Cross Linking Research and Education and Entrepreneurship

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Transcription:

Cross Linking Research and Education and Entrepreneurship MATLAB ACADEMIC CONFERENCE 2016 Ken Dunstan Education Manager, Asia Pacific MathWorks @techcomputing 1

Innovation A pressing challenge Exceptional research but commercialization struggles Insufficient STEM education inadequate collaboration 75% businesses without innovation culture Disruptive technologies present opportunities Education, research & business communities must align 2

Technology & Innovation setting a direction Big Data Machine Learning Modelling & Simulation Robotics Biotechnology Sensors Nanotechnologies Energy technologies IOT These two new general purpose technologies offer enormous social and economic opportunities for countries which facilitate and embrace their widespread development and adoption. 3

Technology & Innovation setting a direction Lead author, Bob Williamson says: "Data analytics stands to be the next general purpose technology, and is surely a harbinger of the next technological revolution," "To me the really interesting thing is rather than say you have this privileged class of technology scientists and then you have all these other poor bunnies. But everyone is a technologist of sorts. "When you consider every student at school now-what is it they need to learn to given that we are moving into an era when data technology will be pervasive. "They don't need to necessarily build it but in the same way I don't need to know how to build a computer but I do need to understand how to exploit it and you are starting to see a lot of this. 4

Demand & opportunity Employer's say.. Our senior engineers with experience and integrated knowhow are retiring and taking with them our core competencies. The new engineers have no multidisciplinary, integrating, systems experience. Academia does not teach that! We are losing our competitive advantage! How can we capture that engineering expertise and enhance our engineering workforce to keep our competitive advantage? 5

Gaps Between What Academia Teaches and What Industry Needs Industry: Essential, Important, or Useful University: Part of the curriculum Linear Models 96.4% 95.6% Control-Oriented Models for System Design 98.2% 67.0% Simulation Models for System Verification or 94.5% 48.5% Product Development Nonlinear Models 90.9% 42.3% Finite State Machine Models 82.9% 33.0% Real-Time Models for Hardware-in-the-Loop Verification or Training 94.4% 25.8% Nov. 2009 Controls Curriculum Survey: An IEEE Control Systems Society Outreach Task Force Report www.ieeecss.org/publications/miscellaneous.html 6

Education is the key for new Industries New industries bring more variations & Complexity in development and production. Requires more capable employees in both the works and the development The worker needs to understand how to influence production plant that is reconfiguring itself. The developer must plan for flexibility in the production systems Modelling and simulation is an indispensable tool. Responsibility for quality and implementation lies with companies and universities 7

Innovating the Engineering Education Model Supply & Demand Supply side Research universities Engineering schools Teaching Research Technology transfer office Technology Engineers Demand side Dynamic changes Service innovation Partner collaboration Globalization Exponential technology Disruptive innovations creating new industries New startups 9

It s Math that Drives Things More math in your system bigger benefit from MATLAB & Simulink 10

Automotive Aeronautics Retail Off-highway vehicles Finance Industrial Automation Internet Oil & Gas Logistics Clean Energy Medical Devices Healthcare Management 11

MathWorks Data Analytics Scope Developing embedded systems which have increasing analytic content Smart Connected Systems Analytics that increasingly require both business and engineering data DATA Engineering, Scientific, and Field Business and Transactional Deploying applications that run on both traditional IT and embedded platforms Business Systems Data Analytics Enable Domain Experts to be Data Scientists 12

MATLAB Enabled Campus Everyone, Anytime, Anywhere Access Unified Computational Ecosystem MATLAB ON PCs Clusters Cloud MATLAB Mobile MATLAB Online Scalable Computing Infrastructure Resource Framework Curricula Materials and Projects Hands on learning with hardware & sensors Online auto grading of assignments Online self paced learning 13

Over 5000 universities use MATLAB 650 provide MATLAB-enabled campuses 14

Australia & New Zealand: 28 out of 48 universities are MATLAB Enabled Campuses 15

Michigan State Integrates MATLAB into Engineering Curricula to Foster Student Proficiency in Problem-Solving Using Computational Tools Challenge Help engineering students build confidence in their ability to apply computational tools and better prepare them for industry and postgraduate study Solution Integrate MATLAB and Simulink throughout the engineering curricula, enabling students to consistently build upon their previous experiences Results Students better prepared to meet industry demands Program outcomes and student skills improved Teaching accelerated in higher-level courses Link to user story Dr. Daina Briedis with a student in the lab. Our environment of choice for problem-solving at the undergraduate level is MATLAB. We selected MATLAB because it is suitable for a broad range of problems and because it is becoming the de facto standard in many university engineering programs, reflecting the increasing use of MATLAB in industry. Dr. Jon Sticklen Michigan State University 16

Supporting Research Programmes development Industry University research education 17

A Challenge for All of Us Universities need to revise curricula to attract and retain students, reflect research interests of faculty, and give students practical knowledge and skills Industry University development Recruitment Tools research education 18

A Challenge for All of Us development Companies need innovative techniques to solve their own real-world problems Industry Recruitment Universities have researchers in search of real-world problems to drive and anchor their research work University research Tools education 19

A Challenge for All of Us development Companies need innovative techniques to solve their own real-world problems Industry Recruitment Universities have researchers in search of real-world problems to drive and anchor their research work University research Tools education 20

Industry-University Research Collaborations Ricardo and Fraunhofer Institute Model-Based Design of a Piezoelectric-Actuated Hydraulic Pump University of Toronto and Space Flight Laboratory Design of Nanosatellite Control Systems FEV and RWTH Aachen New Model-Based Design Techniques for Automotive Software Development 21

A Challenge for All Universities need to revise curricula to attract and retain students, reflect research interests of faculty, and give students practical knowledge and skills Industry University industry Recruitment curricula Companies push the state-of-the-art in development methods, and need engineers who can contribute research curricula education 22

Innovation Transition Sources of Technology Universities Research institutes Corporate research Entrepreneurs Incumbent firms Focus on learning curve and incremental innovations Startups De-risk: Technology Markets Biz-models Independent new company Acquisition of Startups Incumbent Firms R&D 24

MathWorks Startup & Accelerator Program MathWorks supports more than 100 startup accelerators and incubators worldwide. Startups rely on MATLAB and Simulink to reduce technical risk do more with limited resources. focus on competitive differentiation and reach early-stage milestones. Australia & New Zealand 6 Accelerators & >15 Startups supported 25

Bridging Innovation from Academia to Industry How will your teaching, research or learning enable you to collaborate in innovative teams and companies? Are you providing yourself with the competency and tools to deliver innovative products and systems? 26

Accelerating the pace of discovery, innovation, development, and learning in engineering and science. 27