Research

Research & Professional Background

Research

Research Areas

I work in several computer science domains, including intelligent transportation systems, federated learning, and large-scale machine learning applications.

I am interested in applying following methodologies for solving on-going problems:

• Machine learning and deep learning techniques for intelligent transportation systems, focusing on traffic prediction, incident detection, and flow optimization.
• Federated learning frameworks for privacy-preserving data analysis in multi-institutional collaborations, emphasizing model accuracy and security in transportation systems.
• Spatio-temporal modeling for urban traffic systems using advanced neural architectures, such as graph convolutional networks and recurrent units.
• Optimization techniques for enhancing decision-making in transportation systems, with a focus on integrating AI-driven methodologies.
• Vertical federated learning for improving data sharing in sensitive domains, including effective feature selection strategies for real-time applications.
• Large language models and their applications in prompt and data generation.
• Motion diffusion models and their applications in predictive analytics, leveraging latent dynamics in transportation and mobility data.

Professional Experience

Areas of Expertise

I have extensive experience across multiple software development and academic domains, including enterprise systems design, software architecture, and advanced technical leadership in international environments.

I specialize in:

• Software design and architecture for scalable and maintainable applications, using a diverse technology stack, including C++, C#, ASP.NET Core, Java, and Python.
• Enterprise systems development, focusing on robust solutions for multinational corporations in the US, Europe, and Pakistan.
• Technical leadership in cross-functional teams, driving innovation and ensuring alignment with business objectives in complex software projects.
• Cloud computing solutions, particularly with AWS services such as EC2, EKS, and Elastic Load Balancing, emphasizing infrastructure as code and containerized application deployment.
• Academia and mentorship, with over two decades of experience teaching and researching advanced topics in computer science, including machine learning, federated learning, and intelligent transportation systems.
• Research-driven innovation, contributing to the development of novel algorithms and frameworks for real-world challenges in transportation and AI, with multiple publications in leading IEEE journals.
• Utilizing and contributing to open-source software for community-driven growth and innovation in software engineering and research.