BrainMap

Mr. Radu-Emil Precup

Prof.dr.ing.

Professor - UNIVERSITATEA POLITEHNICA TIMIŞOARA

Other affiliations

Senior researcher (CS I) and head of the Data Science and Engineering Laboratory - ACADEMIA ROMANA FILIALA TIMISOARA (Romania)

Teaching staff

Radu-Emil Precup (M IEEE '03 - SM IEEE '07) was born in Lugoj, Romania, in 1963. He received the Dipl.Ing. (Hons.) degree in automation and computers from the "Traian Vuia" Polytechnic Institute of Timisoara, Timisoara, Romania, in 1987, the Diploma in mathematics from the West University of Timisoara, Timisoara, in 1993, and the Ph.D. degree in automatic systems from the "Politehnica" University of Timisoara, Timisoara, in 1996. From 1987 to 1991, he was with Infoservice S.A., Timisoara. He is currently with the Politehnica University of Timisoara, Romania, where he became a Professor in the Department of Automation and Applied Informatics, in 2000, and he is currently a Doctoral Supervisor of automation and systems engineering. From 2022, he is also a senior researcher (CS I) and the head of the Data Science and Engineering Laboratory of the Center for Fundamental and Advanced Technical Research, Romanian Academy – Timisoara Branch, Romania.

Web of Science ResearcherID: A-6993-2009

Curriculum Vitae (18/04/2024)

Expertise & keywords

Artificial Intelligence based Control System for Legged Robots used in Autonomous Navigation, Mapping and Surveillance of Unstructured Environments Call name: P 2 - SP 2.1 - Proiect experimental - demonstrativ
PN-III-P2-2.1-PED-2021-4587 2022 - 2024

Role in this project:

Coordinating institution: UNIVERSITATEA TRANSILVANIA BRASOV

Project partners: UNIVERSITATEA TRANSILVANIA BRASOV (RO); UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Affiliation:

Project website: https://rovislab.com/ai_legrob.html

Abstract:

Autonomous navigation in unstructured environments and rough terrain is a key challenge that must be overcome in order to successfully deploy robotic systems for applications such as autonomous surveillance of protected areas, assistance for the blind, accompany find-and-rescue personnel in their daily operations, or package deliveries in remote areas. In such cases, legged robots present significant advantages over traditional vehicles with wheels and tracks. However, in order for a legged robotic system to operate properly in such environments, it requires an Artificial Intelligence (AI) based controller able to sense in real-time the state of the environment (e.g. detecting objects, humans, obstacles, terrain shape and composition, etc.), as well as to compute safe trajectories and motion control inputs based on the output of the perception system.

Dynamics of hypercomplex-valued neural networks Call name: P 1 - SP 1.1 - Proiecte de cercetare Postdoctorală - PD-2021
PN-III-P1-1.1-PD-2021-0345 2022 - 2024

Role in this project:

Coordinating institution: UNIVERSITATEA POLITEHNICA TIMIŞOARA

Project partners: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Affiliation:

Project website: https://sites.google.com/view/dhvnn

Abstract:

Recurrent neural networks (RNNs) have many applications in classification, optimization, signal and image processing, pattern recognition, system identification, cryptography, and so on. These applications are highly dependent on the dynamical properties of the networks, making the analysis of the dynamical behavior an important part in the design of RNNs.

Also, neural networks (NNs) were extended to hypercomplex domains, yielding hypercomplex-valued NNs, which have caught the attention of researchers in the past years, due to their increasing number of applications.

Thus, the project aims at studying the stability and synchronization of quaternion, octonion, Clifford, and matrix-valued RNNs. Sufficient conditions given in terms of linear matrix inequalities for the stability and synchronization, using different control schemes, of quaternion-valued Hopfield and fractional-order (FO) NNs, of octonion-valued Hopfield and FO NNs, and of Clifford-valued Hopfield and FO NNs with neutral-type, leakage, time-varying, and distributed delays on time scales (TS) will be derived using techniques and methods extended from the real- and complex-valued domains. Finally, all the previously obtained results will be generalized to study the stability and synchronization of matrix-valued Hopfield and BAM NNs with delays on TS. Numerical simulations of various examples will illustrate the effectiveness of the obtained theoretical results and their easiness of use for practical applications.

