Research Interests
Autonomy and control
Distributed control and optimization: theory, algorithms, and computation
Optimization for Machine Learning and Artificial Intelligence
Robotics
Cyber-physical systems
Unmanned aerial vehicle systems, air traffic control and air transportation
Intelligent transportation systems
Current Projects
Ride-sharing with advanced air mobility
Autonomous Aerial Cargo Operations at Scale
Sponsor: NASA
Collaborators: Prof. Karen Marais, and collaborators from UT Austin (Ufuk Topcu, Karen Willcox, and John-Paul Clarke), MIT (Hamsa Balakrishnan), and MIT Lincoln Lab (Allison Chang, Matthew Edwards).
The project addresses NASA's mission in Safe and Efficient Growth in Global Operations, with the expected outcome of an algorithmic foundation that will help realize increasingly autonomous and collaborative air traffic management for all classes of airspace and vehicles and support scalable and efficient operations that rapidly adapt to meet changing demands and to respond system disruptions.
Secure and Safe Assured Autonomy
Sponsor: NASA
Collaborators: Profs. Dan DeLaurentis, Inseok Hwang, Shaoshuai Mou, James Goppert, and collaborators from NCAT and GaTech.
The team seeks to develop a novel integration of secure and safe autonomous systems used on unmanned Advanced Air Mobility (AAM) aircraft with the goal of advancing their technical readiness level and be ready for industry to consider using these technologies. The team intends to validate these systems with flight tests of multiple aircraft.
Collaborative Research: III: Medium: Integrating Large-Scale Machine Learning and Edge Computing for Collaborative Autonomous Vehicles
Sponsor: NSF
Collaborators: Prof. Joy Wang (Purdue ECE), Prof. Heng Huang and Prof. Wei Gao (U. of Pitt).
A novel large-scale machine learning and edge computing framework is developed to integrate the emerging key computational techniques, including fast deep learning optimizations, asynchronous federated learning, cross domain deep learning model compression, hierarchical edge computing, and collaborative autonomous aerial and ground vehicles.
Aircraft Characteristics Database
Sponsor: FAA
In this project, we try to build a comprehensive aircraft characteristics database for the FAA, to provide basic aircraft characteristics for common aircraft needed to perform airport design functions.
[Some] Past Projects
Simulation of Dust Particles During Earth Entry
Scale Aircraft Prototype with Biologically Inspired Topology Optimization
Optimization model of airline crew management
An AI-based Hybrid Pilot Drowsiness Detection System
Resilient Operations of Unmanned Aerial Vehicle Systems
Sponsor: Purdue College of Engineering Center for Resilient Infrastructures, Systems, and Processes (CRISP)
Collaborator: Xiao Wang (Purdue Statistics)
Smart Healthcare with Unmanned Aerial Vehicles: A Fog-computing-based CPS Framework
Adaptive Air Traffic Control for Maximizing On-Time Arrival under Uncertain Weather Conditions
A Tool for Coordinated Strategic-to-Tactical Traffic Flow Management
Integrated arrival and departure optimization in terminal airspace under uncertainty
FACET as a Collaborative, Open Source UAS Research Platform
Stream Management: A Concept for Dynamic Airspace
Design and Evaluation of Conflict-Free Continuous Descent Approach under Normal and Heavy Traffic Conditions
UAS Integration into the National Airspace System
Operational Feasibility of Continuous Descent Approach
Optimized Traffic into Metroplex
Environmental Issues in Traffic Flow Management
Multimodal Transportation System
Nationwide Air Traffic Management
Strategic Traffic Flow Models based on Data-Mining and System-Identification Techniques
|