• Project Management: Led photovoltaic (PV) projects with installations up to 150 kWp, ensuring on-time delivery and seamless coordination of resources, timelines, and stakeholders. • Rooftop PV Design: Utilized PV*SOL to design and optimize rooftop PV systems, improving energy efficiency and maximizing return on investment for clients. • Data & IT Integration: Managed software implementation, data analysis tools, and system integrations to enhance operational efficiency across building management systems and construction projects. • Renewable Energy Strategy: Developed and implemented sustainable energy solutions by integrating PV systems into construction projects, keeping up with industry trends and best practices in renewable energy. • Data-Driven Insights: Oversaw data collection and reporting, leveraging insights to improve project performance and decision-making processes. • Executive Collaboration: Supported the CEO by providing technical expertise on IT, photovoltaics, and data management, while delivering regular project updates. • On-the-Job Learning: Engaged in continuous skill development through hands-on experience and mentorship in project management, data solutions, and renewable energy technologies.

- Developed and implemented AutoML-based image segmentation microservices on the Cloud platform.- Designed and deployed automated image annotation systems, utilizing machine learning techniques for accurate and efficient labeling.- Optimized the image segmentation pipeline by integrating advanced algorithms and techniques, resulting in improved efficiency and accuracy.- Actively researched and implemented state-of-the-art algorithms and methodologies in the field of computer vision to enhance the capabilities of the system.

TUBITAK-1001 project: Video Understanding in Compressed DomainIn this project, under the guidance of PI, we will apply continual learning techniques to compressed videos.

- Implemented image stitching algorithms for pathology images using C++, enhancing the visualization and analysis of large-scale medical imaging data.- Developed custom object detection and classification models using the Tensorflow Object Detection API, enabling accurate and efficient analysis of digital pathology images.- Collaborated with a multidisciplinary team of pathologists, software engineers, and data scientists to define requirements and ensure the successful integration of the developed models into the pathology workflow.

Project leader responsible for creating machine learning techniques to reduce Vodafone customer features for churn prediction. The task was to reduce each customer feature size while achieving the same model accuracy for customer churn.Proposed using graph autoencoders due to their abilities to capture the relationship between the nodes.Github: https://github.com/indritnallbani/Res-V-GAE

TUBITAK-1001 project (119E578): Deep Learning-Based Methods for Analysis of Phase-Contrast Optical Microscopy Time Series Images.Our main goal was to create new machine learning methods to analyze phase-contrast time-series images. During the short time, I was part of the team, I helped with the literature analysis of the topic and proposed some solutions to key problems.

The Laboratory for Computational Ontology (LCO) makes theoretical and practical researches on the formal axiomatic foundations of ontologies related to semantic web, knowledge representation, automated inference, textual entailment, and hybrid computation.

•Participated in research activities on laser application in thin film fabrication.•Researched the effects of different laser power and frequencies on the scribing properties of amorphous Si solar cell.