Call 2019 Partner Search Tool

The Partner Search tool offers to potential applicants to CHIST-ERA Call 2019 the opportunity to find partners, by consulting the list of Expressions of Interest (EoI) below and/or by submitting your own EoI. In the latter case, your EoI will be quality checked and published online within a few days after submission.


Submit your EoI

The following EoI have been submitted for the specific purpose of participating in the Call 2019. Filters are available to search by type of EoI, call topic or country.

Note that to widen participation throughout Europe, proposals are encouraged to include partners from the so-called Widening Countries participating in the call: Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Portugal, Romania, Slovakia and Turkey.

Information: anna.ardizzoni@anr.fr


Expressions of Interest

24-01-2020

Partner looking for project
Explainable Machine Learning-based Artificial Intelligence
Research areas

Research in this area combines expertise in economics, engineering and behavioural psychology to examine policy challenges related to climate change, energy security and sustainable use of environmental resources. The areas where we are active are:transportation, fuel consumption, carbon taxation. The ESRI produces independent, high-quality research with the objective of informing policies that support a healthy economy and promote social progress. Ireland is currently facing many challenges on both fronts. Progress requires policies that are grounded in evidence and therefore likely to act as effective solutions to complex policy challenges.

Comment

Supervised machine learning, econometrics, microsimulation

Contact
Miguel Tovar
Research officer
The Economic and Social Research Institute
Ireland

22-01-2020

Partner looking for project
Explainable Machine Learning-based Artificial Intelligence
Research areas

I'm head of the ISOVIS research group at Linnaeus University, Sweden. Our research interests are decribed online by following this link: https://cs.lnu.se/isovis/research/areas/

We have a broad expertise in Information Visualization and Visual Analytics with applications in text analytics, life sciences and engineering. The explanation of ML/AI models is currently a hot topic in the Information Visualization (InfoVis) community, with results showing that providing insights from ML models can lead to better predictions and improve the trustworthiness of the results.

Our current focus on this research area is (1) methodological by providing surveys and guidance through qualitative and quantitative analyses of its literature and research community as well as (2) technical by developing Visual Analytics (VA) methods to open the black boxes of various ML/AI models.

Comment

We wanna push forward the state-of-the-art of existing visualization approaches for XAI and have an existing collaboration with experts in cognitive psychology, human-computer interaction, and human factors at TU Vienna, Austria. Our collaborator is also interested in joining a project on the above mentioned topic.

Contact
Prof. Dr. Andreas Kerren
Linnaeus University, Department of Computer Science and Media Technology
Sweden

22-01-2020

Project looking for partner(s)
Novel Computational Approaches for Environmental Sustainability
Keywords
computational intelligence systems, climate change, water supply
Abstract

As a consequence of climate change, the regional hydrological cycles in many areas across the world have already or will in the future be altered. Impacts of changing climate on hydropower would be additional stress which the system already faces due to other factors, such as demographic variations, land-use changes, and changing economic activity. Some degree of anthropogenic climate change is unavoidable; and while much effort has been given to the quantitative assessment of water supply, relatively less is known about human-induced climate change on the factors controlling water quality dynamics. Changing climate implies a variability of precipitation and temperature pattern which in turn may affect the streamflow regime and thus altering the resource potential of a given basin. Large-scale climate indices have been employed in hydrological processes because it was proved that the climate indices can provide potential information about climate variability in the global climate system. Simulating the global ecosystem is complex, potentially involving infinite variables that describe and relate nature's chemical, physical, and biological processes. The resulting range of possible climate scenarios has led to public confusion about the validity of climate prediction and, more urgently, to delays inappropriate action. As the hydrological inputs are foremost in assessing the exploitable potential for a hydropower system, the climate change impact assessment study should also integrate a hydrologic model, decently representing the catchment that feeds to the system. Any climate change study that incorporates hydrological modeling is bound to possess uncertainty in the results.

The model based on computational intelligence systems (CIS) can be introduced as alternatives to the traditional models for the complex practice of hydrological variable forecasting. The CIS based models can produce more accurate and stable predictions with the additional advantage of handling nonlinear and non-Gaussian data series; therefore, they can be widely used in the water operations. Moreover, the computational intelligence models are calibrated to provide information for water management and decision-making by providing efficient forecasting performance.