Data-driven fuzzy control with experimental validation Call name: P 4 - Proiecte de Cercetare Exploratorie, 2020
PN-III-P4-ID-PCE-2020-0269 2021 - 2023

Role in this project: Project coordinator

Coordinating institution: UNIVERSITATEA POLITEHNICA TIMIŞOARA

Project partners: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website: http://www.aut.upt.ro/~rprecup/grant2021.html

Abstract:

Fuzzy controllers are an important part of the general class of nonlinear controllers as they are relatively easily understandable and also offer very good control system (CS) performance. An alternative to the classical model-based control is represented by data-driven control (DDC), a hot topic in academia and industry as well. The advantage of DDC is the use of only the input-output data of the process, which is useful if the mathematical model of the controlled process is complex or its identification is very difficult. That is the main reason of the high increased interest for nonlinear controllers whose parameters are determined using the input-output data of the controlled processes, especially in the area of industrial control engineering practitioners. This project proposes the development of new data-driven fuzzy controllers (DDFCs) for nonlinear processes with shape memory alloy (SMA) actuators in order to benefit from the advantages of both fuzzy control and DDC. SMA, as a relatively complex nonlinear process, is challenging and also advantageous by silent operation and acting by contractions like a human muscle, playing the role of actuator in CSs. The new CS structures with DDFCs will be tested and validated experimentally on several classes of processes that include SMA actuators and lab equipment of the research team. They will also be validated as industrial controllers with the support of team’s external partners from Romania, Canada, UK and Australia.

Nonlinear observers-based control structures applied to mechatronics systems Call name: P 1 - SP 1.1 - Proiecte de cercetare Postdoctorală
PN-III-P1-1.1-PD-2016-0331 2018 - 2022

Role in this project: Key expert

Coordinating institution: UNIVERSITATEA POLITEHNICA TIMIŞOARA

Project partners: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website: https://szedlak-stinean.wixsite.com/nobsmecs

Abstract:

Mechatronics systems are successfully used in many industrial and non-industrial applications because of their initial simple and robust structure. The degree of complexity of the control subsystem of a mechatronics application differs from one application to another and may include relatively simple and advanced control structures as well. The development of advanced control solutions is a relatively difficult problem which requires a detailed preliminary study of the process, particularly the parameters variability and of its structural properties. As a continuation of previous research in this project the approach oriented on the analysis, synthesis, modeling and development of modern control solutions, such as nonlinear observers is proposed.

The main objective of this proposal is to develop the necessary tools, modern control solutions and theoretical framework for later multi-purpose applications related to mechatronics systems.

The potential impact to the scientific field may be significant because through new concepts and employed approaches, a new way for the use of highly advanced control designs in mechatronics applications is open. The construction of nonlinear observers still provides an open research field because advances in this area often face many obstacles, such as, for example, the very restrictive conditions that have to be satisfied, uncertainty in the performance and robustness and/or poor estimation results. However, the control systems should benefit from the advantages of the continued analytical development and implementation of dynamic model-based nonlinear observers that promise to improve the performance of different types of mechatronics systems. In the project all mechatronics applications tackled are interdisciplinary and multidisciplinary themselves, with special focus on those applicable cost-effective training systems in the fields of robotics, automation and process control.

Improving the prediction of opinion dynamics in temporal social networks: Mathematical modeling and simulation framework Call name: P 1 - SP 1.1 - Proiecte de cercetare Postdoctorală
PN-III-P1-1.1-PD-2016-0193 2018 - 2019

Role in this project: Key expert

Coordinating institution: UNIVERSITATEA POLITEHNICA TIMIŞOARA

Project partners: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website: http://staff.cs.upt.ro/~alext/projects/impress/site

Abstract:

In a rapidly evolving world, with growing population and accelerated access to online media, the need to understand the structures and behavior of human society has become more important than ever. Having emerged as an interdisciplinary field in the 21st century, social networks analysis is on the quest to understand opinion formation and diffusion from a scientific point of view. The formation of social networks, namely the way connections are created and strengthened, is a very complex process, and there are many factors that interfere for the emergence and evolution of social ties. Notable research efforts try to explain the high complexity of such network structures, by proposing corresponding algorithmic models. Nevertheless, available models have many limitations as they typically assume opinion interaction mechanisms based on fixed thresholds, static topologies, or omnipresent opinion sources.

