Research Program
Detalle BN6
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Research Program
0. Introduction
ITESO's PhD in Engineering Sciences seeks to form engineers who can develop industry-related research projects, in order to increase scientific and technological capacity, encourage economic development, create job opportunities, and promote social welfare and sustainability in the region.
The program sees engineering research as an effective tool for social transformation. The program serves as a platform where researchers can become sensitive to the social issues of their context, push the boundaries of knowledge and develop innovative theoretical and methodological perspectives that offer a high added value and a positive impact on society.
This PhD program started up in August of 2013. It is listed on the National Program of Quality Graduate Programs (PNPC, in its initials in Spanish) of the National Science and Technology Council (CONACYT, in its initials in Spanish, Mexican Government) as an industry-oriented graduate program, at the CONACYT level of Newly Created programs, under the operational option of covering generic requirements applicable to different companies.
The PhD in Engineering Sciences is a formative program that is based on the researcher apprentice model. It is taught within an advisory support system that promotes academic quality while meeting individuals' needs. It offers the possibility of undertaking multidisciplinary work with other ITESO graduate programs in a wide range of areas of knowledge.
ITESO research is organized institutionally in Formal Research Programs (FRPs), which are periodically reviewed and approved by the Academic Council. The institutional lines of research in engineering and exact sciences at ITESO in particular are based on the FRPs of the academic departments related to these fields. Currently, for example, the following lines of research have been defined in this area:
- Design of electronic devices, circuits and systems
- High-performance software
- Innovation and technology management
- Energy, food and the environment
- Engineering for the territorial assessment of urban risk, among others.
The PhD program currently offers three broad lines of research:
1. Design of Electronic Devices, Circuits and Systems with four fields of concentration:
- High-frequency CAD
- Telecommunications
- Integrated circuits
- Digital and embedded systems.
2. High-Performance Software with three with fields of concentration:
- Computer simulation
- Pattern recognition
- Big data.
3. Innovation and Technology Management:
- Information Systems
- Service Ecosystems and Platforms
- BPM and Digital Transformation
- Innovation with Technology.
These lines of research were chosen for the PhD program considering the infrastructure available at ITESO for graduate studies in engineering, in terms of existing graduate courses as well as professors with a PhD who are active in research.
The PhD Program in Engineering Sciences will open new official lines of research as more support infrastructure becomes available (primarily graduate-level courses, laboratories, and full-time professors who are active in research).
The two lines of research that are currently available in the program, along with their particular fields of concentration, are described below.
1. Design of Electronic Devices, Circuits and Systems
1.1. Overall Description
This line is part of the formal research program (FRP) of the Department of Electronics, Systems, and Informatics, and its aim is to solve problems by creating and developing electronic technology that makes innovative contributions to the generation and application of knowledge in the following areas:
- analog electronics
- digital electronics and embedded systems
- radiofrequency and microwave engineering
- computer-Aided Design (CAD)
- digital signal processing (DSP)
Examples of applications from this line of research include communication systems, vehicle technology, high-performance computers, and bio-electronic systems, among others.
The research products of this line consist of:
- design of digital, analog and hybrid electronic circuits and systems, both discrete and integrated, including simulation, characterization, layout, assessment, construction and testing
- design based on the electromagnetic and multi-physical simulation of high-speed structures
- development of algorithmic methodologies for the modeling, analysis and design optimization of electronic circuits and interconnection structures
- design, simulation and assessment of circuits, algorithms and architectures for digital communications
- design of algorithms for wired and wireless communication systems, including the estimation, modeling and simulation of communication channels
- development of formal methods for the modeling, analysis, design, simulation, assessment and implementation of discrete and hybrid controllers applied to embedded systems
- development and implementation of embedded systems through field programmable gate arrays (FPGA)
- development of digital signal processing techniques for telecommunication and embedded systems, including the development of formal methods for their modeling, analysis, simulation, optimization, implementation and validation.
1.2. Fields of Concentration
Literally thousands of devices that we use every day are based on electronic technology. These products reach almost every corner of the planet, and play key roles in areas as diverse as communications, transportation, computer science, instrumentation, health, and industry in general. The research and development of electronic technology has been the key to the economic success of many countries, and access to it (both to technology and the knowledge of how it works) is an important factor in the promotion of a society's development. Below is an overall description of the main research challenges and relevance of the four fields of concentration within the line of research on design of electronic devices, circuits and systems.
