The Virtual Lab for Big Data and Computing is committed to exploring scalable computing technologies and advanced data systems that empower data-driven decision-making in today’s digital world. The works under this lab focuses on developing and optimizing frameworks for managing, processing, and analyzing vast amounts of data across distributed environments. With research spanning big data technology, cloud and edge computing, IoT, and distributed systems, the lab addresses key challenges in handling large-scale data with speed, security, and efficiency.
This lab provides a dynamic environment where students and researchers engage in projects that challenge conventional approaches to data storage, processing, and connectivity. From exploring the Internet of Things (IoT) to enhancing big data analytics, the lab cultivates expertise and fosters a practical understanding of the complex ecosystems within big data and computing. The lab prepares students to be leaders in fields where data is not just generated but harnessed to its fullest potential.
Research Areas:
- Distributed Systems: Developing systems that distribute data and computing tasks across multiple machines to improve scalability, reliability, and performance.
- Big Data Technology: Exploring tools and techniques for storing, processing, and analyzing massive datasets to extract meaningful insights.
- Internet of Things (IoT): Integrating data from connected devices to enable smart environments and facilitate real-time data-driven applications.
- Cloud Computing: Leveraging cloud-based platforms for flexible, on-demand data storage and computational power, supporting a wide range of applications.
- Edge Systems: Enhancing real-time data processing by bringing computation closer to data sources, reducing latency and supporting responsive applications.