This project comes to improve our understanding of opinion diffusion in emergent social networks. Consequently, to build models that are aware of these phenomena, I propose fundamental topological analysis of empirical data - using network motifs, community detection algorithms and statistics - to understand the behavioral patterns and centralities which have an impact on spatial and temporal distribution of opinion. As opposed to most existing opinion interaction models, I propose a temporal opinion injection model which evolves over time according to basic human traits and underlying social topology. Also, by employing discrete event simulation on real-time gathered social network data, I propose the implementation of an online platform to offer improved prediction on poll outcomes for socially-relevant topics.

In the wake of big data analytics, this project sets out to push the boundaries of scientific understanding of opinion dynamics in social networks by analyzing how the underlying network topology influences communication patterns and polarization of opinion.

Learning techniques for improving control systems performance using model-free approaches Call name: Projects for Young Research Teams - RUTE -2014 call
PN-II-RU-TE-2014-4-0207 2015 - 2017

Role in this project: Key expert

Coordinating institution: UNIVERSITATEA POLITEHNICA TIMIŞOARA

Project partners: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website: http://mbradac.info/te2015.html

Abstract:

The main objective of this proposal is to develop the necessary tools, algorithms and theoretical framework in order to induce the learning-predictive behavior for control systems using model-free control approaches. The control loops at the lower hierarchical level will be first designed and tuned using model-free techniques such as Iterative Feedback Tuning, Virtual Reference Feedback Tuning, Model Free Adaptive Control. With the fixed designed control loops, the typical reference input-controlled output behavior specific to stable closed-loop control systems will be next improved using a model-free Iterative Learning Control approach to optimize the reference inputs in a trajectory tracking problem framework. Several reference input-controlled output behaviors are memorized as primitive tasks inside a library of primitives. The primitives are used in predicting the optimal behavior of the control system when a new complex task is to be executed. A planning mechanism similar to a brain will be built in order to achieve this task. The developed mechanism operates at the higher hierarchical level with respect to that of the basic control tasks (reference tracking and disturbance rejection). This will be done using the Linear Time Invariant framework and will be developed for both Single Input-Single Output and Multi Input-Multi Output systems. This approach will then be experimentally validated on various linear and nonlinear laboratory control systems.

ADVANCED CONTROL SYSTEM OF A BIOREFINERY PLANT Call name: Joint Applied Research Projects - PCCA 2013 - call
PN-II-PT-PCCA-2013-4-0070 2014 - 2017

Role in this project: Partner team leader

Coordinating institution: UNIVERSITATEA "DUNAREA DE JOS"

Project partners: UNIVERSITATEA "DUNAREA DE JOS" (RO); UNIVERSITATEA DIN CRAIOVA (RO); UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO); TEAMNET ENGINEERING SRL (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website: http://www.biocon.ugal.ro

Abstract:

The main objective of the BIOCON project proposal is the experimental analysis and in the efficiency increase through automation of a complex biorefinery installation that consists in the coupling of two processes: an anaerobic digestion process and a photosynthetic growth process of microalgae in photobioreactor. The resulting installation is used to obtain microalgal biomass for added value compounds extraction, to bio-mitigate the CO2 evolved from combustion of biogas using it as substrate for the photosynthetic growth of microalgae, to study the utilization of biomass residues derived from the extraction of added value compounds from microalgae as substrate for the production of biogas through anaerobic digestion and to analyze the production of biogas in the anaerobic treatment of wastewaters. To accomplish these objectives with the available resources a structure based on the modern concept HILS (Hardware in the Loop Simulations) was adopted. This structure involves the coupling of an experimental structure (a photobioreactor for the photosynthetic growth of microalgae) and a software structure (an anaerobic digester), noting that this HILS structure behave similarly with an experimental biorefinery installation.

