© 2021 Logicx Research & Development
© 2021 Logicx Research & Development
About Us
#story #vision #mission #drive
Logicx Research & Development is an internal incubator of Logicx Innovations GmbH. The R&D team is responsible for finding, validating, and developing new product ideas in the IT domain.
Why are we doing it? Because we love challenging state-of-art solutions and enjoy the process of success formation.
Why are we doing it? Because we love challenging state-of-art solutions and enjoy the process of success formation.
Our Process
From inspiration to product, from product to a functioning business, from functioning business to a new inspiration
Our Process
From inspiration to product, from product to a functioning business, from functioning business to a new inspiration
1
Create a pool of product ideas
Although, initially we consider almost any idea worthy of discussion and exploration, we mainly focus on AI-related technologies such as predictive analysis, object recognition, process optimization, and complex simulation.
2
Select one idea to focus on
After a literature review, evaluation of state-of-the-art products, analysis of business potentials, and technical feasibility studies, we focus on one idea that is proven to be the most plausible considering the information at this stage. Beside taking into account theoretical, technical, and market factors in picking the right idea to proceed, the potential synergy with existing projects and products in the group portfolio also plays an important role as a decision factor.
3
Organize project financing
Logicx Innovation GmbH is our premier investor for the MVP stage. Depending on the project type, we often consider cooperation with universities, industrial partnerships, as well as research and innovation funding programs.
4
Implement a Minimum Viable Product (MVP)
Depending on the product complexity, the MVP development stage might last six to eighteen months. This stage is critically important for the future success of the project since it is meant to expose the idea to the outside world. Therefore, we design and implement the product core in a small team, where each member ensures the achievement of the target quality with extreme dedication and passion.
5
Turn MVP into a sustainable business
After testing the MVP with our first customers, we focus our efforts on establishing a team that will enable implementation of following business plan steps, including all required aspects such as further technical development, sales, building strategic partnerships, organizing financing, etc.
6
Continue the process of innovation
After making sure that our project turned into a sustainable business organization we start a search for the next idea to get inspired with.
After making sure that our project turned into a sustainable business organization, we start a search for the next idea to get inspired with.
After making sure that our project turned into a sustainable business organization, we start a search for the next idea to get inspired with.
Our Projects
Our Projects
RAIL DIGITAL TWIN
Rail Digital Twin is a recent R&D baby with scheduled first MVP release date in 11/2022. The Twin will offer corporate-wide planning consistency and operational efficiency for railway companies.
The system is designed for analysis of short-term and long-term effects of managerial strategies, tracing cause-effects relationships from high level systems to individual assets, and virtually testing decisions under varying external conditions.
The system takes into account parameters of demand, infrastructure, operations, and rolling stock (D.I.O.R.) in a track-exact timetable simulated for the next 30 years and shows resulting capacity, quality, and economic KPIs.
The project is funded by Logicx Group and an Innovation grant from Vienna Business Agency.
Rail Digital Twin is a recent R&D baby with scheduled first MVP release date in 11/2022. The Twin will offer corporate-wide planning consistency and operational efficiency for railway companies.
The system is designed for analysis of short-term and long-term effects of managerial strategies, tracing cause-effects relationships from high level systems to individual assets, and virtually testing decisions under varying external conditions.
The system takes into account parameters of demand, infrastructure, operations, and rolling stock (D.I.O.R.) in a track-exact timetable simulated for the next 30 years and shows resulting capacity, quality, and economic KPIs.
The project is funded by Logicx Group and an Innovation grant from Vienna Business Agency.
RAIL DIGITAL TWIN
Rail Digital Twin is a recent R&D baby with scheduled first MVP release date in 11/2022. The Twin will offer corporate-wide planning consistency and operational efficiency for railway companies.
The system is designed for analysis of short-term and long-term effects of managerial strategies, tracing cause-effects relationships from high level systems to individual assets, and virtually testing decisions under varying external conditions.
The system takes into account parameters of demand, infrastructure, operations, and rolling stock (D.I.O.R.) in a track-exact timetable simulated for the next 30 years and shows resulting capacity, quality, and economic KPIs.
