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

  • Sponsor: CCAT: Center for Connected and Automated Transportation

  • Collaborator: Prof. Dan DeLaurentis

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

  • Sponsor: JPL

  • Collaborator: Prof. David Spencer

Scale Aircraft Prototype with Biologically Inspired Topology Optimization


Optimization model of airline crew management

  • We develop an optimization model and numerical/computational methods to solve large scale airline crew management problems.

An AI-based Hybrid Pilot Drowsiness Detection System

  • Sponsor: Purdue Institute for Global Security and Defense Innovation (iGSDI)

  • Collaborator: Xiao Wang (Purdue Statistics)

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

  • Sponsor: Purdue Research Foundation

  • Collaborator: Nan Kong (Purdue BME)

Adaptive Air Traffic Control for Maximizing On-Time Arrival under Uncertain Weather Conditions

  • Sponsor: NASA

A Tool for Coordinated Strategic-to-Tactical Traffic Flow Management

  • Sponsor: NSF

  • Collaborators: Prof. Yan Wan (UNT) and Prof. Sandip Roy (WSU)

Integrated arrival and departure optimization in terminal airspace under uncertainty

  • Sponsor: NASA

FACET as a Collaborative, Open Source UAS Research Platform

  • Sponsor: NASA

  • Collaborators: Dr. Jimmy Krozel (The Innovation Laboratory, Inc.) and Prof. Wei Zhang (OSU)

Stream Management: A Concept for Dynamic Airspace

  • Sponsor: NASA

  • Collaborator: Prof. Steve Landry (PI, Purdue IE)

Design and Evaluation of Conflict-Free Continuous Descent Approach under Normal and Heavy Traffic Conditions

  • Sponsor: FAA

  • Collaborator: Prof. Steve Landry (Purdue IE)

UAS Integration into the National Airspace System

  • Sponsor: NASA

  • Collaborators: Prof. Dan DeLaurentis (PI, Purdue AAE), Prof. Inseok Hwang (Purdue AAE) and Prof. Bill Crossley (Purdue AAE)

Operational Feasibility of Continuous Descent Approach

  • Sponsor: FAA

  • Collaborator: Prof. Dan DeLaurentis (Purdue AAE)

Optimized Traffic into Metroplex

  • Sponsor: NASA

  • Collaborators: Prof. Dan DeLaurentis (PI) and Prof. Steve Landry

Environmental Issues in Traffic Flow Management

  • Sponsor: Purdue Engineering

Multimodal Transportation System

  • Sponsor: Purdue Engineering

  • Collaborator: Prof. Srini Peeta (Purdue CE)

Nationwide Air Traffic Management

  • Sponsor: NASA

Strategic Traffic Flow Models based on Data-Mining and System-Identification Techniques

  • Sponsor: NASA