Faculty Research

Software Engineering is dedicated to the systematic development, operation, and maintenance of high-quality software systems. It addresses the growing complexity of software by improving methodologies for software design, development, testing, and maintenance. Research includes:

• Formal methods for specification, modeling, and verification
• Software validation, quality assurance, and testing
• Human and social aspects in software development teams
• Empirical studies of software practices and evolution
• Emerging domains such as mobile app ecosystems, app store analytics, and AI-assisted development tools
• Designing and improving programming languages and their supporting tools (compilers, solvers, etc.) 

Faculty: Elena Sherman, Jim Buffenbarger, Max Taylor, Zach Hansen

Data Science is an interdisciplinary field focused on extracting knowledge and insights from data using scientific methods, processes, algorithms, and systems. This includes work with structured, unstructured, and streaming data across domains. Key areas include:

• Large-scale data analytics, statistical modeling, and machine learning
• Big Data systems and platforms for high-throughput data processing
• Data visualization for exploratory analysis and communication
• Real-time and predictive analytics for scientific, business, and social applications
• Data Mining: Developing algorithms to discover hidden patterns, anomalies, and trends in vast datasets
• Social Media Mining: Analyzing social platforms (e.g., Twitter, Reddit, Facebook) to understand human behavior, social interactions, and information diffusion

Faculty:

• General Data Science: Steven Cutchin, Amit Jain, Casey Kennington, Edoardo Serra, Francesca Spezzano, Jun Zhuang, Xinyi Zhou, Yu Zhang
• Large-Scale Data Analytics: Amit Jain
• Data Mining: Edoardo Serra, Gaby Dagher, Jun Zhuang, Xinyi Zhou
• Social Media Mining: Francesca Spezzano, Xinyi Zhou

Artificial Intelligence (AI) focuses on creating intelligent systems capable of reasoning, learning, and interacting with their environment. AI research spans theory, algorithms, and practical applications in diverse fields. Core sub-areas include:

• Machine Learning: Designing algorithms that improve performance through data; includes supervised/unsupervised learning, reinforcement learning, deep learning
• Natural Language Processing (NLP): Enabling machines to understand, interpret, and generate human language using linguistic rules and data-driven techniques
• Knowledge Representation and Reasoning: Formalizing how machines represent and reason with information about the world
• Computer Vision and RoboticsRobotics and Perception: Integrating sensing, planning, and action to enable machines to navigate and interact in physical environments
• Ethical and Trustworthy AI: Ensuring fairness, accountability, transparency, and safety in AI systems
• Use-Inspired and Applied AI: Develop AI tools and systems that address real-world societal or industry challenges.

Faculty: Casey Kennington, Jun Zhuang, Tim Andersen, Edoardo Serra, Francesca Spezzano, Xinyi Zhou, Yu Zhang, Sindhu Reddy Kalathur Gopal, Zach Hansen

Cybersecurity and Privacy research aims to protect systems, networks, and data from malicious attacks, unauthorized access, and information leakage. This area includes:

• Network and system security, including intrusion detection and mitigation
• Cryptography, secure communication, and data integrity
• Cyber-Physical System (CPS) security, such as protecting IoT and embedded devices
• Privacy-preserving data analytics and secure multiparty computation
• Policies and frameworks for compliance, risk assessment, and user privacy

Faculty:

• Cybersecurity & CPS Security: Gaby Dagher, Hoda Mehrpouyan, Jyh-Haw Yeh,Sindhu Reddy Kalathur Gopal, Max Taylor 
• Information Security & Privacy: Gaby Dagher, Hoda Mehrpouyan, Edoardo Serra, Jyh-Haw Yeh, Sindhu Reddy Kalathur Gopal, Max Taylor

Human-Centered Computing explores how people interact with technology, with the goal of improving usability, accessibility, and the overall user experience.

Human-Computer Interaction (HCI):

Design and evaluation of interactive systems with a focus on user needs, behavior, and feedback. Includes interface design, user testing, and interactive visualization.

Human-Robot Interaction (HRI):

Study of interactions between humans and autonomous or semi-autonomous robots. Includes collaborative tasks, natural communication, and trust in robotic systems.

Human–AI Interaction and Collaboration (HAI)

Investigates how humans and AI systems can communicate, coordinate, and work together to achieve goals neither could accomplish as effectively alone.

Security for Human-Computer Interaction (SHCI):

Explores the intersection of security, privacy, and human-computer interaction, focusing on designing, evaluating, and deploying secure systems that account for human behavior, usability, trust, and user experience while protecting users from cyber threats and privacy risks. 

Faculty: Sindhu Reddy Kalathur Gopal

Faculty (HCI & HRI & HAI): Jerry Fails, Casey Kennington, Xinyi Zhou, Yu Zhang

This area focuses on techniques for creating visual representations of data, models, and environments. Research includes:

• Scientific visualization of complex simulations and phenomena
• Visual analytics for data exploration and decision support
• Computer graphics, 3D modeling, and rendering
• Augmented and virtual reality applications

Faculty: Steven Cutchin

Systems and Networking research develops efficient, scalable, and reliable computing infrastructure. It addresses challenges in hardware, operating systems, distributed systems, and communication networks.

Networking & Mobile Computing:

Focus on communication protocols, wireless and mobile devices, network security, and heterogeneous networks. Includes edge and cloud computing architectures.

Faculty: (Not specified in original list)

High Performance Computing (HPC):

Designing and optimizing systems capable of massive parallel computation for scientific simulations, analytics, and AI workloads.

Faculty: Steven Cutchin, Amit Jain

Distributed Systems & Cloud Computing:

Explores architectures for scalable computation, data storage, and resource management across multiple machines. Topics include cloud services, containerization, and decentralized systems.

Faculty: Gaby Dagher, Jyh-haw Yeh

Quantum Computing explores computational models based on quantum mechanics. This emerging field promises exponential improvements in solving specific problems. Topics include:

• Quantum algorithms and complexity theory
• Quantum information and error correction
• Quantum simulation for chemistry, cryptography, and optimization
• Integration of quantum computing with classical systems

Faculty: Jun Zhuang, Min Long

Focuses on mathematical modeling and numerical simulation of complex physical, biological, and engineering systems. Research integrates computing with scientific inquiry, including:

• High-fidelity simulations for physical phenomena
• Numerical methods for differential equations and systems modeling
• Computational tools for engineering design and optimization

Faculty: Min Long

Computer Science Education explores how people learn computing and how to teach it effectively. Research covers:

• Curriculum design for K–12 and university-level CS education
• Learning analytics and educational technologies
• Inclusive and accessible pedagogy in computing
• Professional development for educators and instructional design

Faculty: Amit Jain, Tim Andersen