Statement of Teaching Philosophy
My desire to solve the practical problems of medical systems made me tend naturally towards mathematical medicine and to be a teacher of the subject. My philosophy, as a science teacher, has always been to place great importance on student's fundamental understanding and concepts behind the subject. It also aims to explore the methods or tools in details including how and when these concepts may be applied to different fields of applied science, including several branches of sciences and engineering. In helping the students to achieve these goals, I employ a variety of techniques to accommodate the different backgrounds, learning styles, and I include a significant number of examples in my courses which make the course enjoyable even for the students who are usually averse to applied mathematics and bioengineering. Bringing out the geometric intuition appropriately behind the results under discussion enables students to understand the subject easily. Overall in all topics of mathematical medicine, a slightly informal style, with plenty of diagrams and real world examples, conveys best those aspects of the material that are hardest to get from standard textbooks. Different students have different styles of learning, and thus it is best to give varied perspectives such as, geometrical, analytical, and numerical. Developing the ability to think critically and to formulate logical arguments are among the important goals of learning mathematical medicine. Making one's own mistakes and discoveries is integral to developing these skills, and for this reason, I believe that students must take an active role in their education in order to achieve this level of learning. As it is my job to facilitate student growth, I devote my time and energy to help students take charge of the learning process so that they can develop into an independent thinkers who can conceptualise and utilise mathematics in board areas of sciences and technologies. My five years teaching experience at the Krishnath College (University of Kalyanni, India) has taught me that hard working of both teachers and students towards these goals only makes them realised intensely. However, during my career I have noticed that the majority of my student's course-related ambitions differ from my own at the beginning of the semester; most of the students want to arrive at the final answer, while I want to emphasise the thought process required to arrive that answer. Towards a common goal of mine and my student, I try to accomplish few tasks in the classroom. Firstly, I convince my students that only by focusing on how they approach, frame and solve a problem can they become independent thinkers and identify themselves with a larger scientific community in the future. Secondly, I make my students aware that I have been appointed to support them and match their effort in the course to learn mathematical medicine properly. Finally, I strongly encourage them to ask questions, both vocally and by example, during any stage of my teaching in the class sessions (and take more time outside the routine class if it is needed), because I believe that a successful lecture is a dialogue between student and teacher; and I also believe that one of the most important skills of a teacher is to gain the ability to answer student's questions very well. I repeatedly inform my students, "If you have a question with something, then you are not the only one." During the time of explaining difficult material, I keep my eyes to the signs of the face of my students, if I feel that they are having trouble understanding me, I pause frequently to ask me for questions. I always try to treat their questions as a natural part of my lecture, so that students gain confidence and join the dialogue soon. My students highly praise this particular aspect of my teaching method in their feed-back evaluations to the department. Another integral part of the good mathematical modelling pedagogy is group work. Most people learn better and are more motivated when they can share their knowledge and questions with their peers as well as their teacher. The numerical methods with practical exercises encourage the students to work in groups; this is how I teach the basics of numerical methods and their computations. Kalyanni's mathematics, physics and physiology departments (where I taught over 5 years) also encouraged student group work.
In summary, my ultimate goal as a teacher in mathematical medicine is to introduce students to the excitement of working on new mathematical ideas that resolve many critical crises in Health Science. I am looking forward to improving my skills further and to sharing my knowledge and enthusiasm for mathematical medicine in the years to come. I will continue to teach with this goal in mind throughout my career.
Timothy Scott -2014-2017.
Teaching Assignment in Undergraduate Section B.Sc. (Mathematics & Physics Hons):
Differential Equations; Probability and Statistics-I; Algebra; Linear Programming Problem and Game Theory; Real Analysis; Particle, Rigid and Hydro Dynamics; Numerical Analysis-I; Calculus and its Applications. Computer Languages: Basic.
Teaching Assignment in M.Sc. (Physiology)
Mathematical and Computer Modelling of Physiology.
Research Assignment in Master Project
(1) Co-guided few undergraduate projects for Master of Applied Mathematics Course of North University of China, Shanxi, P. R. China with Professor Jin Zhen.
- Biomedical Engineering and Clinical Neuroscience: Effect of Mechanical Ventilation on Human Physiology, Brain, Neural, Cardiovascular and Respiratory system. Design, develop and apply pathophysiological models of human organ systems, with the aim of addressing issues of impact in critical illness and medical crisis scenarios.
