Research labs

Active Perception Group
Yezhou Yang
ASU Active Perception Group is a new American computing research group attending to the research fields of Cognitive Robotics, Computer Vision, and Robot Vision, especially the problems of exploring visual primitives in human action understanding from visual input, robustly grounding them by natural language as well as high-level reasoning over the primitives for intelligent robots. The group’s research focused on solutions to visual learning, which significantly reduces the time to program intelligent agents. These solutions involve Computer Vision, Deep Learning, and AI algorithms to interpret peoples’ actions and the scene’s geometry. The research draws on the strengths of the symbolic approach (classical AI), connectionism (deep learning), and dynamicism (control theory).

Arizona Center for Integrative Modeling and Simulation
Hessam S. Sarjoughian
Research activities span modeling theories/methodologies, simulation algorithms/techniques, modeling and simulation tool development, and software architecture/design. In recent years, research has focused on poly-formalism modeling, meta-modeling, and cloud-based simulation with applications to semiconductor supply-chain enterprises, human/landscape processes, and cyber-physical systems. Research concepts, theories, and methods are developed and when successful they are introduced into the DEVS-Suite Simulator and the Component-based System Modeling and Simulator.

Automated Reasoning Group
Joohyung Lee
The Automated Reasoning Group is interested in designing and building intelligent systems, which can perform automated reasoning based on the knowledge represented in a formal language, thereby intelligently handling open-ended tasks by *thinking*. Towards this end, the group has been working on knowledge representation and reasoning, computational logic, logic programming, commonsense reasoning, reasoning under uncertainty, ontology modeling, cognitive robotics, security and question answering.

Autonomous Agents and Intelligent Robotics Lab (AAIR-Lab)
Siddharth Srivastava
Sequential decision making under uncertainty, integrated task and motion planning, robotic mobile manipulation, generalized planning, knowledge representation, probabilistic programming, probabilistic inference and machine learning.

Blockchain Research Lab
Dragan Boscovic
The ASU Blockchain Research Lab’s mission is to advance the research and development of blockchain-based technologies for use in Business, Finance, Economics, Mathematics, Computer Science, and all other areas of potential impact.

Center for Cognitive Ubiquitous Computing (CUbiC)
Sethuraman Panchanathan, Troy McDaniel, Jay Klein
The purpose of the Center for Cognitive Ubiquitous Computing is to make fundamental contributions in the areas of human-centered multimedia and ubiquitous computing through the design, development, evaluation and deployment of assistive, rehabilitative and healthcare technologies that augment the sensation, perception, and cognition of humans to a level above their innate abilities.

Center for Intelligent, Distributed Embedded Systems and Applications (IDEAS)
The Intelligent, Distributed, Embedded Applications and Systems (IDEAS) Center is an NSF IUCRC that addresses a broad range of industry-relevant, application-driven projects. Their work involves co-designing smart hardware and software that sense, collect, compute, communicate, and control the world around us while targeting extreme energy efficiencies and high performance.

Cognitive Information Processing Systems (CIPS) Lab
Hasan Davulcu
Information extraction, linking and complex pattern discovery from semi-structured and unstructured data sources.

COmplex Data Reasoning and Analysis Lab (CoRAL)
Vivek Gupta
The Complex Data Reasoning and Analysis Lab (CoRAL) focuses on advancing AI systems capable of reasoning over complex and structured data. Our research integrates natural language processing, computer vision, and machine learning to develop AI that effectively understands and interprets structured formats like tables, charts, and maps. We explore hybrid LLM-SQL approaches, symbolic query generation, and multi-table retrieval to enhance AI’s reasoning capabilities. Additionally, we investigate dynamic data adaptation and hierarchical structures to improve reliability and interpretability. Our goal is to develop robust AI systems with real-world applications in healthcare, finance, and e-commerce. CoRAL is a key component of ASU’s Natural Language Processing (NLP) research community.

Data Mining and Machine Learning Lab (DMML)
Huan Liu
Leading novel and creative research through the application of data mining, machine learning, social computing, and artificial intelligence.

Data Systems Lab (DataSys)
Mohamed Sarwat
The mission of DataSys is growing data systems research through education, innovation and discovery as well as bridging the gap between the data systems community and other scientific and business domains that may benefit from data management solutions. Members of the Data Systems lab design experimental data management systems that enable emerging applications, involve the human in the system design, process non-traditional data types, or support emerging software platforms or hardware paradigms.

Emerging Device and Architecture Group
Shimeng Yu
Emerging devices and circuits beyond CMOS; New computing paradigms beyond Boolean logic.

EMITLAB
K. Selcuk Candan and Maria Luisa Sapino
Data management and analysis, big data, multimedia.