The original scientific contributions of the project consist in solutions for the automation of a very complex process (with strong nonlinearities, affected by parametric and model uncertainties and subjected to perturbations): mathematical models for the anaerobic digester and photobioreactor, and for the coupling between a software entity – anaerobic digester and an experimental one – photobioreactor for microalgae growth; prototype of the biorefinery installation based on the HILS concept, controlled with the process computer; control solutions for the biorefinery installation, advanced control system for the global process. The main novelty and originality character of the project consist in the systemic approach (modeling and control) of the biorefinery installation for which few references can be found in literature. The following main objectives of the project can be mentioned: modeling of the anaerobic digestion process, modeling and identification of the microalgae photosynthetic growth process based on the experiments made on the pilot photobioreactor, synthesis of control algorithms (fuzzy and optimal), for both processes (anaerobic digester and photobioreactor) treated individually and coupled, through numerical simulation and implementation on the biorefinery installation based on HILS concept. In the current competitive context for energy resources, the project aims to encourage the use of anaerobic treatment methods, providing solutions for the removal of nutrients from the anaerobic digester effluents through the photosynthetic growth processes in order to comply with the imposed quality standards. The project also encourages the use of photosynthetic growth processes with low-cost substrates such as wastewater and CO2 from biogas combustion. It must be underlined that both processes and technologies within the project are approached through a systemic-engineering manner that is specific to process automation. The consortium consists in four entities, all with wide experience in the development of scientific research projects: Coordinator – Dunarea de Jos University of Galati, P1 – University of Craiova, P2 – Polytechnic University of Timisoara and T3 – TeamNet SRL Company. The consortium includes specialists in automation, process informatics and biotechnology, responding thus to the interdisciplinary characteristic of the project. The working plan is rigorous and well-balanced, all partner institutions providing highly qualified human resource and appropriate logistics, and creating good premises for the accomplishment of the expected results.

Advanced control systems for bioprocesses in food industry Call name: Joint Applied Research Projects - PCCA 2013 - call
PN-II-PT-PCCA-2013-4-0544 2014 - 2017

Role in this project: Partner team leader

Coordinating institution: UNIVERSITATEA DIN CRAIOVA

Project partners: UNIVERSITATEA DIN CRAIOVA (RO); MOARA CALAFATULUI S.R.L. (RO); UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO); UNIVERSITATEA "DUNAREA DE JOS" (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website: http://www.ace.ucv.ro/adcosbio/

Abstract:

The significant improvement of performance and quality of products in a vital economic domain represented by the food industry can be done by using modern monitoring and control techniques. The project follows the recent research trends and it attempts to unify the team experience in order to apply the research results to bioprocesses in food industry, particularly to bread production and to related wastewater treatment processes.

Bioprocess modelling and control can be successfully achieved using interdisciplinary approaches from control engineering, biochemistry, applied mathematics and information technology. The bioprocesses are complex nonlinear systems, characterized by modelling uncertainties, interconnections, delays, and lack of cheap and reliable instrumentation. Taking into account the previous results obtained by the team in the field of applied automatic control, these interdisciplinary approaches will be used to develop advanced control systems that will be able to deal with the above mentioned specific problems of the bioprocesses.

Firstly, the project will develop advanced control techniques based on nonlinear algorithms (adaptive, predictive, sliding mode, neural, fuzzy, hybrid) for bioprocesses, in different control system structures. Secondly, it will implement, test and validate these techniques on processes in food industry, primary at mills and bread factories. Three main processes are envisaged: bread production, wheat grinding and flour processing, and wastewater treatment.

The main research objectives are:

1. Analysis and modelling of processes in food industry;

2. Development of novel estimation and identification techniques for bioprocesses;

3. Design of advanced control techniques for three classes of bioprocesses;

4. Implementation of advanced control systems for processes in food industry.

These objectives deal with several challenging topics, considered open problems by the Technical Committee on Biosystems & Bioprocesses of the International Federation of Automatic Control (IFAC). These scientific interdisciplinary problems can be investigated and can produce many original elements, and thus the Romanian research in the area can be highlighted.