1.2.1. High-frequency CAD
The growing sophistication of electronic applications has generated an ongoing demand for faster, more robust, less energy-consuming, smaller, and lighter electronic systems.
In the field of high frequency, the exponential growth of the telecommunications and computer industries around the world has driven the development of electronic circuits with increasingly broader bandwidths. A great number of technological developments confirm this trend.
With the increasing operational frequency of electronic circuits (or the continuous decrease in the transition times of digital signals), many phenomena that occur on devices cannot be modeled accurately enough by circuit simulators, either with lumped or with distributed parameters, making classic models less and less reliable for predicting the behavior of manufactured components. This situation is compounded by the physical size of devices, for which interconnections and packaging are critical circuits. In these cases, it becomes necessary to resort to full-wave electromagnetic simulators, or even multiphysical simulators that capture electromagnetic, thermal, and mechanical behavior in conjunction. These simulators have proven to be highly accurate, although in most practical cases they take up a great amount of computational resources, mainly in terms of memory and simulation time. This second disadvantage of electromagnetic and multiphysical simulators, the excessive simulation time, has generated the need to come up with innovative techniques to use them efficiently, not only as validation instruments, but as design tools in numerical optimization algorithms.
The use of numerical optimization algorithms to design electronic circuits has been driven by two main factors. The first factor is technical in nature: the complexity of the models themselves makes it difficult to manipulate using traditional engineering practices. The second factor is economic: growing industrial competitiveness imposes highly demanding and mutually exclusive design specifications, combined with the need to shorten product development cycles, from conceptualization to market launch.
The line of research on design of electronic devices, circuits and systems cultivates the field of Computer-Aided Design (CAD) of high-frequency circuits by innovating algorithmic methods for optimized physical design based on electromagnetic and multiphysical simulation of high-speed structures, as well as by developing state-of-the-art algorithmic methodologies for the modeling, analysis and design optimization of electronic circuits and interconnect structures, at PCB (Printed Circuit Board), packaging, and integrated circuit levels.
1.2.2. Telecommunications
The use of communication systems pervades our society. From technologically obsolete systems such as analog radio and television, to cutting-edge municipal networks and satellite vehicle security and control systems. Every day we benefit from communications to improve our quality of life.
This success and widespread popularity of communications has generated one of their main problems: the radioelectrical spectrum is shared, and increasingly scarce. This scarcity has made it expensive, and most of it is controlled by powerful commercial entities that restrict its use, limiting the possibilities of seeking greater social benefits.
Some of the most interesting theoretical results of recent decades suggest that this problem is artificial: we do not know how to fully exploit the atmosphere as a communication channel. Technology offers the promise of creating communication systems that are available to all, free from commercial control, thus consolidating the initial promise of the internet: we can all publish our own creations, not just consume the creations of others.
Some examples of new technologies that share this objective are: the so-called cognitive radio, MIMO (multiple input, multiple output) systems, cooperative diversity, software-defined radio, and reconfigurable digital systems.
Moreover, recent progress in the performance of communication systems has been enabled by the application of digital signal processing (DSP). This is a field of electrical engineering and mathematics that implements digital signal operations and transformations. Thus, DSP constitutes the basis for the development and implementation of digital modules and algorithms for new standards and technologies in wired and wireless communication systems.
The line of research on design of electronic devices, circuits and systems cultivates the field of digital telecommunications, with an emphasis on MIMO systems, software-defined radio, and the estimation, modeling and simulation of communication channels, supported by the development of state-of-the-art DSP techniques, through both computer simulation and field programmable gate array (FPGA) hardware implementations.
1.2.3. Integrated Circuits
The design and development of integrated circuits (IC) refers to a specific technology in which electronic solutions can be implemented to solve different problems. The electronic implementation at the integrated circuit level constitutes the most advanced and cost-effective form of making physical realizations of electronic circuits and systems.
Integrated circuit design generally goes beyond solving a specific social problem, since a single integrated circuit tends to have a wide variety of applications. Some applications focus on people's security, for instance in the car industry, where integrated circuits are implemented in electronic devices that control air bags and anti-blocking brakes, headlight control, among others, or for instance in anti-theft security in homes, offices, cars, etc. Better integrated circuits allow for innovations in medical equipment (CAT scanners, X-rays, tests for diabetes, cholesterol and other blood components), as well as in information systems that monitor people's health in real time, diagnose diseases and provide treatment and cures for genetic diseases and anomalies. Some integrated circuits are used in electronic devices and systems that monitor air quality, food quality, etc.