The project is funded by Logicx and an Innovation grant from Vienna Business Agency.
Rail Digital Twin is a recent R&D baby with scheduled first MVP release date in 11/2022. The Twin will offer corporate-wide planning consistency and operational efficiency for railway companies.
The system is designed for analysis of short-term and long-term effects of managerial strategies, tracing cause-effects relationships from high level systems to individual assets, and virtually testing decisions under varying external conditions.
The system takes into account parameters of demand, infrastructure, operations, and rolling stock (D.I.O.R.) in a track-exact timetable simulated for the next 30 years and shows resulting capacity, quality, and economic KPIs.
The project is funded by Logicx and an Innovation grant from Vienna Business Agency.
~
OTPICAL SUPPORT SYSTEM (OSS)
The goal of this project was to design a safety-critical warning system for preventing train departure or movement towards a red signal visible in a distance from 1 to 600 meters. The system includes hardware, recognition software, and an online reporting tool. The project has successfully passed the field test and substantially outperformed alternative products.
Here are some of the design challenges we had to solve:
The goal of this project was to design a safety-critical warning system for preventing train departure or movement towards a red signal visible in a distance from 1 to 600 meters. The system includes hardware, recognition software, and an online reporting tool. The project has successfully passed the field test and substantially outperformed alternative products.
Here are some of the design challenges we had to solve:
- Design of a wide-angle and high-resolution camera system able to see a signal both from a very close and extremely far distances regardless of the tracks curvature.
- In-motion rail curvature detection and camera pack rotation, allowing rail tracking from 1 to 600 meters ahead.
- Error-free detection of rail signals and rule-based identification of the ones relevant for the used track.
- Creation of a light-weight and compact hardware design allowing the camera pack installation on a windshield.
- Environmental stability of the recognition: operation at night, with extreme contrast situations against the direct sunlight, in a fog, during a rain, in a snow shower, etc.
- Hardware stability in extreme temperature modes: under the direct sunlight without air conditioning, in transition from low to normal temperature, etc.
OTPICAL SUPPORT SYSTEM (OSS)
The goal of this project was to design a safety-critical warning system for preventing train departure or movement towards a red signal visible in a distance from 1 to 600 meters. The system includes hardware, recognition software, and an online reporting tool. The project has successfully passed the field test and substantially outperformed alternative products.
Here are some of the design challenges we had to solve:
The goal of this project was to design a safety-critical warning system for preventing train departure or movement towards a red signal visible in a distance from 1 to 600 meters. The system includes hardware, recognition software, and an online reporting tool. The project has successfully passed the field test and substantially outperformed alternative products.
Here are some of the design challenges we had to solve:
- Design of a wide-angle and high-resolution camera system able to see a signal both from a very close and extremely far distances regardless of the tracks curvature.
- In-motion rail curvature detection and camera pack rotation, allowing rail tracking from 1 to 600 meters ahead.
- Error-free detection of rail signals and rule-based identification of the ones relevant for the used track.
- Creation of a light-weight and compact hardware design allowing the camera pack installation on a windshield.
- Environmental stability of the recognition: operation at night, with extreme contrast situations against the direct sunlight, in a fog, during a rain, in a snow shower, etc.
- Hardware stability in extreme temperature modes: under the direct sunlight without air conditioning, in transition from low to normal temperature, etc.
~
RAIL SWITCH PREDICTIVE MAINTENANCE (SPM)
The goal of this project was to convert sensor readings into actionable insights, allowing rail infrastructure managers to reduce their maintenance costs and improve asset availability, thus helping operators to increase their punctuality and avoid unpleasant train delays.
We consider rail switches being one of the most relevant applications of our predictive maintenance know-how in a rail infrastructure domain due to the following two facts:
The Logicx SPM system has been tested for 9 months on 9 frequently used switches and demonstrated prediction precision and reliability both in absolute and relative terms. SPM produced 15 times less false negative predictions and 3 times less false positive predictions in comparison to the native analytic system delivered by the switch manufacturer. The pilot version of SPM has predicted 95% of failures and produced 18% false positive alarms.