The research product of the project will be a package of innovative procedures and technologies (algorithms, software and hardware) for bioprocess control, with direct applicability in food industry and wastewater treatment. The specific expected results are as follows: experimental models of fermentation and wastewater treatment bioprocesses, novel identification and estimation techniques (including software tools) for bioprocesses, innovative advanced control technologies, intelligent tuning algorithms for low-cost controllers, practical control solutions for industrial processes in food industry. The ADCOSBIO project is conceived in order to apply these research results in a real industrial environment; by using new control technologies, the processes in food industry can be significantly improved in terms of performance and quality. The applicability of the obtained results can be extended with minor costs to related areas, such as other bioprocesses in food industry (alcoholic and lactic fermentation, synthesis of enzymes) and to various chemical processes.

The research consortium is composed of four partners: three research organizations (University of Craiova - coordinator, “Politehnica” University of Timișoara, University “Dunărea de Jos” of Galaţi) with well known national and international experience in scientific and research area, and one enterprise (SC Moara Calafatului SRL), the biggest mill and bread production enterprise in south-region of Dolj County. The research teams are multidisciplinary, with specialists in control engineering, information technology, electrical engineering, biotechnology, biochemical and agricultural engineering.

Experimental model for an automatic capacitive compensator designed for improving the power factor and for load balancing in low-voltage electricity distribution networks Call name: Joint Applied Research Projects - PCCA 2013 - call
PN-II-PT-PCCA-2013-4-1083 2014 - 2017

Role in this project: Key expert

Coordinating institution: UNIVERSITATEA POLITEHNICA TIMIŞOARA

Project partners: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO); ICPE S.A. (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website: http://www.sites.google.com/site/caeredjt/

Abstract:

The project is meant to finance activities of industrial research and activities related to this field, which are necessary in order to put into practice, under the form of an experimental model, the research findings of a group of academics from the Department of Power Engineering from the Politehnica University of Timisoara - UPT (CO), regarding the load balancing of electric three-phase networks by unbalanced cross capacitive compensation. When using an unbalanced capacitive compensator one can achieve both an improved power factor and a total or almost total balancing of the load. The efficiency of such a compensator becomes significant if the two functions are applied continuously, following the change in load. Large scale replacement of existing capacitive compensators used in low voltage networks with unbalanced capacitive compensators will produce a number of benefits, the most important being the following:

1) increasing the quality of supply voltage to customers (increasing the quality of service of power supply to customers) by total or near-total balancing of three-phase voltages and thus reducing the damage caused by unbalanced three-phase voltages;

2) increasing the energy efficiency of the equipment used for the generation, transmission, distribution and use of electricity, as a result of total or almost total elimination of negative and zero sequence current flow.

The automatically unbalanced capacitive compensator proposed by this project is an innovative product, so achieving a functional experimental model involves overcoming a number of scientific and technical challenges, the most important being: control and single-phase switching of the capacitor banks steps, the construction algorithm and implementation of a programming language for PLC process control, process optimization for automatic compensation.

Two teams of specialists, associated as partners in the present project responded to these challenges:

1) A team from the Politehnica University of Timisoara (CO) (www.upt.ro) composed of academics from the Department of Power Engineering and from the Department of Automation and Applied Informatics, with valuable results of their applied research activity in the field of power engineering and automatic control of processes, respectively.

2) A team from ICPE SA Bucharest (P1) (www.icpe.ro), a prestigious company in the Romanian electrical industry, which includes researchers from the Department of Electrical Equipment, with important achievements in the field, in the form of original technical solutions with industrial applications.

ICPE SA (P1) has stated from the very beginning its interest for the innovative solution proposed by UPT (CO), which is considered as having great potential to be transformed into a competitive product on the national and even on the international market of the industry, with a significant impact. This is why it will help finance the project in a percent of at least 35%.