In the field of bioelectronic systems, progress made in the manufacturing processes of semiconductor devices has made it possible to integrate MEMS (micro-electro-mechanical systems, also known as micro-machines) with integrated circuit devices, or to develop analog integrated circuits that serve as an interface with a hostile environment, which opens up the possibility of exploring the development of electronic systems for the detection and measurement of chemical or biological entities. This has been used, for example, to monitor food quality, develop on-chip laboratories, and other emerging applications that represent a niche of opportunity. Here the main problem is the uncertain behavior of electronic devices when they are immersed in a chemical or biological system, sometimes at extreme temperatures; in this sense, multiphysical studies of such devices become essential.
On the other hand, the design of analog integrated circuits generally takes up a great deal of designers' time, making the use of optimization algorithms and CAD methods necessary to speed up the process of designing such circuits. Thanks to the combination of these design tools, it is possible to develop electronic systems on robust high-performance integrated circuit technology for different applications.
The line of research on design of electronic devices, circuits and systems cultivates the field of analog, digital, and mixed-signal integrated circuit design, from computer simulation to synthesis and implementation on microchips and their experimental characterization, thus promoting the development of innovative architectures that operate at high and/or low frequencies, with the benefits of low energy consumption, high density and high signal to noise ratios.
1.2.4. Digital and Embedded Systems
The progress achieved by the digital electronics industry has made it possible to obtain very reliable, high-performance and low-cost microcontrollers and microprocessors. This means that digital processing units can be found in practically every aspect of our everyday lives, ranging from smartphones and tablets, to automotive applications and consumer electronics. This diversity of applications, along with the competition to be the first to market with a given product, demands complex specifications and methodologies in the design and verification of digital systems.
Currently, hardware description languages, programmable logical circuits, and digital synthesis tools are resources that enhance the development of digital systems, and in view of the current challenges of digital electronic design, they represent fertile ground for technological development and research. In particular, key challenges can be found in the design of digital systems in the following niches: high-speed serialization and deserialization circuits, high-volume fast-access memory and storage systems, high-performance computer platforms, high-resolution video for info-entertainment systems, processor networks and their interconnectivity, among others.
In addition, the development of embedded systems calls for reliable, low-cost, high-performance hardware, generally with a specific purpose, together with the development of algorithms for the hardware to carry out the purposes it was designed for. This combination of hardware/software integrated into the application is what gives rise to embedded systems.
An embedded system differs from a traditional digital processing system, such as a desktop computer, in that the former deals with time-continuous signals, is generally subject to real-time restrictions, must contain failure-tolerance mechanisms, and its safety and performance must be guaranteed. For example, the embedded system that controls the airbags in cars must decide in a question of milliseconds whether the airbags should be activated. The system must determine whether the car has undergone a collision and then activate the airbags in the precise moment to absorb the hit without asphyxiating the passenger. The system must also avoid false alarms, since reinstalling the airbag system is expensive. Solutions that are based on embedded systems achieve passenger security by using sophisticated embedded DSP sensors and algorithms. Moreover, to avoid false positives, many cars use redundant sensors which use a "voting" system in firmware to decide whether the system should be activated or not.
All the restrictions to which an embedded system is subject pose important challenges, in both research and technology development. Formal methods for modeling and analyzing embedded systems serve to introduce a certain mathematical rigor into their construction, together with the possibility of conducting computer simulations, which makes it possible to adjust the models and bring down the total creation costs of embedded systems.
Hybrid control techniques, for their part, allow designers to treat embedded systems as "plants to control," where linear and non-linear techniques can be implemented for controllability, observability, stability, failure tolerance and redundancy, either in continuous-state, discrete or hybrid spaces.
As in the case of telecommunication systems, DSP techniques have played a key role in the development and practical application of embedded systems. Modern DSP techniques together with efficient hardware implementations are leading to increasingly higher information processing capacities in real time, obtained through local or remote perception systems (sensors), with a high degree of flexibility to modify the operation of the DSP through software within the embedded system, giving rise to a wide variety of applications in multiple industrial, commercial and health sectors.