Project Title: Development, validation and application of pulmonary disease models using robustness analysis and ensemble forecasting.
Lung diseases affecting the critically ill (acute respiratory distress syndrome (ARDS), pneumonia and ventilator-associated lung injury (VALI)) are acute, severe injuries affecting most or all of both lungs. Patients with these conditions experience defects in gas-exchange and tissue oxygenation and often require mechanical ventilation (life support) because of respiratory failure. While medical researchers and physiologists have been studying these disease for many years, very limited progress has been made in understanding the underlying causes and mechanisms (especially of ARDS and VALI). As a result of the explosive developments and demonstrated successes of molecular systems biology in the last decade, many researchers are now attempting to apply similar systems-based computational approaches to develop and analyse physiological simulation models at the organ level. However, the uncertainty that arises due to patient and disease heterogeneity, and the difficulty in rigorously validating simulation models which take this uncertainty into account, represent serious roadblocks to progress in applying systems approaches in a clinical setting. This project will tackle both of these problems by adopting a highly novel and interdisciplinary approach. Using approaches from the field of Control Engineering, we will develop population-based disease models which explicitly take account of uncertainty and variability both within a single patient and between diverse members of a patient population, and rigorously validate these models using advanced robustness analysis techniques. By adapting ensemble modelling techniques from the field of climate forecasting, we will develop reliable descriptors of disease severity and novel disease-specific therapeutic strategies that are applicable to populations of individual patients, rather than a single "typical" patient. By transferring state-of-the-art technologies from control engineering and climate science into critical-care medicine, this project will deliver a significant improvement in the understanding, diagnosis and treatment of ARDS, pneumonia and VALI, and a corresponding reduction in both their impact on patients and the associated cost to the National Health Service.
DAS, ANUP, HAQUE, MAINUL, CHIKHANI, MARC, COLE, OANA, WANG, WENFEI, HARDMAN, JONATHAN G and BATES, DECLAN G, 2017. Hemodynamic effects of lung recruitment maneuvers in acute respiratory distress syndrome BMC pulmonary medicine. 17(1), 34
ALI, NIJAMUDDIN, HAQUE, MAINUL, VENTURINO, EZIO and CHAKRAVARTY, SANTABRATA, 2017. Dynamics of a three species ratio-dependent food chain model with intra-specific competition within the top predator Computers in Biology and Medicine. 85, 63-74 CHIKHANI, M, DAS, A, HAQUE, MAINUL, WANG, W, BATES, DG and HARDMAN, JG, 2016. High PEEP in ARDS: quantitative evaluation between improved oxygenation and decreased oxygen delivery British Journal of Anaesthesia. 117(5), 650-658
ANUP DAS, OANA COLE, MARC CHIKHANI, WENFEI WANG, TAYYBA ALI, MAINUL HAQUE, DECLAN G BATES AND JONATHAN G HARDMAN, 2015. Evaluation of lung recruitment maneuvers in acute respiratory distress syndrome using computer simulation Critical Care. 19(8),
- Mathematical Modelling of System Biology: Dynamics of Gene Regulatory Networks and cellular signaling and its consequence of environmental hazards caused by chemical mixtures, soils, and waters. My models are based on sets of mathematical equations and experimental data that simulate key biological processes, and are used by pharmaceutical companies to accelerate their internal drug discovery and development programs.
- Mathematical/theoretical Ecology: Predator-prey, Food chain, Epidemiology, Eco-epidemiology, Chaos, Diffusion and Pattern Formation in Ecology and Epidemiology, control of diseases in agricultural and natural eco-systems.
Project Title: Development, validation and application of blast lungs.
The purpose of the current project is to assess the VQ configuration of the integrated model which has been developing from last couple of years to match the gas-exchange characteristics of blast lung (BL) victims and how it affects the cardiovascular variables to match the disturbed blood circulation of BL victims. We will test the integrated (multi-organ) model for it's robustness and credibility by generating a spectrum of disease states that represent BL and compare them with the animal data from the MOD and published literature. We will, also, design the protocols to test the BL simulations; we aim to have a robust, credible computational model of lifelike with considerable flexibility and measurable BL victims to work with in-silico studies. Finally, the current project aims to design protocols to test investigative and therapeutic manoeuvres in BL victims such as fluid resuscitation, fluid withholding, and ventilator strategies.