Expertise needed / Role in project

We are looking for partners interested in computational intelligence systems, also we expect partners who have a background in climate change, water treatment plants.

Preferred countries
Any
Comment
 

 

Contact
Rui Araújo
Assistant Professor
ISR-Institute for Systems and Robotics/ DEEC-Department of Electrical and Computer Engineering University of Coimbra, Polo II
Portugal

21-01-2020

Partner looking for project
Novel Computational Approaches for Environmental Sustainability
Research areas

Our group (http://biosystems.lv/) develops models of cellular metabolism and computational tools for doing that. We are developing and optimisng kinetic models of metabolic pathways as well as mediun scale and genome scale stoivhiometric models of metabolism. We have co-authored COBRA toolbox https://opencobra.github.io/cobratoolbox/stable/ for development, analysis and optimisation of constraint based stoichiometric models.

Our group developed the Total Optimisation Potential (TOP) approach for metabolic engineering of microorganisms at the metabolic pathway scale.

We can contribute modeling and optimising biotechnological processes as well as make sustainability assessment (environmental, economical and societal aspects). Software tools can be developed.

Comment

We have rich experience in ERA-net projects since 2013. Several members of our group have IT background.

Contact
Egils STALIDZANS
director
University of Latvia, Institute of Microbiology and Biotechnology
Latvia

21-01-2020

Partner looking for project
Novel Computational Approaches for Environmental Sustainability
Research areas

Kaunas University of Technology (KTU) is the largest technical university in the Baltic States. Being one of the most dynamic centres for higher education in Lithuania, KTU is often regarded as a research and study leader in various fields. The Institute of Environmental Engineering (APINI) a multidisciplinary research institute, who has built up an international reputation for quality environmental research and innovative teaching. The innovations developed by APINI are responsive to the needs of the national economy and the International research market. The institute seeks critical evaluation and innovations in its learning, teaching, research, management, and other activities, propagates innovative technologies, fosters the development of the knowledge society, and actively furthers the preparation of the national long-term development strategy. Institute of Environmental Engineering conducts research in the fields of sustainable development and environmental protection. The main research areas of the Institute are:

  • Environmental performance improvement through cleaner production and pollution prevention
  • Life Cycle Assessment (LCA)
  • Chemicals management and environmental impact assessment
  • Smart city
  • Eco-design
  • Energy efficiency and renewable energy
  • Integrated waste management

The concept of a sustainable city encompassing all the above is one of the key research areas of the Institute. It is the leader of the sustainable and smart city research group in Kaunas University of Technology (urban planning, behavioural change, new transport model shift, demand responsive transport policy development, etc.). The team of the Institute’s researchers focus on activities for creating smart sustainable city employing a cross-sectorial, transdisciplinary and multi-stakeholder approach, which calls for the establishment of strategic collaborations. Also, Institute of Environmental engineering participates and initiates national and international research projects, leads MSc and PhD (Double degree PhD with Bologna University) programmes in environmental engineering, organises online courses related to sustainable mobility and urban planning, professional training, LCA and sustainability assessment.

Website: https://apinien.ktu.edu/

Comment

Scientist and researchers will be involved in the project:

- Professor Ph.D. Zaneta Stasiekiene currently works as a director at the Institute of Environmental Engineering, Kaunas University of Technology, Lithuania. Zaneta has extensive experience in project management and innovations development: she was manager of 53 industrial projects and 10 complex international projects, with numerous stakeholders (governmental institutions, industry, universities, NGO, etc.). Over the past several years Professor’s work was built on diverse expertise in preventive innovation development in industry, sustainability assessment, and environmental economics, which presently are and will remain in the future as one of the important fields of scientific research. Moreover, while participating and managing science – industry and science – society projects she gained excellent people management and organisational skills and the ability to organise others to meet deadlines. Zaneta has an extensive experience in trainings for industrial top managers and representative of governmental institutions, which enables her with strong analytical and written communication skills, experience of writing briefing material and management information reports.
Moreover, Professor Ph.D. Zaneta Stasiekiene has solid record of scholarly contributions and projects.