The line of research on design of electronic devices, circuits and systems cultivates the field of digital and embedded system design with an emphasis on formal methods for specification, analysis, design and implementation, using both rigid-architecture digital devices and microprocessors and microcontrollers, along with digital devices with configurable architecture, such as FPGAs. This field of research involves DSP techniques for the design and implementation of signal processing algorithms in digital and embedded systems, as well as in closed-loop control techniques applied to embedded systems.
1.3. Network of Disciplines-Problems-Beneficiaries
The line of research on design of electronic devices, circuits and systems is supported by a number of disciplines, which provide knowledge (theoretical and practical) that is essential to solving the problems that are addressed, which are shown in the figure below. It is important to point out that part of the innovation produced in this line of research comes from combining and reinterpreting these areas of basic knowledge.
These basic disciplines lay the foundation that supports the scientific work in the four fields of concentration within the line of research on design of electronic devices, circuits and systems. The products that are generated from this research take the form of pieces of knowledge and technology: systems, circuits, devices, methods, algorithms, programs, etc. (see figure below).
The results of this line of research, within the framework of the PhD program, are relevant for a considerable number of industries, including the software, computer, telecommunications, semiconductor, vehicle, food, agriculture, and biomedical equipment industries. Regional examples of such industries are: ATR, A2e, Bosch, Continental, CORMAT, Dell, Eneri, Flextronics (formerly Solectron), Hella, NXP (formerly Freescale), Keysight Technologies (formerly Agilent), Jabil, HP, Intel, Mixbaal, Oracle, Sanmina-SCI, Siemens, Soluciones Tecnológicas, Tata, and TRW, among others. A number of these industries are large transnational companies, while others are small Mexican businesses. All cater to global markets.
2. High-performance Software
2.1. Overall Description
We live in a society of global information and knowledge. The phrase "Knowledge is power" (Sir Francis Bacon) holds true now more than ever. Organizations must take steps to store, manage and exploit the information that is generated externally and internally; to transform the information into knowledge; and to exploit this knowledge in order to obtain competitive advantage (for example, in strategic decision-making) that will help them survive, excel, and transcend in their environment.
The line of research on high-performance software, of the PhD Program in Engineering Sciences at ITESO, focuses on the development of software systems to solve problems that require the appropriate use of hardware resources, more specifically the continuous and efficient (nearly optimal) use of processing units, as well as behavior characteristics of the software that can be classified as intelligent behavior.
High-performance software can have different applications according to the users' needs, some of which are listed below:
- support for training personnel to perform specific functions,
- support for learning and teaching processes at any educational level,
- support for authorities in charge of disaster prevention and civil protection,
- support for organizations' decision-making,
- support for the optimization of company and/or government resources,
- support for the automation and optimization of manufacturing and design processes.
This line of research belongs to the formal research program (FRP) of the Department of Electronics, Systems, and Informatics, and has as its primary aim the design and implementation of software-based systems that deliver appropriate results within a computationally acceptable time span and that can be considered real-time under the conditions and requirements of the model being developed, making efficient use of the available hardware.
2.1. Fields of Concentration
The quantity and quality of the information generated is impossible for any human being to process without technological tools, primarily computers and specialized software. For specialized software to be truly useful, it must be easy to learn and use, as well as flexible, robust and reliable. Moreover, new information systems must display characteristics and behaviors that make them ever more accessible to the user, who will be less and less expert in technology; this means that new information systems must also be autonomous, proactive, good team workers and loyal. In other words, they must display characteristics that qualify them as "smart." At the same time, it is essential to offer the user a better perception and interaction with computer systems, for instance, through more intuitive and realistic graphic interfaces that better represent the user's object of study and offer both deeper understanding and the possibility to predict events.
To achieve this, it is essential to take full advantage of the capabilities of computer devices through the creation of algorithms, models and programming paradigms. Below is a description of the main research challenges and relevance of the three fields of concentration within the line of research on high-performance software.
2.1.1. Computer Simulation
Computer simulation emerged as a scientific tool for applications in meteorology and nuclear physics during the period following the Second World War, and since then it has become an essential element in numerous fields of knowledge. The list of scientific disciplines that make extensive use of computer simulation has grown to include astrophysics, particle physics, material sciences, engineering, fluid dynamics, Earth sciences, evolutional biology, economics, decision theory, medicine, sociology, epidemiology, among others. In fact, there are some disciplines such as chaos theory and complex theory whose very existence has gone hand in hand with the mathematical computer models that they study.
