From a broad perspective, my research areas of interest involve working with the various facets and principles of Engineering, Computer Science, and Mathematics. More specifically, my focus includes the areas of Autonomous Systems/Robotics & Sensors, Oceanography & Environmental Science, Data Analysis, Computer Vision, and Applied Machine Learning.
- Robotics and Sensors-based Technology: For this research area, my work involves both the hardware and software domain of engineering. A typical project in this category could involve various tasks starting from the creation of a hardware architecture (viz. a 3D-printed prototype) to deploying such a finished system in the real-world environment so as to analyze its performance on the specific task.
- Oceanography and Environmental Monitoring: This is one of the major application-focused areas that I am interested in so as to learn more about remote and/or hostile environments of various ecosystems. By deploying unmanned systems with sensory integrations, it is possible to procure research data from such environments which can then be analyzed for further study.
- Environmental Data Analysis: Typically, data analysis tasks for environmental applications could involve either using publicly available databases (such as from USGS and EPA repositories), or sample data collected using autonomous/unmanned vehicles. Such data could be analyzed using various kinds of learning algorithms that can help us to learn more about the region, or the level of environmental degradation of an ecosystem.
- Computer Vision: With the help suitable machine learning algorithms, I am interested in learning how computer vision techniques could better be applied for differentiating between various imaging datasets either for environmental applications (viz. recognizing various terrain-types in satellite images), or medical procedures (viz. discriminating between benign and malignant tumor formations).
Please refer to my LinkedIn page for more details.