Website: https://www.researchgate.net/profile/Zaneta_Stasiskiene

- Ph.D. Irina Matijosaitiene currently works at the Data Science Institute, Saint Peter's University, NJ, USA, and Department of Architecture and Urbanism, Kaunas University of Technology, Lithuania. Irina does advanced research in Data Science, Information Systems (Business Informatics), Data Mining and Computing for Insurance Analytics, Environmental sciences, Social science, Crime prevention, and Urban science. She is managing teams of data scientists while developing big-scale data, predictive analytics, machine learning and artificial intelligence projects.

Website: https://www.researchgate.net/profile/Irina_Matijosaitiene

- Gabriele Zabelskyte, a second year Ph.D. Candidate at Kaunas University of Technology, in the Environmental Engineering doctoral program. Gabriele’s interest of field is Urban Ecosystems, Health risks, Urban Planning, Smart Engineering solutions. The main goal of her doctoral thesis is to create Data and Artificial Intelligence (AI) driven solutions for urban ecosystem services to mitigate health risk. For her research she uses top-notch methods and state-of-the-art tools to analyse the doctoral thesis research problem, such as big data, Machine learning, Artificial Intelligence, Deep learning, smart solutions. Gabrielė has experience in working with ArcGIS, Python, statistics tool R, SPSS.

Website: https://www.linkedin.com/in/gabriel%C4%97-zabelskyt%C4%97-85070a5a/

Contact
Gabriele Zabelskyte
The Institute of Environmental Engineering, Kaunas University of Technology
Lithuania

21-01-2020

Project looking for partner(s)
Novel Computational Approaches for Environmental Sustainability
Keywords
microbial communities - NGS data modelling
Abstract

Develop mechanistic methods for hypothesis generation and ad-hoc experimental design of bioprocesses-related microbiomes: a metagenome-scale computational model able to integrate NGS data and metabolic reconstructions to predict/simulate community composition/dynamics from growth and environmental parameters in selected, environmentally relevant case studies. The main goal of this project is to develop a computational framework to: i) predict and simulate microbial assemblage dynamics from environmental parameters and microbial interactions and ii) using such predictions to design intervention strategies to optimize specific environmentally-related biological processes carried out by characterize microbial communities or to sustain naturally occurring microbial biodiversity of unique, pristine environments in the face of global climate changes.

Partners already involved

University of Florence, Italy

University of Warsaw, Poland

Expertise needed / Role in project

Microbial communities of biological interest, NGS data collection

Preferred countries
Different from those already involved
Contact
Marco Fondi
Assistant professor
Dep. of Biology, University of Florence
Italy

20-01-2020

Partner looking for project
Novel Computational Approaches for Environmental Sustainability
Research areas

Plant phenotyping, development, antioxidants

Contact
Miroslava Zhiponova
Department of Plant Physiology
Bulgaria

17-01-2020

Partner looking for project
Explainable Machine Learning-based Artificial Intelligence
Research areas

AICOS is an R&D institute specialised in ethnographic and co-creation methods that can help: 1) identify needs, values, and requirements of users; 2) co-create solutions with users and stakeholders involved in the project in order to ensure the effectiveness of explainable systems. Moreover, AICOS has expertise in interaction and user interface design, as well as mobile, web, cloud, and AI development capabilities, which can contribute to the development of novel XAI approaches.

Contact
Rita Gil Mata
Research Funding Advisor
Fraunhofer Research Portugal
Portugal

16-01-2020

Project looking for partner(s)
Explainable Machine Learning-based Artificial Intelligence
Keywords
AI; Digital Pathology
Abstract

In the last few years the field of pathology is going through the revolution of digitization. This means that the glass slides can be scanned into high resolution computer files. This allows pathologists to send biopsies to second opinion via email and view the images on the screen. 

Moreimportantly, once the slides are digitized, they can be submitted to sophisticated computer vision and AI algorithms. 

Applying state of the art visualization methods to neural networks that are tuned to various challenges in pathology may provide new insights on features that can eb of interest. 

Partners already involved

DeePathology Ltd. - expert in Computer Vision and AI

Expertise needed / Role in project

We look for academic institutes that do resrarch in pathlogy, that have WSI that can be shared and who can anlyze and validate the results of the neural networks. 