The project team have young post-doctoral researchers and their involvement in industrial research, project management and dissemination of results may help them improve their professional capabilities and skills.

The results of the research will be subject to evaluation by the scientific community by writing scientific papers and publishing them in scientific journals or presenting them at national and international conferences, at round tables and seminars.

The new technical solutions brought about by this automatic capacitive compensating device concerning the structure, order, dimensioning, automatic control algorithm, will benefit from intellectual property protection, as part of this project.

Software products based on artificial intelligence algorithms applied to modelling and optimization of chemical systems Call name: Joint Applied Research Projects - PCCA-2011 call, Type 2
PN-II-PT-PCCA-2011-3.2-0732 2012 - 2016

Role in this project: Partner team leader

Coordinating institution: UNIVERSITATEA TEHNICĂ "GHEORGHE ASACHI" IAŞI

Project partners: UNIVERSITATEA TEHNICĂ "GHEORGHE ASACHI" IAŞI (RO); UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO); ROMUS TRADING & DEVELOPMENT SRL (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website: http://proiecte.romus.com/proiecte/uti/web/web_home.php?lang=ro

Abstract:

- The main goal of this project is to obtain new software products which implement advanced modeling, optimization and control methodologies based on artificial intelligence tools (neural networks, evolutionary algorithms, fuzzy systems). These methodologies are applied to various complex processes selected from chemical engineering field, but they are designed in a such general and flexible manner that to be also useful for other processes and systems. The artificial intelligence tools are used individually or as soft computing hybrid configurations.

- The software products implementing the modeling, optimization, and control methodologies are the important deliverables of the project. An efficient technological transfer can be realized through activities performed by the partner software company.

- Besides the applied character, the present proposal has a fundamental research component being represented by a high level scientific research whose main results will be found in the published articles. The original and novel elements of this proposal are connected, mainly, to the development of new artificial intelligence algorithms, new variants and combinations among them, the elaboration of complete methodologies for modeling and optimal control and applications to various chemical processes, for which the phenomenological modeling is difficult to be applied.

-The project shall be developed as a partnership of two prestigious universities (Technical University "Gheorghe Asachi" of Iasi, as the project coordinator, and the University "Politehnica" of Timisoara), together with a software company (Romus Trading & Development SRL). The team proposed to fulfill the project objectives is composed of computer scientists and chemists working on the interface of the two fields, chemistry-artificial intelligence, with competence and experience in both areas.

New performance improvement techniques of control systems using experiment-based tuning Call name: Exploratory Research Projects - PCE-2011 call
PN-II-ID-PCE-2011-3-0109 2011 - 2016

Role in this project: Project coordinator

Coordinating institution: Universitatea Politehnica Timisoara

Project partners: Universitatea Politehnica Timisoara (RO)

Affiliation: Universitatea Politehnica Timisoara (RO)

Project website: http://www.aut.upt.ro/~rprecup/grant2011.html

Abstract:

The experiment-based tuning to improve the performance of control systems (CSs) belongs to the data-based control (DbC) framework, where few information on the process is used to meet the CS design specifications. DbC techniques usually work offline after collecting batches of data from the open/closed-loop CS.

Principal Investigator (PI)’s team will develop new DbC tuning techniques for certain CS structures. Their necessity and advantages over other tuning techniques are: no need for process identification, low cost design and implementation, convenient use of elaborated data processing techniques.

Our techniques will be tested in process control in mechatronics applications (servo systems, actuators, 3D crane systems, etc.). The critical analysis of the CS performance and implementation costs of our techniques will be conducted by comparisons with other techniques to prove the improvement and to outline the attractiveness of our techniques to many other areas as well.

This proposal is backed up by the results of PI’s team in control structures and algorithms (including optimal and fuzzy ones) published in high impact leading journal papers (Automatica, IEEE Trans. Ind. Electron., Inf. Sci., Eng. Appl. Artif. Intell., etc.).

This grant aims the funding of the research co-operation of PI’s team reflected by five bilateral projects (2003-2010) and by more than 30 joint publications with teams from Canada, France, Germany, Hungary, Slovenia, The Netherlands and UK.