Here are a few research challenges we have faced during the system design face:
The goal of this project was to convert sensor readings into actionable insights, allowing rail infrastructure managers to reduce their maintenance costs and improve asset availability, thus helping operators to increase their punctuality and avoid unpleasant train delays.
We consider rail switches being one of the most relevant applications of our predictive maintenance know-how in a rail infrastructure domain due to the following two facts:
- By being itself an advanced data processing layer, Logicx SPM reuses already existing sensor data collection & storage systems, which makes Logicx SPM introduction a lite and cost efficient project
- According to our research, maintenance of switches, on average, takes up to one third of maintenance budget of rail infrastructure companies
The Logicx SPM system has been tested for 9 months on 9 frequently used switches and demonstrated prediction precision and reliability both in absolute and relative terms. SPM produced 15 times less false negative predictions and 3 times less false positive predictions in comparison to the native analytic system delivered by the switch manufacturer. The pilot version of SPM has predicted 95% of failures and produced 18% false positive alarms.
Here are a few research challenges we have faced during the system design face:
- Giving an operator an actionable insight, saying in how many days a switch is likely to fail (alternative systems did not provide any safety window information).
- Showing the switching phase in which the failure is likely to occur.
- Developing a generic prediction method that would work both for electric and hydraulic switches.
- Providing technicians with visual information that would allow them trace back and understand issues.
- Using data from pre-installed power consumption sensors, and avoiding installation of proprietary sensors.
- Development of a deep-learning system for automatic model parameter tuning for new switch types and instances.
RAIL SWITCH PREDICTIVE MAINTENANCE (SPM)
The goal of this project was to convert sensor readings into actionable insights, allowing rail infrastructure managers to reduce their maintenance costs and improve asset availability, thus helping operators to increase their punctuality and avoid unpleasant train delays.
We consider rail switches being one of the most relevant applications of our predictive maintenance know-how in a rail infrastructure domain due to the following two facts:
The Logicx SPM system has been tested for 9 months on 9 frequently used switches and demonstrated prediction precision and reliability both in absolute and relative terms. SPM produced 15 times less false negative predictions and 3 times less false positive predictions in comparison to the native analytic system delivered by the switch manufacturer. The pilot version of SPM has predicted 95% of failures and produced 18% false positive alarms.
Here are a few research challenges we have faced during the system design face:
The goal of this project was to convert sensor readings into actionable insights, allowing rail infrastructure managers to reduce their maintenance costs and improve asset availability, thus helping operators to increase their punctuality and avoid unpleasant train delays.
We consider rail switches being one of the most relevant applications of our predictive maintenance know-how in a rail infrastructure domain due to the following two facts:
- By being itself an advanced data processing layer, Logicx SPM reuses already existing sensor data collection & storage systems, which makes Logicx SPM introduction a lite and cost efficient project
- According to our research, maintenance of switches, on average, takes up to one third of maintenance budget of rail infrastructure companies
The Logicx SPM system has been tested for 9 months on 9 frequently used switches and demonstrated prediction precision and reliability both in absolute and relative terms. SPM produced 15 times less false negative predictions and 3 times less false positive predictions in comparison to the native analytic system delivered by the switch manufacturer. The pilot version of SPM has predicted 95% of failures and produced 18% false positive alarms.
Here are a few research challenges we have faced during the system design face:
- Giving an operator an actionable insight, saying in how many days a switch is likely to fail (alternative systems did not provide any safety window information).
- Showing the switching phase in which the failure is likely to occur.
- Developing a generic prediction method that would work both for electric and hydraulic switches.
- Providing technicians with visual information that would allow them trace back and understand issues.
- Using data from pre-installed power consumption sensors, and avoiding installation of proprietary sensors.
- Development of a deep-learning system for automatic model parameter tuning for new switch types and instances.
~
OPTICAL ASSET RECOGNITION (OAR)
The goal of this project was to create a mobile app for supporting work of rail maintenance engineers and improving quality of rail infrastructure asset databases. For this purpose we had to find the most efficient methods for generic object detection, classification, and object parameter definition.
Here are a few challenges we had to address in the OAR project:
The goal of this project was to create a mobile app for supporting work of rail maintenance engineers and improving quality of rail infrastructure asset databases. For this purpose we had to find the most efficient methods for generic object detection, classification, and object parameter definition.