Contact
Chen Sagiv
Cם CEO
DeePathology.ai
Israel

15-01-2020

Project looking for partner(s)
Novel Computational Approaches for Environmental Sustainability
Keywords
weather, forecast, windfarm, solarfarm
Abstract

 

Energy from renewable sources is key to eliminate the use of fuel, coal and nuclear sources. However, even if the use of the green source is reliable in ideal conditions, their efficiency and their reliability are reduced considerably when they are used in extreme environments, such as cold, snow and ice conditions. This research proposes to implement the maintenance process of a wind farm into a computational approach in order to optimize and simplify the decision-making procedure.

 The proposed computational approach will consider regular preventive maintenance, weather forecasts, staff availability, peak electricity demand period and a performance index to prioritize infrastructure maintenance.

 

Preferred countries
Any
Contact
Jean-Denis Brassard
Research Professor
Université du Québec à Chicoutimi /Anti-Icing Materials International Laboratory
Canada

15-01-2020

Partner looking for project
Explainable Machine Learning-based Artificial Intelligence
Research areas

Natural Language Processing, Machine Learning, Neuro-Symbolic Reasoning, Automatic Knowledge Base Construction

Comment

We are interested in developing more robust, verifiable, explainable machine learning models that can be useful in small data regimes.

Contact
Pasquale Minervini
Senior Research Associate
University College London
United Kingdom
AttachmentSize
PDF icon curriculum.pdf128.03 KB

14-01-2020

Partner looking for project
Novel Computational Approaches for Environmental Sustainability
Research areas

The IoT Data Assurance and Network Data Analytics group specialise in the communications dimension of data gathering, and evaluating the quality of data when gathering data from multiple data streams (IoT, crowd sourced, web data, etc.).
The group is currently involved with multiple research projects relating to sustainable environments including CONSUS (https://www.ucd.ie/consus/), a large scale and multidisciplinary smart agriculture project, and SmartBOG (www.smartbog.ie), an environmental modelling project for peat-land areas. As such, the group combines cross disciplinary knowledge and expertise in communication engineering, data science and environmental systems.

Comment
  • Communications netowrking and data analitics group with expertise in IoT systems.
  • Analytical approach to robust data collection.
  • Experience in data gathering for environmental features in agricultural and peatland scenarios.
  • Access to live test sites over multiple land use conditions.
Contact
Declan Delaney
Asst. Professor
IoT Data Assurance and Network Data Analytics Group, University College Dublin
Ireland

13-01-2020

Partner looking for project
Novel Computational Approaches for Environmental Sustainability
Research areas

National Research and Development Institute of Occupational Safety – INCDPM “Alexandru Darabont” Bucharest was founded in 1951 by the Romanian Academy. It performs a continuous activity of over 68 years in research for prevention of occupational risks, substantiation of the occupational health and safety legislation, training and technical assistance for companies. INCDPM “Alexandru Darabont” is a Romanian public institution and now it is functioning under the coordination of Ministry of Education and Research. The main activity object consists in fundamental and applied research on the occupational health and safety domain for all types of industrial activities, except potential explosive atmosphere and ionising radiation. INCDPM “Alexandru Darabont” also perform studies and technical assistance on occupational health and safety for companies. The institute has a large expertise in training, performing various training programs (forming/perfection) for Romanian companies. In the last 5 years, the institute has implemented 9 projects (in consortium or alone) at national and EU level, funded by EU-OSHA, EEA Grant or Structural funds. The institute is the host of Focal Point for Romania of European Agency for Occupational Health and Safety (EU-OSHA).

Applicative researches are performed in 6 laboratories: Chemical&Biological Risks; Electrical&Mechanical Risks; Ergonomics; Personal Protective Equipments; Noise&Vibration Control; OHS Management & Risk Assessment.

Further information: www.inpm.ro

Contact
Doru DARABONT
General Director
National Research and Development Institute of Occupational Safety
Romania

10-01-2020

Partner looking for project
Novel Computational Approaches for Environmental Sustainability
Research areas

GEOexplorer Impresa Sociale S.r.l. is an innovative small enterprise (with the status of social enterprise), born as an academic start-up of the University of Siena funded, thanks to the contribution of researchers from the Centre for GeoTechnologies of San Giovanni Valdarno (University of Siena) and the Department of Physics and Earth Sciences (University of Ferrara). Our staff comes from an experience of great passion and work within the Italian university and today puts these characteristics at the disposal of private companies and public bodies. GEOexplorer offers research and services in the field of underground exploration to a wide variety of customers, who must solve practical problems of management of natural and artificial resources, providing complete results and immediately usable. GEOexplorer invests in Research and Development through various channels ranging from scholarship funding, doctorates and research grants to participation in funded projects of organizations such as the Tuscany Region and the EU. Over the years many objectives have been achieved that have allowed the development of an increasingly qualified staff under the scientific aspect and to direct their activities towards the sectors of greatest interest for universities and public administrations.