It is complicated to come up with an adequate definition of computer simulation since it can be seen from many points of view: any one definition is necessarily subjective and limited. In a specific sense, it can be described as a computer program that executes an algorithm with different methods that explore the approximate behavior of a certain mathematical model. In a more general sense, it is a methodology for studying systems through the computational implementation of their model and obtaining their output data.
The line of research on high-performance software cultivates the field of computer simulation by promoting the development of innovative techniques, methodologies and mathematical modeling applications in simulations through digital computers. The issues addressed by this area mostly include the simulation of natural and/or social occurrences: car flow in a city, crowd behavior in massive concentration venues such as concerts or demonstrations, behavioral studies, and the forecasting of natural disasters such as fires, earthquakes or storms.
2.1.2. Pattern Recognition
Pattern recognition deals with processes in engineering, computer science and mathematics that relate to physical and/or abstract objects, for the purpose of extracting information that will help to determine the properties of these objects as well as their interrelationships. In a wider sense, pattern recognition offers a means for interpreting the world.
There are four approaches to pattern recognition:
- Statistical: This is based on probability and statistics theory, assuming that there is a group of numerical measurements with known probability distributions from which the recognition is achieved.
- Syntactic: This is based on finding the structural relationships between objects of study, using formal language theory. The objective is to build a grammar that describes the structure of the universe of objects.
- Neuronal: This is based on the design of models that are inspired by biological neuronal networks, which are interconnected and stimulated by each other to give a certain response when certain input values are presented.
- Logical-combinational: This is based on the idea that problem modeling must be as close to its reality as possible, without making baseless assumptions. Thus, the characteristics that describe the objects of study must be carefully described.
The processes of automatic recognition, description and classification (groups of patterns within classes) have become essential tools to solve a wide array of problems in engineering and in other scientific disciplines including biology, psychology, medicine, marketing, computer vision, artificial intelligence, and remote perception, among others. In practically every area of science where data are studied but there are no mathematical and statistical models available, pattern recognition can be used to support human perception for analysis and decision-making purposes.
The line of research on high-performance software cultivates the field of pattern recognition with an emphasis on the development of methodologies and technologies that generate accurate and efficient processes for learning and detection of objects and patterns, for the purpose of implementing them partially or completely through computer languages. Some of the applications of this field of knowledge are the identification of elements and their characteristics in fixed images, videos or tables of values, for the purpose of studying their dynamics and follow up; quality assurance in manufacturing or defect detection processes, recognition formats for the internet of things, or preventing and solving crime, among other applications.
2.1.3. Big Data
In general terms we can define big data as the trend in technological progress that has opened the gate to a new approach to understanding and decision-making, which is used to process and describe massive amounts of data (structured, non-structured and semi-structured) that would be too time-consuming and costly to enter into a relational database for analysis. Thus, the concept of big data applies to any information that cannot be processed or analyzed using traditional computer processes or tools.
Aside from the large volume of information, there is a wide variety of data that can be represented in different ways all over the world, for instance, in mobile devices, audio, video, GPS systems, countless digital sensors in industrial equipment, cars, electricity meters, vanes, anemometers, etc., which can measure and communicate the position, movement, vibration, temperature, humidity, and even the chemical alterations of the air, in such a way that the applications that analyze these data require a fast enough response time to obtain the right information at the right time. These are the main characteristics of the issues associated with big data.
The line of research on high-performance software cultivates the field of big data to develop knowledge about the processes of representation, manipulation, analysis and interpretation of large amounts of data in a non-restricted format and in different contexts. Examples of applications include: a) for companies, the facilitation and/or automation of business processes (for example, the identification of the best candidate for a job opening) or the identification of behavioral patterns in their customers to offer better service; b) in e-commerce environments, systems that offer user assistance for the optimization of time, cost and security during their transactions; c) in scientific settings, the best possible processing of the information needed to conduct experiments and technological developments; d) in entertainment settings, the manipulation (understanding and transformation) of multimedia content, etc.
2.2. Network of Disciplines-Problems-Beneficiaries
The line of research on high-performance software is supported by a wide variety of disciplines that provide the knowledge needed to analyze and solve the proposed issues. In addition, they lay the foundations for generating new knowledge, which is essential in a doctoral project. In the figure below, the upper section shows the set of disciplines that support the work of this line of research.
These basic disciplines produce research results in more concrete areas, which form a second level containing the four main branches of computer science, which are: computer programming, computer graphics, data mining and artificial intelligence.