Here are a few challenges we had to address in the OAR project:
- Creation of a generic system that can be set up for the recognition of a new object type within 1 day.
- Creation of a generic multi-level object hierarchy, allowing recognition not only of objects but also of their subparts.
- Simultaneous recognition of small and large object parts (10-25 times size difference).
- Recognition quality assurance system: working with indoor and outdoor lighting, object pictures and pictures of pictures, different weather conditions, high and low contrast environments, object color variations, as well as with confusing background patterns.
- Object recognition in real time speed.
- Identification not only of object types but also of object instances.
- Size identification of remote objects (10 to 50 meters away from a camera), since in-built distance detection in modern smartphones works only in a close range (<5 m).
OPTICAL ASSET RECOGNITION (OAR)
The goal of this project was to create a mobile app for supporting work of rail maintenance engineers and improving quality of rail infrastructure asset databases. For this purpose we had to find the most efficient methods for generic object detection, classification, and object parameter definition.
Here are a few challenges we had to address in the OAR project:
The goal of this project was to create a mobile app for supporting work of rail maintenance engineers and improving quality of rail infrastructure asset databases. For this purpose we had to find the most efficient methods for generic object detection, classification, and object parameter definition.
Here are a few challenges we had to address in the OAR project:
- Creation of a generic system that can be set up for the recognition of a new object type within 1 day.
- Creation of a generic multi-level object hierarchy, allowing recognition not only of objects but also of their subparts.
- Simultaneous recognition of small and large object parts (10-25 times size difference).
- Recognition quality assurance system: working with indoor and outdoor lighting, object pictures and pictures of pictures, different weather conditions, high and low contrast environments, object color variations, as well as with confusing background patterns.
- Object recognition in real time speed.
- Identification not only of object types but also of object instances.
- Size identification of remote objects (10 to 50 meters away from a camera), since in-built distance detection in modern smartphones works only in a close range (<5 m).
~
SMART GROCERY SHOPPING APP
This app is meant to substitute outdated paper booklets with special offer ads and coupons from grocery shop chains, that have traditionally been delivered to households post boxes.
The goal of this project was to create a system that would learn user's shopping behavior based on her/his activities in multiple online and brick and mortar stores (as opposed to analysis based on a single shop loyalty program).
The app helps consumers find grocery products and household supplies at a better price and suggests optimized shopping strategies for benefiting from special offers from all available supermarket chains.
Here are a few development challenges we had to consider in this project:
This app is meant to substitute outdated paper booklets with special offer ads and coupons from grocery shop chains, that have traditionally been delivered to households post boxes.
The goal of this project was to create a system that would learn user's shopping behavior based on her/his activities in multiple online and brick and mortar stores (as opposed to analysis based on a single shop loyalty program).
The app helps consumers find grocery products and household supplies at a better price and suggests optimized shopping strategies for benefiting from special offers from all available supermarket chains.
Here are a few development challenges we had to consider in this project:
- Development of a method for high-accuracy recognition of printed receipts with different layouts.
- Learning shop-specific product abbreviations.
- Learning shop-specific product categorization system.
- Coming up with correct user profile classification and behavioral patterns explanation (e.g. a vegetarian buying a steak for a friend).
- Shopping effort optimization: we want to take into account personal utility functions that reflect substitution rate between time, physical effort, and money. In other words, how much time and physical effort would a person be willing to sacrifice for a sum that can be saved.
SMART GROCERY SHOPPING APP
This app is meant to substitute outdated paper booklets with special offer ads and coupons from grocery shop chains, that have traditionally been delivered to households post boxes.
The goal of this project was to create a system that would learn user's shopping behavior based on her/his activities in multiple online and brick and mortar stores (as opposed to analysis based on a single shop loyalty program).
The app helps consumers find grocery products and household supplies at a better price and suggests optimized shopping strategies for benefiting from special offers from all available supermarket chains.
Here are a few development challenges we had to consider in this project:
This app is meant to substitute outdated paper booklets with special offer ads and coupons from grocery shop chains, that have traditionally been delivered to households post boxes.
