invasion and control of cancer using stochastic partial differential equations. Specifically, her work centered on a project involving the measurement of cortex thickness variation during brain cancer, a highly aggressive condition.
Following the completion of her Master's degree, Dr. Kausar joined the control system research group at TU Kaiserslautern to pursue her Ph.D. in control systems. Her Ph.D. studies were financially supported by the DAAD MIC (Mathematics in Commerce) program. Prior to her Master's and Ph.D., she obtained a Master's degree in Computational Mathematics from the University of Punjab, as well as a Bachelor's degree in Mathematics and Physics from Queen Mary College Lahore.
Throughout her Ph.D. research, Dr. Kausar conducted an in-depth exploration of fault detection and control design for various networks. Notably, she designed a comparative model for fault detection in water networks utilizing switched differential-algebraic equations. Employing higher-order schemes for hyperbolic Partial Differential Equations, she successfully developed a MATLAB model for a water network and optimized it using Python. A significant contribution of her Ph.D. thesis was the pioneering development of the theory of Switched Differential-Algebraic Equations, which allowed for the representation of impulses caused by instantaneous faults commonly observed in real-life networks, which frequently exhibit nonlinearity.
Dr. Kausar has also gained valuable experience as a Data Scientist through participation in different projects. For instance, she contributed to the design of a system aimed at optimizing time and transportation costs for same-day delivery of orders across various parts of Germany, utilizing order data. Additionally, she worked on a project focused on estimating the lifespan of sensors in automatic cars.
With a teaching experience spanning approximately ten years, Dr. Kausar has instructed numerous subjects at both the graduate and post-graduate levels. Her teaching expertise encompasses areas such as Modeling via Differential Equations, Linear Algebra, Calculus and Analytical Geometry, Probability and Statistics, Discrete Structures, Quantitative Techniques for Business, Advanced Neural Networks, System and Control Theory for Robotics, and Mathematics for Machine Learning.