The experience of the members, for the most part Ph.D. in Earth Sciences, allows to provide geophysical exploration services for superficial and deep research, using both surface methods (seismic, geoelectric, electromagnetic, magnetotelluric and gravimetric) and in hole (down-hole, cross-hole, geophysical logs and dilatometric tests). GEOexplorer also has considerable experience in the hydrogeological sector, providing services in the areas of research, assessment and management of groundwater resources, as well as innovative solutions to meet the growing water demand even in extreme climatic areas. Furthermore, we perform in-situ and in laboratory radioactivity measurements in compliance with the UNI 10797 and the Council Directive 2013/59/Euratom. We are specialized in the radiometric characterization of Naturally Occurring Radioactive Materials (NORMs), which are byproduct materials of human activities containing natural radionuclides in higher than normal concentrations. Lastly, these skills are complemented by a strong predisposition for technological innovation: this was mainly focused on the airborne implementation, through the design, construction and marketing of Rad_gyro services, an autogyro built-up to support gamma spectroscopy with remote sensing in a large part of the electromagnetic spectrum. The company structure allows access to a wide range of skills ranging from support during the flight to data processing, mapping, land measurements and topographic acquisition. We operate by efficient and innovative technologies, applying geophysical, hydrogeological and airborne methods. We integrate geophysical, hydrogeological, and environmental methodologies, operating directly in the field and in the laboratory with technologically advanced equipment: this approach allows to greatly reduce the risks related to the earth, prevent environmental problems and optimize the resources of the subsoil.

Detailed topics:

• Exploration of the subsoil for research and water supply
• Evaluation and analysis of water resources about quantitative and qualitative features
• Study of soil and subsoil for agronomic and wine-producing applications
• Surveys to support geotechnical design and slope stability
• Technologies for the study of rock masses in extractive areas
• Study of the radioactivity level of lands, rocks, air and building materials
• Technologies for cultural heritage
• Hydrogeological and environmental studies for polluted sites
• Training and capacity building

Website: http://geoexplorer.cgtgroup.org/en/geoexplorer/

Comment

As a social enterprise funded by researchers (physics and heart scientist) from two Italian university (University of Siena and University of Ferrara), we can provide a wide, flexible and multidisciplinary point of view to our potential project partners. Furthermore, in our specialized fields (groundwater and natural radioactivity) we may provide a network of interested stakeholders and tests sites where the project innovative computational approach can be tested.

Contact
Colonna Tommaso, PhD
Company President
GEOexplorer Impresa Sociale S.r.l.
Italy

10-01-2020

Partner looking for project
Novel Computational Approaches for Environmental Sustainability
Research areas

CGT SpinOff S.r.l. is a private company founded in May 2010, by the researchers of the CGT – Centre for GeoTechnologies (University of Siena, Italy) as an academic spin off in order to capitalize their ten-year research experience in Applied Geology and Geotechnologies. The company, certified ISO 9001: 2015, relies on the experience of a staff that has carried out over 700 research and scientific consulting projects using scientific advice from leading figures in the academic and professional world. The technical and scientific competence of CGT SpinOff S.r.l. staff is its own most important asset. The staff recruitment policy is based on the selection of motivated and highly trained young people. Constant attention is paid to technical and scientific updating through the involvement of company personnel in scientific production and dissemination, academic involvement by the University of Siena, Ph.D. co-tutoring in environmental applied research. Thanks to the professional and academic experience of its staff, CGT SpinOff S.r.l. utilizes the most innovative and tested methodologies in the fields of Applied and Environmental Geology, Geopedology, Hydrogeology and Geomatics, always with continuous updates given the close link to the world of scientific.