Energy-Efficient Computer Architecture Lab
Carole-Jean Wu
Energy-efficient architecture, shared resource management for heterogeneous computing, high-performance cache design.

Geometry Systems Laboratory
Yalin Wang
Development of novel geometry analysis systems with applications on brain imaging and general imaging analysis.

Health Engineering Applications Lab (HEAL)
John Femiani, Ashraf Gaffar, Tom Sugar, Kevin Gary, Angela Sodemann
Mobile, web, gaming, and systems for clinical applications.

IMPACT Lab
Sandeep K. S. Gupta, Georgios Varsamopoulos
Safe, secure, and sustainable mobile and cyber-physical computing and networking.

Intelligent Interactive Instructional Systems
Kurt VanLehn
Finding methods for combing human and machine intelligence to increase student learning.

International Logistics and Productivity Improvement Laboratory
Rene Villalobes
The International Logistics and Productivity Improvement Laboratory performs industry-oriented research within three main areas: supply chain and logistics; quality and productivity; and marketing and strategic planning.

Knowledge Representation and BioAI lab
Chitta Baral
Representation and reasoning with knowledge, natural language understanding and applications to molecular biology.

Lab V2
Paulo Shakarian
Applying scientific ideas such as formal logic and causality to the practical problems of machine learning operations. Specific domain areas of focus include sustainability, healthcare, supply chain, analysis, and agriculture technology.

Make Programming Simple Lab
Aviral Shrivastava
The mission of Make Programming Simple Lab is to investigate novel architectural, compiler, runtime, and operating system mechanisms to make the task of programming ambitious applications easier on complex, distributed, and heterogeneous computing platforms. We publish in top-tier venues like Embedded Systems Week (ESWEEK), Design Automation Conference (DAC), Machine Learning and Systems (MLSys), Architectures Systems Programming Languages and Operating Systems (ASPLOS), IEEE Transactions on Reliability (TR), ACM Transactions in Cyber-Physical Systems (ACM TCPS), ACM Transactions on Embedded Systems (ACM TECS) etc.

Mobile Ad hoc ReSearch (MARS)
Violet R. Syrotiuk
Research on mobile ad hoc networks (MANETs) including wireless sensor networks (WSNs), delay tolerant networks (DTNs), vehicular ad hoc networks (VANETs) among others. Interests in medium access control protocols and higher layer protocols, cross-layer design and optimization, applying techniques from combinatorics, and designed experiments.

ONRL (Optimization and Networking Research Laboratory)
Guoliang Xue
ONRL is home to many dedicated graduate students and undergraduate students, conducting high quality research in many areas, including human-centric computing, crowdsourcing to smart phones, privacy and security, robustness and survivability; and optimal resource allocation.

Parallel Systems and Computing Laboratory (PSCLab)
Fengbo Ren
We focus on bringing energy efficiency and data/signal intelligence into a wide spectrum of today’s computing infrastructures, from data center/edge node server systems to wearable/IoT devices. We aspire to provide real-time and energy-efficient computing solutions for data analytics and information processing.

Research Laboratory for Virtualized Infrastructure, Systems, and Applications (VISA)
Ming Zhao
Cloud and edge computing, machine learning and big data systems, high-performance computing, operating and storage systems

Secure Networking And Computing (SNAC)
Dijiang Huang
Research focus on computer and network security, mobile ad hoc networks, network virtualization, and mobile cloud computing.

Security Engineering for Future Computing (SEFCOM)
Gail-Joon Ahn
The mission of SEFCOM is to make a significant impact on our society through innovative research projects, assurable development, and hands-on training programs in the areas of cyberspace security and defense. Current research interests include identity management and access control, formal models for computer security, network and distributed systems security including mobile and cloud computing, vulnerability and risk assessment and cybercrime analysis among others.

Self-Organizing Particle Systems (SOPS) Lab
Andrea W. Richa
Investigating the theoretical and algorithmic underpinnings of programmable matter, largely through the lens of distributed computing and randomized algorithms. Though collaborations, we also develop simple robotic systems through which we realize and test our algorithms.

Semantic Computing and Big Data Lab
Srividya Bansal
Semantic computing, big data integration, web service description, discovery, and composition, outcome-based instruction design in STEM, software engineering education.

Visual Analysis and Data Exploration Research (VADER)
Ross Maciejewski
Visual analytics, information visualization, health informatics, crime analysis, non-photorealistic rendering.

Visual Representation and Processing Laboratory
Baoxin Li
We perform research related to computer vision, multimedia processing, statistical methods in visual computing, and assistive technologies.

Yochan Group
Subbarao Kambhampati
Automated Planning, Scheduling; Integrated AI systems, Human-Robot Interaction Information Integration, Social Media Analysis.