Trustworthy Intelligent Computing
A trustworthy system does what its legal users expect it to do – and not something else – despite environmental disruption, impairments caused by itself, human users and operators, and potential attacks by hostile parties. Design and implementation of errors must be avoided, eliminated, or somehow tolerated. It is not sufficient to address only some of these dimensions, nor is it sufficient simply to assemble components that are themselves trustworthy. Thus, trustworthiness is multi-facetted and holistic.
Intelligent computing aims to integrate systems to perceive, reason, learn, and act intelligently in the real world. As the real world data and processes are dynamic and stochastic, an intelligent system has to deal with large volumes of data, occasional updates to the data by the users, and unexpected changes in data distributions due to nuisance factors. Therefore, the design of such systems involves hard scalability and robustness constraints that needs to be satisfied. Accordingly, our research areas include but are not limited to the following:
Research Areas
Computer Systems
This research area covers the broad areas of parallel systems, networked systems, embedded systems, and operating systems. The focus is to design and implement hardware components and software systems by considering performance, energy, reliability, availability, safety, and security requirements. Methodologies, architectures, and mechanisms that support modeling, design, implementation, and evaluation of efficient hardware/software systems and applications are our main concern.
Our research concentrates on following topics:
- Dependable Components and SoC (DCSoC), directed by Assoc. Prof. Tolga Ayav:
- SoC and IC Testing
- Model Checker based Testing and Verification
- Fault-tolerant Design
- Software Vulnerability Detection
- Validation, Verification, and Testing
- Software Reliability / Fault Tolerance
- Metrics, Measurements, and Analysis
- Parallel Systems Research Group (PARS), directed by Asst. Prof. Işıl Öz:
- Multicore/GPU architectures
- Performance and reliability analysis of parallel systems
- Parallel software development
- Parallel programming models
Data Science
The field of Data Science covers a wide panorama of research areas focusing on capturing (data acquisition, data entry, signal reception, data extraction), organizing (data warehousing, data cleansing, data staging, data processing, data security, data extraction, data modeling), understanding (data visualization, explanatory, predictive analysis, regression, text mining, qualitative analysis), and applying (business intelligence, decision making) massive data. It continues to evolve as one of the most promising in-demand research axis in fast growing data driven modern world.
Our research concentrates on following topics:
- Data Analytics Research Group (DARG), directed by Assist. Prof. Selma Tekir
- Natural Language Processing, Semantics
- Text Mining
- News Analysis
- Information Warfare
- Data Processing Research Group (DWorld), directed by Assoc. Prof. Belgin Ergenç
- Large Scale Query Optimization
- Federated Query Processing on Linked Data
- Dynamic Itemset Mining and Hiding
- Frequent Pattern Mining on Graph Data
- Recommender Systems
- Information Systems Security Research Group (ISSRG), directed by Assist. Prof. Serap Şahin
- Data Analysis and Information Security
- Applied Crypto Solutions – research, design and implementation
- Dr. Burak Galip Aslan
- Decision Support Systems
- Forecasting and Prediction
- User-Modeling
- Web-Based Learning Systems
- Buket Erşahin
Software Engineering
IZTECH Software Engineering Research Group (SERG) targets to disseminate the software engineering domain knowledge on principles, processes, methods and techniques required to engineer and manage the development and evolution of software systems. We lead the advancement of software practice in Turkey, execute state of the art projects together with industry and bring forth experts and scientists in the field through our graduate programs.
Our research is directed mainly towards the following areas:
- Software Management – Focusing on Quality, Measurement and People-ware
- Enterprise Modelling – Focusing on Process Modelling and Digitization
- Reactive Systems – Analysis and Design Approaches for Micro-service Based Architectures
- Software Reliability – Verification and Validation
- Test Automation
- Software Safety and Security
- Model Driven Software Development
Our research concentrates on following topics:
- Prof. Onur Demirörs
- Software Process Improvement
- Process Models: Methods, Tools, Techniques
- Business Process Management
- Software Quality Management
- Software Measurement
- Software Project Management
- Conceptual Modelling
- Safety, Security and Reliability of Software Systems Group (S2RS2), directed by Assoc. Prof. Tuğkan Tuğlular
- Validation, Verification, and Testing
- Software Reliability
- Model-based Testing
- Testing of Software Product Lines
- Software Safety and Security
- Software Vulnerability Detection
- Model-Driven software Development
- Prof. Fevzi Belli
Computer Vision
Computer Vision (CV) research focuses on analyzing and understanding visual data in order to extract meaningful information contained within still images and video streams. Example outputs of computer vision algorithms include detected object locations and labels (such as faces, cars, pedestrians), a 3D model of the scene generated from images, images containing virtual objects rendered from the camera point-of-view, and pixel-level segmentation of the objects.
Our research concentrates on following topics:
- Computer Vision Research Group (CVRG), directed by Assoc. Prof. Yalın Baştanlar
- 3D Reconstruction from Images
- Visual Object Detection/Classification
- Omnidirectional Vision
- Vision for Traffic Analysis
- Visual Intelligence Research Group (VIRG), directed by Assoc. Prof. Mustafa Özuysal
- Real-time Object Detection and Tracking
- Large Scale Object Identification
- Augmented Reality
- Scene Text Recognition
- Computer Simulation, Intelligence and Graphics for Biometrics (CSIGB) Lab, directed by Assist. Prof. Nesli Erdogmus
- Computer Vision for Forensics
- Biometric Recognition
- Biometric Security
- Realistic Biometric Data Generation
