© 2018 Logicx data science R&D



We invest in R&D - you get the fruits


We invest in R&D - you get the fruits



We invest in R&D - you get the fruits





We invest in R&D - you get the fruits

Our story and what drives us

#story #vision #mission #drive
Logicx Data Science R&D is a spin-off of Logicx consulting and workflow integration GmbH. We are a growing team of international experts from all over the world, focused on creating business value with the help of data science tools. We are driven by genuine interest in applied data science research, software system engineering, and use-case focused business value creation.

Our network

We are happy to share that we collaborate with the following research, business, and funding partners:
FFG (Österreichische Forschungsförderungsgesellschaft) is an Austrian research funding agency
VDA is a Visualization and Data Analysis Research Group at the University of Vienna headed by Univ.-Prof.Torsten Möller, PhD
Forome was founded by key members of computational genomics laboratories from Harvard Medical School. Forome association democratizes assess to the genetic analysis of undiagnosed rare diseases
Applied Statistics - a TU Wien data science consultancy spin-off
Logicx Digital Strategies is an innovation strategy consulting company, member of the Logicx Group
MuleSoft is a cloud ESB provider, and one of the prominent promoters of microservice architecture philosophy

Our research topics

Topic I: Rail Switch Predictive Maintenance

The goal of this research is to convert sensor readings into actionable insights, allowing rail infrastructure managers to reduce their maintenance costs and to improve asset availability. It also means that rail operators will be able to increase their punctuality and avoid unpleasant train delays.

Here are a few research challenges of this project:
  • Giving an operator an actionable insight, saying in how many days a switch is likely to fail
  • Show in which switching phase the failure is likely to occur
  • Developing a generic prediction method that will work both for electric and hydraulic switches
  • Providing technicians with visual information that would allow them tracing back and understanding issues
  • Using data from any sensors which are already installed, and going away from the need to install proprietary sensors
  • Development of a fully automatic prediction system
  • Development of a deep-learning system for automatic model parameter tuning for new switch types and new instances
~
Topic II: Optical Object Recognition

The goal of this research project is to find the most efficient methods for generic object detection, classification, and object parameter definition.

Here are some of our research challenges :
  • Creation of a system that can be set up for recognizing a new object type within 1 day
  • Creation of a generic multi-level object hierarchy, allowing recognition not only of objects but of their subparts too
  • Recognition of small and large objects (10-100 times size difference) on the same image
  • 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
  • Keeping recognition speed within a 1 second frame
  • Identification not only of object types but also of object instances
  • Size identification of remote objects (10 to 50 meters away from the camera)
~
Topic III: Machine Learning Based Shopping Optimization Engine

The goal of this research project is to create a system that would learn user's shopping behavior based on his/her activities in multiple online and offline shops (as opposed to single shop loyalty-program-based analysis). The idea is to help consumers finding the products they like at a better price, to recommend them products they would like (as opposed to junk recommendations we often experience), and to help them to optimize their shopping activities.

Here are a few challenges associated with this research 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 (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 service: from data to value

1
You ask us a question
You approach us with a project idea or just with an assumption that the data that your organization has generated might have valuable insights.
#Asking_is_free
2
We check business hypotheses
In turn, we will validate pre-existing hypotheses, explore data trends, as well as generate, propose, and validate new hypotheses on business value of the available data
#Statistical_analysis #Machine_learning_techniques
3
We build a PoC product
After the availability of business relevant insights in the data is confirmed we will build a PoC (proof-of-concept) product: a system that demonstrates the main functions of the envisioned solution. PoCs include productive data processing core design and use case specific workflow definition.
#Database_and_API_design
#UI_prototyping
#Design_of_AI_web_and_mobile_services

4
You test your idea in practice
A prototype is worth a thousand words. You test the solution functionality both in technical and in business terms. At this step we validate user acceptance, quantify KPIs, recalculate the business case using the empirically confirmed numbers, and analyze how organizational processes need to be adjusted in your company in order to ensure successful integration of our solution.
#UX_testing #User_acceptance
#Calculation_of_business_KPIs
#Analysis_of_organizational_processes
5
We build an enterprise-grade system
After you test the prototype and refine specifications, we build for you an enterprise-grade solution with end-to-end use case support and roll it out in your organization.
#Micro-services_architecture
#Load_balancing
#Backup_and_versioning_systems
#Workflow_management_system
#Refined_UI_and_UX

Our USP

Dedicated and passionate team of international experts focused on data science. Learn more in the team section
Solutions with end-to-end use case support: we are backed up with enterprise system engineering experience of our mother company
Benefit from our R&D investment. Learn more in the research section on our website

Stronger together

We are a team of international experts, focused on data science research, software engineering, and application research
Research Team
Georg Doppler-Popovic
Founder & CEO of Logicx group of companies
Georg inspires us with his vision and values. Apart from being the company´s CEO, Georg is also our mentor in multiple areas including requirements engineering, project structuring, information and UX design, as well as software architecture.
Alireza Ghane
Chief Data Scientist
Alireza has a strong academic background as a researcher of Simon Fraser University in Canada and the University of Vienna. His research expertise covers such fields as nonlinear recursive integral equations, rendering algorithms, computer vision, and deep neural networks.
Vipul Khatana
Machine Learning Engineer
Vipul is a machine learning researcher from Indian Institute of Technology Delhi and University of Vienna. Vipul's research fields are Machine Learning, Computer Vision, NLP, and Data Visualization.
Daniel Shulman
Business Development & Application Research
Daniel is responsible for a variety of tasks including application research, business development, recruitment, and in-house consulting. Daniel's research interests include nonlinear mixed-integer optimization, environmental damage valuation methods, and waste management planning.
Data Science Fridge
Predicts a sort of beer you want
This valuable team member takes care of the beer supply in our office. If you are unsure about the type of beverage you want, our fridge will analyze your requirements and will offer you a beer.
Development Team
Shoban Kumar
Full-Stack Guru & Machine Learning Engineer
Shoban leads our full-stack development team, being both a solution architect, a SCRUM master, and a playing captain. Shoban is one of the top-rated Stack-Overflow authors. Shoban's applied research interest span from machine learning and IoT systems to recommendation engines and object recognition.
Anatoly Vasilyev
Full-Stack Developer & Machine Learning Engineer
Anatoly is our multi-talent developer with expertise both in full-stack engineering and in data science. Anatoly's research interests include application of deep learning methods to microbiome genetic analysis, design of bioinformatic pipelines, and consumer data classification algorithms.
Konstantin Ivanov
Full-Stack & GIS Developer
Konstantin is a full stack developer with unique skills and diversified international project experience. Konstantin is the type of a developer who finds an error causing an issue just by looking at a page of code for 10 seconds. Konstantin's research interests include geographic information systems, automated person identification, as well as ML-based image segmentation.
Alexandra Demidova
BPM Consultant & Requirements Engineer
Alexandra is our requirements engineer, supply chain management specialist, and a project manager. Alexandra is result oriented, "pixel perfect" in definitions, and has a proven track record of projects completed in scope, on time, and in budget. The field of Alexandra's research interests in business process management.
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.
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.
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.
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.

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