The School’s six research clusters create a foundation for interdisciplinary research, bringing together expertise in computing, health, and engineering. These clusters closely align with Montclair State University’s broader initiatives in Engineering, Computing, and Applied Data Science, especially in areas like AI, cybersecurity, data engineering, and health. The research clusters at SoC offer students access to a wealth of expertise and state-of-the-art resources, fostering a vibrant, interdisciplinary environment.
Research Clusters
The SoC research clusters present a framework of innovation partnerships focused on interdisciplinary research and collaboration in health, engineering, and computing. This framework strongly aligns with Montclair State University’s initiatives in Engineering, Computing, and Applied Data Science, particularly in the areas of AI, cybersecurity, data engineering, and interdisciplinary applications in health and resilient systems. Montclair’s approach mirrors the interdisciplinary, innovation-driven model in the SoC research framework presented below, integrating computing, engineering, and societal impact.
Core Research Areas
Algorithms, Networks, and Complex Systems (ANCS)
ANCS aims to establish a strong foundation for scalable computing systems, network architectures, and the study of complex adaptive systems. As computing continues to evolve, challenges related to efficiency, scalability, and interconnected systems are becoming increasingly significant.
Faculty Involved
AI Engineered Systems (AIES)
Artificial intelligence (AI) is rapidly reshaping the landscape of modern computing, offering new opportunities for intelligent automation, decision-making, and system adaptability. The AIES research cluster at Montclair State University focuses on harnessing AI to develop innovative, high-performance systems that are capable of autonomously improving and responding to dynamic challenges. By integrating AI into the core architecture of computing systems, we aim to create self-optimizing, data-driven frameworks that can learn, adapt, and scale as needed to address complex, real-world problems.
Faculty Involved
Neuro-physiological Computational Learning (NPCL)
The Neuro-Physiological Computational Learning (NPCL) Cluster is an interdisciplinary research initiative situated at the intersection of neuroscience, physiology, artificial intelligence, computational modeling, and reinforcement learning. By integrating these fields, the cluster aims to deepen our understanding of cognitive processes and improve intelligent systems, particularly for learners with special needs in STEM education, crisis decision-making, and real-world applications such as defense, military operations, cybersecurity, and human errors in computing.
Faculty Involved
Interdisciplinary Data Engineering and Science (IDES)
Data science has emerged as a transformative force in today’s research landscape, impacting nearly every field from healthcare to cybersecurity. The IDES cluster seeks to push the boundaries of data engineering and applied data science by fostering collaboration across disciplines and enabling the creation of data-driven solutions for complex, real-world problems. The research agenda can be organized around three key pillars: theoretical foundations, methodological advancements, and industry standards.
Faculty Involved
Software Engineering Reliability and Privacy (SWRP)
As software systems become more complex, ubiquitous, and interconnected across various domains—including finance, healthcare, transportation, and critical infrastructure—the need for reliability and privacy has never been more urgent. The Software Engineering, Reliability, and Privacy (SWRP) Cluster is dedicated to advancing research in secure and resilient software engineering practices. This cluster brings together interdisciplinary expertise to address fundamental challenges in building dependable, privacy-conscious, and secure software systems capable of withstanding evolving cybersecurity threats and operational disruptions.
Faculty Involved
Cyber-physical Resilient Systems (CPRS)
The CPRS cluster focuses on building secure and resilient systems for the next generation of interconnected technologies. Cyber-physical systems (CPS) combine physical components (like sensors, actuators, and machinery) with digital elements (such as software, networks, and AI) to create interconnected systems that operate in critical sectors like energy, healthcare, transportation, and defense. However, the interconnected nature of CPS introduces vulnerabilities that must be addressed through resilient design, cybersecurity, and real-time response mechanisms. This cluster’s research aims to solve problems specific to IoT, smart infrastructure, autonomous systems, and other critical infrastructures, ensuring that these systems can continue to function even under extreme conditions.
Faculty Involved
This framework creates a strong foundation for developing SoC research that is both forward-thinking and deeply aligned with the cutting-edge research happening at the SoC. The six faculty research clusters offer an excellent structure to support diverse and specialized research areas including future faculty hiring initiatives.
By aligning with these dynamic research clusters, the SoC research will not only address pressing societal challenges but also foster interdisciplinary collaboration among fields like AI, data science, software engineering, cybersecurity and systems engineering. It would be a great way to provide research leadership equipped to tackle the multifaceted challenges of today’s technological landscape.
Recent Grants
- CAREER: Human Factors and Task Scheduling for Multi-Human Multi-Robot Collaborative Manufacturing in Industry 5.0 Contexts
- Grantor (Organization the Grant Came from): National Science Foundation
- PI: Weitian Wang
- Amount: $500,000
- Grant Duration: 2024-2029
- I-Corps: Translation Potential of a Multimodal, Human-Robot Teaching-Learning- Collaboration Framework to Advance Manufacturing Flexibility and Productivity, National Science Foundation
- Grantor: National Science Foundation
- PI: Weitian Wang
- Amount: $50,000
- Grant Duration: 2024-2025
- RET-MRI: Building Robotics and AI Capacities for Pre-University Communities
- Grantor: National Science Foundation
- PI: Weitian Wang
- Co-PI: Michelle Zhu and Amy Tuininga
- Amount: $50,000
- Grant Duration: 2024-2025
- ERI: High-performance Human-robot Collaborative Manufacturing Enabled by Integrated Multimodal Teaching, Learning, Prediction and Interaction
- Grantor: National Science Foundation
- PI: Weitian Wang
- Amount: $200,000
- Grant Duration: 2022-2024
- MRI: Acquisition of a Multimodal Collaborative Robot System (MCROS) to Support Cross-Disciplinary Human-Centered Research and Education at Montclair State University
- Grantor: National Science Foundation
- PI: Weitian Wang
- Co-PI: Michelle Zhu and Amy Tuininga
- Amount: $289,737
- Grant Duration: 2021-2024
- RI: Small: DaRE: Detection and Recognition of Euphemisms
- Grantor: National Science Foundation
- PI: Anna Feldman
- Co-PI: Jing Peng
- Amount: $564,126
- Grant Duration: 2023-2025
- REU SITE: Enhancing Undergraduate Research Experiences in Cybersecurity and Privacy-Enhanced Technologies
- Grantor: National Science Foundation
- PI: Bharath Kumar Samanthula
- Co-PI: Boxiang Dong
- Amount: $395,470
- Grant Duration: 2021-2024
- ERI: An Emotion-Based Robotic Behavior Optimization System for Comfortable and Friendly Human-Robot Collaboration
- Grantor: National Science Foundation
- PI: Rui Li
- Amount: $200,000
- Grant Duration: 2023-2025
- Quantifying the role of vegetation cover on berm-dune geometry and sedimentation patterns in Long Branch, New Jersey
- Grantor: NJ Sea Grant Consortium
- PI: Jorge Lorenzo Trueba
- Co-PI: Aparna Varde and Danlin Yu
- Amount: $139,999
- Grant Duration: 2023-2025
- Northern NJ – Montclair Computer Science Education Hub
- Grantor: NJ Department of Education
- PI: Katherine Herbert
- Amount: $280,000
- Grant Duration: 2025-2026
- Assessing Early Cardiovascular Effects: Is There a Time Too Early for Spinal Stimulation in Acute Spinal Cord Injury?
- Grantor: Kessler Foundation (Prime Sponsor: NJ Department of Health)
- PI: Haiyan Su
- Amount:
- Grant Duration: 2024-2025