AI and Robotics

The AI & Robotics group at Lehigh CSE department engages in a wide range of research areas such as computer vision, machine learning, deep reinforcement learning, planning and learning, resilient robot swarms, environmental monitoring using automated vehicles, robotic manipulation, large scale knowledge graphs and semantic webs. Within these areas, students and faculty also pursue real-world applications to perception related problems in autonomous vehicles, swarms of robots, robustness of deep learning models. Their research are funded by ONR, NSF, NRL, AFRL, DARPA, and industries such as Qualcomm, FORD.

Machine Learning and Data Mining

Lehigh CSE faculty are passionate about their work in machine learning, data mining, data science, and related areas.  Our efforts encompass foundational research in areas such as deep learning, AI, reinforcement learning, embeddings, tensor learning, and natural language processing as well as applied research of those areas into a wide variety of classification, ranking, planning, recommendation, and prediction tasks in areas such as healthcare data mining, information retrieval, bioinformatics, neuroimaging, simulations, and many more.  Our research is funded by NSF, NIH, DARPA, ONR, AFRL, and NRL as well as grants from industry.

Human Computer Interaction & Social Computing

Research on HCI and Social Computing at Lehigh covers a broad range of issues in the relationships between humans, computing, and society. Examples include information visualization, social media design, human interactions with AI/ML systems, and social privacy practices, to name a few. This work addresses complex, pressing sociotechnical issues, such as harassment detection and prevention, online political engagement, and resistance to technology development.

Systems

The Systems faculty in the Lehigh CSE department engages in a wide range of research topics such as blockchain, databases and key-value stores, distributed & transactional systems, internet of things and cyber-physical systems, ubiquitous system design, wireless sensing for structural health, programming languages. Students and faculty also pursue real-world applications to problems in SCADA intrusion detection, smart transportation, blockchain database, Transactional Memory acceleration for multi-threading software, GPU computation,  programming language extensions for Non-Volatile Memory, low-latency distributed computation enabled by the Remote Direct Memory Access technology, and multi-resource orchestration in next-generation wireless networks.

The Computer Science and Engineering Department has funding from a variety of governmental and corporate sources including the National Science Foundation, National Institute of Health, DARPA, and the Naval Research Laboratory. Please select one of the links below to learn more about our many innovative research groups.