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  • Operations Research

    Wikipedia on operations research:

    Operations research, or operational research in British usage, is a discipline that deals with the application of advanced analytical methods to help make better decisions.[1] It is often considered to be a sub-field of mathematics.[2] The terms management science and decision science are sometimes used as synonyms.[3]

    Employing techniques from other mathematical sciences, such as mathematical modeling, statistical analysis, and mathematical optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems. Because of its emphasis on human-technology interaction and because of its focus on practical applications, operations research has overlap with other disciplines, notably industrial engineering and operations management, and draws on psychology and organization science. Operations research is often concerned with determining the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost) of some real-world objective. Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries.[4]

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  • Artificial Intelligence

    Wikipedia on artificial intelligence:

    Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines."
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  • Neuroengineering

    Wikipedia on neuroengineering:

    This field of engineering draws on the fields of computational neuroscience, experimental neuroscience, clinical neurology, electrical engineering and signal processing of living neural tissue, and encompasses elements from robotics, cybernetics, computer engineering, neural tissue engineering, materials science, and nanotechnology.

    Prominent goals in the field include restoration and augmentation of human function via direct interactions between the nervous system and artificial devices.

    Much current research is focused on understanding the coding and processing of information in the sensory and motor systems, quantifying how this processing is altered in the pathological state, and how it can be manipulated through interactions with artificial devices including brain-computer interfaces and neuroprosthetics.

    My own BE and PhD theses and associated papers were in the field of neuroengineering. On an irregular basis I am still researching and publishing in the field in cooperation with my former PhD supervisors, Peter D. Neilson and Megan D. Neilson at the Neuroengineering Lab at UNSW.

    Doctor of Philosphy (PhD) thesis

    After my BE thesis I decided to complete a one-year MEngSc coursework degree in systems and control before I once again became tempted by a PhD research project supervised by Peter Neilson. The project dealt with three fundamental characteristics of human movement, namely speed-accuracy tradeoffs, velocity profiles, and physiological tremor.

    I implemented a a simulator based on the BUMP model of response planning. Performing a number of simulations studies of discrete step movements and constant velocity ramp movements, I found that these three phenomena can be explained as the direct consequence of a movement response planning system that acts as an intermittent optimal controller operating at discrete intervals of approximately 100 ms.

    While there are other models of response planning that account for one or other set of experimentally observed features of speed-accuracy tradeoffs, velocity profiles, and physiological tremor, none accounts for all three. The BUMP model succeeds in explaining these disparate movement phenomena within a single framework, strengthening this approach as the foundation for a unified theory of motor control and planning.

    Bachelor of Engineering (BE) thesis

    My first real research project was my final-year bachelor thesis at the University of New South Wales in Sydney, Australia. Dr. Peter Neilson, who was an associate professor at the School of Electrical Engineering and Telecommunications and lecturer of systems and control courses at the time, offered to supervise a study of decoupled control in human visual pursuit tracking tasks. The project sounded so interesting that I turned down another project that even offered a AUD $5000 scholarship, a choice I am extremely happy that I made.

    Together with other final-year students, we had 24 subjects come in to the neuroengineering lab to perform tracking tasks using a joystick to control a cursor on a computer screen. A statistical analysis of collected data showed that the central nervous system decouples the nonlinear, highly cross-coupled dynamics of the neuromusculoskeletal system. This result contradicts existing views on independent visuomotor channels, where these channels are thought to correspond to independent neuroanatomical pathways.

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  • Education

    Wikipedia on education:

    Education is the process of facilitating learning. Knowledge, skills, values, beliefs, and habits of a group of people are transferred to other people, through storytelling, discussion, teaching, training, or research. Education frequently takes place under the guidance of educators, but learners may also educate themselves in a process called autodidactic learning. Any experience that has a formative effect on the way one thinks, feels, or acts may be considered educational.

    Education is commonly and formally divided into stages such as preschool, primary school, secondary school and then college, university or apprenticeship. The methodology of teaching is called pedagogy.

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