The technologies utilized are consequently the most modern available on the market and not, being able to experiment or contribute to the development of new tools and systems still in the prototype phase, as well as consolidating the use of the latest technological discoveries supplied by the major national and international producers. CGT SpinOff S.r.l. offers services and consultancies for Geomatics and Environment to achieve the goals of private companies and public bodies that have the following needs related to the territory.

Detailed topics:

·         Geology for the environment and the territory
·         Hydrogeological and environmental studies for contaminated sites
·         Annual and multi-year aquifer monitoring plans
·         Environmental characterization plans, Risk analysis, Drafting of remediation projects
·         Creation of software for environmental data collecting and integrated managing
·         Numerical modeling of groundwater flow and transport of pollutants in groundwater
·         Spatial, temporal and geostatistical data analysis
·         Study of the soil and subsoil for agronomic and wineyard applications
·         Application of technologies for the study and monitoring of rock masses in natural contexts and extractive areas
·         Rock stability analysis using traditional equilibrium methods and advanced numerical modeling methods
·         GIS, databases and Topography at the service of public and private institutions
·         Digital photogrammetry and remote sensing for the environment and the territory
·         Surveys with remote piloted aircraft systems in natural or anthropic contexts
·         Training and capacity building 

Website: http://www.cgt-spinoff.it/en/home-3/

Comment

As a company specialyzed on enviromental activities we can offer our expertize, regarding this call, on field activities, test site management and liasonig office with stakholders and environmental authorities in order to efficently test the proposed approach. In particular, thanks to our multidisciplary staff (already exeperienced in international project) and academic contacts we are confident to be able to addres different potential issues which may rise during the project and provide a wider, than our main research areas, technical support to the project partners.

Contact
Guastaldi Enrico, PhD
Company President
CGT SpinOff S.r.l.
Italy

10-01-2020

Partner looking for project
Explainable Machine Learning-based Artificial Intelligence
Research areas

We are Turkish consulting company, based in Istanbul, working over 10 years in the field of R&D consulting activities. We have over 200 customers from various expertise like ICT, defense, machine and tool producers, dedicated to faciliate the company?s R&D path both in national and international level. We are running over 25 EU funded projects, over 1000 national collaborative projects. We have large scale of customer number, our customers are active in various sectors , two of them are the biggest ecommerce companies ; HEPSIBURADA , TRENDYOL (investment and strategic partnership with ALIBABA) https://www.hepsiburada.com : The Company is the market leader in the high growth Turkish online retail sector and is the most visited online retail site in the country, with over 1.5 million unique customers a year and more than 14 million unique monthly visitors, corresponding to more than a third of Turkey's total online population Company is the part of big group active in the media, energy, financial services and tourism sectors. The Company began as a vertical e-commerce player focused on IT hardware and has since diversified its portfolio. Its offering of 500,000 products in more than 30 different categories in 2014 is rapidly expanding and already has a broad range from mobile phones to cosmetics. https://www.trendyol.com : Company is the largest and fastest growing mobile commerce company in Turkey and in the MENA region. Company mission is to serve our customers to buy what they want, when they want with the best experience driven by technology. Company are a Tech company - Technology is the driver, Company have announced an investment and strategic partnership with Alibaba Group which is the largest internet sector in 2018 . The Company is always open to growth and development and is qualified to take part in technology projects. Please let me know if you need ecommerce partner related consorsia about Artificial intelligence, deep learning and machine learning, virtual reality, image and voice processing, big data, automation, natural language processing, Blockchain, wearable Technologies.

Comment

I would be grateful for a reply to my e-mail address below:
meltem.bayraktar@etkinproje.com

Contact
Meltem
R&D Project Manager
Etkin Proje
Turkey

09-01-2020

Partner looking for project
Explainable Machine Learning-based Artificial Intelligence
Research areas

 

Machine learning, deep learning, natural language processing, data mining, software development

 

 

Comment

 

Koçfinans was established in 1995 to provide consumers with direct financing; it is Turkey’s first and leading financing company, and it offers loan services across many sectors (https://www.kocfinans.com.tr/en/). Its R&D Department has been conducting innovative software projects in the field of optimization, data mining, machine learning, information technology and systems management since 2017.