The goal of this project was to create a system that would learn user's shopping behavior based on her/his activities in multiple online and brick and mortar stores (as opposed to analysis based on a single shop loyalty program).
The app helps consumers find grocery products and household supplies at a better price and suggests optimized shopping strategies for benefiting from special offers from all available supermarket chains.
Here are a few development challenges we had to consider in this project:
- Development of a method for high-accuracy recognition of printed receipts with different layouts.
- Learning shop-specific product abbreviations.
- Learning shop-specific product categorization system.
- Coming up with correct user profile classification and behavioral patterns explanation (e.g. a vegetarian buying a steak for a friend).
- Shopping effort optimization: we want to take into account personal utility functions that reflect substitution rate between time, physical effort, and money. In other words, how much time and physical effort would a person be willing to sacrifice for a sum that can be saved.
~
Our Team
What makes us a team? Probably the fact that we enjoy working with each other, try to listen and understand the reasoning behind other's words, and share the passion for bringing new ideas to success
Our Team
What makes us a team? Probably the fact that we enjoy working with each other, try to listen and understand the reasoning behind other's words, and share the passion for bringing new ideas to success
Georg Doppler-Popovic
Founder & CEO of Logicx group of companies
Georg inspires us with his vision and values. Apart from being the CEO of Logicx companies and carrying full responsibility as an R&D team member, Georg plays a mentor role, sharing his expertise in requirements engineering, project structuring, software architecture, UI/UX, and information design.
Alireza Ghane
Chief R&D engineer
Alireza has a strong academic background as a researcher at Simon Fraser University in Canada and at the University of Vienna. His expertise covers such fields as nonlinear recursive integral equations, rendering algorithms, computer vision, deep neural networks hardware engineering, and high performance computing.
Daniel Shulman
Requirements engineering & Business development
Daniel inspires us to bring the best of us to the light. He loves to think beyond borders and to encourages us to fight for our dreams, at the same time having in mind that no one should follow external goals more than her/his inner call for self-realisations. His communication skills and empathy create a fundament that allows people from all over the world to join our team.
Our Advisers and Mentors
Our Advisers and Mentors
Univ.-Prof. Torsten Möller, PhD
Scientific Adviser
Torsten is a head of research group Visualization and Data Analysis at University of Vienna. Torsten's research interests include visualization, computer graphics, image processing, and data science. Torsten is an Editor-in-Chief (EiC) of IEEE Computer Graphics and Applications journal, general chair of IEEE Symposium on Visualization in Data Science (VDS), and has been a member of 15+ scientific committees. Torsten has held research and management positions in several universities in the USA, Canada, Austria, and Switzerland.
Ing. Robert Nieschlag
Railway Industry Expert
Robert has 40+ years of experience in railroad infrastructure management at Austrian Federal Railways during which he structured, lead and executed complex projects aimed at improvement of system punctuality, safety and efficiency.
Robert helps us finding adequate and realistic answers for the railroads by applying best practice approaches in combination with state-of-the-art technical innovations.
Robert helps us finding adequate and realistic answers for the railroads by applying best practice approaches in combination with state-of-the-art technical innovations.
Ing. Robert Stenitzer
Software Engineering Mentor & Logicx Group CTO
Robert consults our team on difficult software engineering problems and helps us to make sure that our technology choices are future-proof, well thought-out, and go in line with the overall group IT strategy.
Robert has over 15 years of highly successful software engineering and IT project management experience, which helps us finding shortcuts in complex decision making problems.
Robert has over 15 years of highly successful software engineering and IT project management experience, which helps us finding shortcuts in complex decision making problems.
Dipl.-Ing. Arkadi Seidscher, PhD
Research Adviser & Automotive Industry Expert
Arkadi is our research adviser for the logistics related topics. The main fields of Arkadi's scientific expertise are supply chain and inventory management. Arkadi is an automotive industry expert, being a head of materials management at a global automotive tier-1 supplier.
Dmitry Etin, M.Sc.
Biotech Adviser
Dmitry is a founding member of Forome Association that consolidates international research efforts in a field of undiagnosed rare disease treatment. Dmitry has been a solution architect at multiple international corporations including EMC, Dell, and OpenText, working on large-scale healthcare system digitization projects in Europe, Middle-East, and Africa. Most recently, Dmitry has assumed the position of a World Wide Life Sciences Presale Lead at OpenText.