These areas feed their results directly into the three areas of concentration addressed by this line of research, which were described above. These areas focus specifically on the applications where they can be developed, for instance, catastrophe forecasting, urban traffic simulation, crowd organization, and decision-making, among others.
The results of the research conducted in this line of high-performance software, which the doctoral program intends to develop, are relevant for government institutions, the videogame development industry, educational institutions, service companies, design and manufacturing companies, as well as for private security companies, among others; these make up the fifth level of the figure below. Regional examples of this type of industry include: Oracle, Hewlett-Packard, IBM, Intel, Continental, Flextronix, NXP (formerly Freescale), Jabil, Siemens, and Tata, among others.
3. Innovation and technology management (InnTM)
Today's changing world requires companies to continuously update their processes, and technology is a key engine for innovation and sustainable business growth.
Innovation and technology management is a relevant setting for the development of models, practices and tools that can have a positive impact on the performance of companies and organizations.
This line of research focuses on transforming organizations through the incorporation of technology and new models designed to create value and compete. Whether through digital transformation, the intensive use of information systems, or the creation of innovation-promoting platforms, we look for proposals that enable organizations of all sizes to access resources that can help make them more sustainable and competitive.
We aim for economic development and social well-being grounded in competitiveness models that connect social actors of all sizes, through the sharing of resources supported by information technologies.
Fields of concentration:
3.1 Information Systems
This program stimulates applied research on information systems within organizations, which means the improvement of a company's services, processes and information systems.
This line of research is designed to prepare PhD students for careers in industry, teaching and research, involving the design, analysis, implementation and operation of information systems that process operations related to business, government and social responsibility. In this sense, we prioritize technological integration based on information systems that support informed decision-making by organization leaders, thereby helping them to visualize competitive advantages within a globalized world economy.
3.2 Service Ecosystems and Platforms
Services have taken on greater importance as they become the quintessential means of interaction and the creation of joint value. Services can be categorized as service systems or what has recently become known as ecosystems.
In ecosystems, actors (such as people, companies, organizations and institutions) interact with the common goal of generating collective well-being through the joint creation of value. In ecosystems, the competitiveness models are based more on networks than on productive chains.
Digital platforms have become an ideal medium for the support and development of ecosystems. New business and competitiveness models are created based on the application of technology.
The focus of this field of concentration is to develop theory, models and proposals that promote the development of ecosystems supported by digital technologies. The problems it addresses relate to the transformation of business practices and models using digital platforms in industries, institutions and society.
We also look for ways that digital platforms can facilitate fairer competitiveness models, whereby small companies, as well as social organizations and collectives, can have access to resources that allow them to achieve sustainability.
3.3 BPM and Digital Transformation
The growing need for productivity in organizations that operate in changing and highly competitive environments at a global level, in addition to the growing supply of digital tools such as BPMS, BRE, RPA, and BPA, motivate organizations to undertake digital transformation strategies in their business processes.
These organizational optimization strategies, achieved through digital transformation – a fundamental aspect of business research and practice – require management that is based on Business Processes, for the purpose of identifying, modeling, analyzing, designing, automating and continually improving processes that generate value for organizations.
Hence the importance of this line of research that focuses on the study, innovation and development of new models, methods, techniques, technologies and procedures for the optimization of business processes that support organizations in developing their competitiveness in a sustainable way.
The line of research in Business Process Management (BPM) and Digital Transformation cultivates the field of modern business management, focusing on processes, Business Ecosystems, Digital Transformation, Process Automation, and Process Intelligence, contributing to this field of knowledge by innovating management models and methods that use digital technologies, based on simulations and case studies.
3.4 Innovation with Technology
Innovation continues to be one of the most commonly-used elements for transforming the reality of companies and organizations to make them more competitive. However, innovation is still beyond the reach of people and organizations with limited resources.
Technology makes existing resources for product and service innovation more accessible. In addition, business models and industry configurations are undergoing radical transformations by incorporating technology, thereby acquiring the ability to turn existing products and services into digital versions, which offer distinct advantages over tangible products.
This field of research looks for models, methods and tools that can transform the innovation process in companies and organizations, especially small and medium-sized companies. It seeks to generate new models for networked innovation and resource optimization.
Our field of action includes companies and organizations that want to become more sustainable and/or competitive through the implementation of more accessible technology-supported innovation models.