With the open banking developments in the banking and finance sector the introduction of financial services through APIs has become widespread. Koçfinans is the first financing company that uses innovative, scalable and high-performance microservice architecture in loan application, evaluation and opening processes. In preparation for this process, Koçfinans has developed Devops infrastructure by combining open source tools, using test-oriented development (TDD) techniques, running static code analysis on developed codes, and performing a large percentage of its tests with automations.

In the process of digitalization, Koçfinans searches solutions that increase efficiency and automation in nearly all of its processes. The activities carried out by the legal department which is done manually, the majority of which can not be fully formulated and involves variable decision-making has been modeled and developed by optimization, text mining and machine learning techniques. Koçfinans focus on the AI solutions primarily for customers and internal stakeholders and continues to carry out advanced data analytics projects.

With the grant support we have given at İTÜ Cekirdek Big Bang Entrepreneurship Competition we believe in the importance of technology initiatives and the creation of an ecosystem around these initiatives. We are cooperating with academic institutions and start-ups for the projects developed and looking for new partnerships with national and international academic institutions and R&D centers.

 

Contact
Ozden Ozvural
R&D Process Manager
IT and R&D
Turkey

09-01-2020

Partner looking for project
Explainable Machine Learning-based Artificial Intelligence
Research areas

BeyondMinds is an applied AI research company based in Tel Aviv and London. Our mission is to develop innovative AI technologies that change industries and have a positive impact on economics and humanity.
We are currently working on technological advancements in the fields of Explainable AI (xAI), Bias and Uncertainty in AI models, Data Compression using NN and more.
We’re a team of AI researchers and technologists with over 50% dedicated to research activities. This has made us capable of solving the most challenging problems in diverse industries with state-of-the-art accuracies.
The technologies we are developing are already powering companies in different industries such as Finance, HealthCare, and Defense to help address real-world challenges. Today, we are trusted by customers and partners all over the world.
For more details, visit https://www.beyondminds.ai/

Contact
Carmel Shor
Algorithm Researcher
BeyondMinds
Israel

08-01-2020

Project looking for partner(s)
Novel Computational Approaches for Environmental Sustainability
Keywords
Ecology, genetic algorithm, python,
Abstract

The EU Water Framework Directive (EC 2000) indicates that the ecological status of water bodies is required to quantify by the establishment of methods. Ecological status is assessed by different indicators. Biological indicators are a key parameter for this assessment. A numerical scale between zero and one, the ‘Ecological Quality Ratio’ (EQR) is used for biological assessment results. Ecological quality ratios are applied for the classification of ecological status. These ratios shall represent the relationship between the values of the biological parameters observed for a given body of surface water and the values for these parameters in the reference conditions applicable to that body. The ratio shall be expressed as a numerical value between zero and one, with high ecological status represented by values close to one and bad ecological status by values close to zero. The value for the boundary between the classes of high and good status, and the value for the boundary between good and moderate status shall be established through the intercalibration exercise. EQR requires that several key issues are addressed, including the choice of appropriate indicators, typology, reference conditions, and agreement on common principles for setting quality class boundaries. Chemical, physical, biological, hydrological and hydromorphological parameter have been used to determine EQR. However, there are not enough studies about determination EQR and appropriate tool. We aim to develop tool for the calculation of EQR by using different optimization methods.

Partners already involved

Abant İzzet Baysal University, Department of Environmental Engineering

Expertise needed / Role in project

We need expertise about nonlinear optimization algorithms such as genetic algorithm, python software or any program codes, and also we expect from partners who have a background about the environment, ecology.

We prefer partners who have experience in tool development in environmental issues.

Contact
Ayfer ÖZDEMİR
The Republic of Turkey Ministry of Agriculture and Forestry General Directorate of Water Management
Turkey

08-01-2020

Partner looking for project
Explainable Machine Learning-based Artificial Intelligence
Research areas

- Control algorithms
- AI based embedded control
- Inverse Optimal Control (IOC) or inverse reinforcement learning (IRL)
- Open ECU (electronic control unit)
- Evaluation toolbox (interface)
- Dynamic simulator/ CAVE (VR/AR/MR)
- Closed loop controller design and comparison with uncontrolled state
- Human centred open ECU
- Human centred vehicle dynamics control
- Embedded software
- Embedded control
- OpenIMU platform

Contact
Baris Aykent
Senior Project Manager
Profen Group
Turkey

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