Creșterea capacității instituționale în domeniul cercetării din Universitatea Politehnica Timișoara Call name: Fondul de Dezvoltare Instituţională - FDI - Competiţia 2021
CNFIS-FDI-2021-0573 2021 -

Role in this project:

Coordinating institution: UNIVERSITATEA POLITEHNICA TIMIŞOARA

Project partners: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Affiliation:

Project website:

Abstract:

Obiectivul general al proiectului este consolidarea capacității instituționale a Universității Politehnica Timișoara (UPT) pentru susținerea infrastructurilor și activităților de cercetare-dezvoltare performante, prin următoarele obiective specifice (OS):

OS 1: Suport pentru asigurarea sustenabilității proiectelor de cercetare finalizate prin promovarea rezultatelor obținute, prin susținerea salarială a personalului implicat în activități de cercetare și prin dezvoltarea unei structuri care să asigure transferul de cunoaștere dobândit în activitățile implementate.

OS 2: Mentenanța și îmbunătățirea echipamentelor de cercetare existente.

OS 3: Asigurarea funcționării în bune condiții a infrastructurilor de susținere a activităților de cercetare-dezvoltare prin continuarea proceselor de digitalizare a activităților administrative.

OS 4: Susținerea activităților desfășurate de UPT pentru dezvoltarea cercetării prin asigurarea resurselor financiare pentru publicarea în reviste științifice de prestigiu și prin asigurarea accesului la literatura științifică de specialitate (baze de date actualizate, publicații în format electronic, biblioteci digitale).

Obiectivele proiectului sunt în concordanță cu politicile naționale de creștere a capacității instituționale în cercetare, cu prevederile Planului strategic de dezvoltare al UPT pentru perioada 2020-2024 și cu măsurile de susținere și promovare a activităților de cercetare prevăzute în planul managerial al rectorului UPT.

Susținerea cercetării de excelență din Universitatea Politehnica Timișoara Call name: Fondul de Dezvoltare Instituţională - FDI - Competiţia 2019
CNFIS-FDI-2019-0696 2019 -

Role in this project: Project coordinator

Coordinating institution: UNIVERSITATEA POLITEHNICA TIMIŞOARA

Project partners: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Affiliation: UNIVERSITATEA POLITEHNICA TIMIŞOARA (RO)

Project website:

Abstract:

Obiectivul general al proiectului este susținerea cercetării de excelență în Universitatea Politehnica Timișoara (UPT), prin următoarele obiective specifice (OS):

OS 1: Suport financiar pentru sprijinirea activităților de excelență în cercetare.

OS 2: Suport pentru asigurarea sustenabilității proiectelor de cercetare încheiate prin susținerea salarială a personalului implicat în activități de cercetare, prin asigurarea mentenanței pentru activitățile deja implementate și prin promovarea rezultatelor obținute.

OS 3: Reparații/îmbunătățiri pentru echipamente deja existente, în limita finanțării de bază.

OS 4: Asigurarea funcționării în bune condiții a infrastructurilor de susținere a activităților de cercetare din cadrul UPT.

Obiectivele proiectului sunt în concordanță cu politicile naționale de susținere a excelenței în cercetare și cu acțiunile din Planul strategic de dezvoltare al UPT pentru perioada 2016-2020, propunându-și să continue activitățile și să dezvolte mecanismele de susținere a cercetării de excelență din UPT. Vor fi finanțate: activități de mentenanță a infrastructurii de cercetare, reparații și îmbunătățiri ale unor echipamente specifice de cercetare, mobilități la manifestări științifice de prestigiu, va fi susținută salarial o parte a personalului implicat în activitatea de cercetare, vor fi dezvoltate mecanisme de creștere a vizibilității cercetării de excelență, de îmbunătățire a proceselor de evidență și monitorizare a proiectelor și granturilor.

FILE DESCRIPTION	DOCUMENT
List of research grants as project coordinator or partner team leader	Download (50.28 kb) 07/10/2019
Significant R&D projects for enterprises, as project manager
R&D activities in enterprises
Peer-review activity for international programs/projects