Open Positions
Join our team!
Open Positions
Join our team!
Full-stack R&D engineer (f/m)
ABOUT THE POSITION
In this position you would be in the core team to develop a highly sophisticated digital twin system for the railway industry. The system is designed for analysis of short- and long-term effects of managerial decisions, and trace causes and effects from high level systems to individual assets.
The offered role requires a mixture of architectural and hands-on development skills. Though software architecture design is critically important for the project success, it will take approximately 20% of the focus, since it is done once and reused as the project roadmap for a large portion of the development timeline. The other 80% of the effort will be invested in the front-end design and implementation of the UI-related services. The implementation of the core analysis and simulation services in the backend is done by other team members. Stating this, we would like to underline that it is critically important for the project's success that you should be passionate about information visualization and UI design. At the same time, a responsive and interactive data visualization / UI in this project would require both front-end and back-end competence. Such expertise is required due to data transformations and process optimizations that would only be possible with the proper interactions between front-end and back-end services,
MINDSET REQUIREMENTS FOR THE DIGITAL TWIN TEAM
This job requires advanced technical and personal qualities such as
· Ability to independently design complex high-performance software from scratch
· Persistence in achieving goals and ability to challenge typical solutions
· Personal honesty, reliability, and commitment to the team
REQUIRED SKILLS / EXPERIENCE
· Experience in microservice architecture / orchestration
· Experience with data visualization front-end technologies
· Experience in .Net Core
· Experience with front-end frameworks, ideally vue.js
· Familiarity with UI/UX topics
· Completed technical education in a computer science domain
· Fluent English
WE OFFER YOU TO
· Enjoy the opportunity of developing an innovative and complex product from scratch
· Gain insight into the railway industry
· Work in a small international team with a flat hierarchy
· Competitive salary compliant with Austrian collective agreement and overpayment according to your qualifications
· Top technical equipment for business and private use
· Modern office in the Vienna city center
In this position you would be in the core team to develop a highly sophisticated digital twin system for the railway industry. The system is designed for analysis of short- and long-term effects of managerial decisions, and trace causes and effects from high level systems to individual assets.
The offered role requires a mixture of architectural and hands-on development skills. Though software architecture design is critically important for the project success, it will take approximately 20% of the focus, since it is done once and reused as the project roadmap for a large portion of the development timeline. The other 80% of the effort will be invested in the front-end design and implementation of the UI-related services. The implementation of the core analysis and simulation services in the backend is done by other team members. Stating this, we would like to underline that it is critically important for the project's success that you should be passionate about information visualization and UI design. At the same time, a responsive and interactive data visualization / UI in this project would require both front-end and back-end competence. Such expertise is required due to data transformations and process optimizations that would only be possible with the proper interactions between front-end and back-end services,
MINDSET REQUIREMENTS FOR THE DIGITAL TWIN TEAM
This job requires advanced technical and personal qualities such as
· Ability to independently design complex high-performance software from scratch
· Persistence in achieving goals and ability to challenge typical solutions
· Personal honesty, reliability, and commitment to the team
REQUIRED SKILLS / EXPERIENCE
· Experience in microservice architecture / orchestration
· Experience with data visualization front-end technologies
· Experience in .Net Core
· Experience with front-end frameworks, ideally vue.js
· Familiarity with UI/UX topics
· Completed technical education in a computer science domain
· Fluent English
WE OFFER YOU TO
· Enjoy the opportunity of developing an innovative and complex product from scratch
· Gain insight into the railway industry
· Work in a small international team with a flat hierarchy
· Competitive salary compliant with Austrian collective agreement and overpayment according to your qualifications
· Top technical equipment for business and private use
· Modern office in the Vienna city center
Get in Touch
Get in Touch
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© 2021 Logicx Research & Development
Address: Czerningasse 10, 1020 Vienna, Austria
Logicx consulting & workflow integration GmbH
Address: Czerningasse 10, 1020 Vienna, Austria
Logicx consulting & workflow integration GmbH