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Farokh BastaniView profile

Professor

• AI-Based Automated Software Synthesis
• Embedded Real-Time Systems
• Formal Methods and Program Transformation
• +4 more

Farokh Bastani is the Excellence in Education Chair and Professor of Computer Science at the University of Texas at Dallas (UT Dallas). He serves as Director of the UT Dallas National Science Foundation Net-Centric Software & Systems Industry/University Cooperative Research Center. His academic journey includes roles at the University of Houston (1980–1997) and visiting positions at Michigan State University and the University of California, Berkeley. Bastani holds a Ph.D. in Computer Science from UC Berkeley (1980), an M.S. from the same institution (1978), and a B.Tech. in Electrical Engineering from the Indian Institute of Technology, Bombay (1977). His research focuses on AI-driven software synthesis, embedded real-time systems, formal methods, high-assurance decentralized systems, and tele-collaborative systems. He has led projects on fault-tolerant distributed systems, software reliability, and security assurance. His work emphasizes modular parallel programming and telecommunication system design. Bastani’s publications span topics like P2P data grids, robotic swarm systems, and real-time anomaly detection. He has received multiple IEEE awards, including the Meritorious Service Certificate (2001) and Golden Core Award (1996). He holds editorial roles in journals like the IEEE Transactions on Knowledge and Data Engineering and Wiley’s Encyclopedia of Computer Science. He has directed significant grants, including the $207,250 High-Assurance NCCS project (DoD, 2007–2008) and NSF-funded initiatives. His lab, the Embedded Software Center, develops resilient systems for hostile environments. Collaborations with industry partners like Boeing and Lockheed Martin underscore his applied research impact.

Jorge CobbView profile

Associate Professor

• Network Protocols
• Quality of Service in Networks
• Mobile Computing
• +6 more

Jorge Cobb is an Associate Professor in the Department of Computer Science at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. His research focuses on network protocols, quality of service (QoS), mobile computing, and distributed systems. He holds a Ph.D. from the University of Texas at Austin (1996), an M.A. (1989), and a B.S. (1987) from the University of Texas at El Paso. His research interests include design and implementation of network protocols, QoS in high-speed networks, mobile computing, and distributed systems. He has published extensively on topics like sensor networks, routing algorithms, and network stabilization. Recent work emphasizes fault-tolerant systems, barrier coverage in sensor networks, and SDN-based traffic engineering. Key awards include AT&T scholarships and fellowships from UT Austin. He has led projects such as CHAMPS (National Science Foundation) and contributed to optical network research. His teaching spans computer networks, database systems, and distributed systems at both undergraduate and graduate levels.

Jeong-Hyon HwangView profile

Associate Professor

• Databases
• Distributed Systems
• Graph Database Systems
• +5 more

Jeong-Hyon Hwang is an Associate Professor at the University at Albany, State University of New York , affiliated with the College of Nanotechnology, Science, and Engineering and the Department of Computer Science . As Director of the Data Management Systems (DMS) Lab, he focuses on scalable graph databases, trajectory data compression, and real-time stream processing. His work on the G* graph database system, funded by the NSF CAREER award IIS-1149372 , enables efficient storage and analysis of distributed dynamic graphs. PhD in Computer Science, Brown University (2008) MS in Computer Science, Brown University (2003) MS in Computer Science and Engineering, Korea University (2000) BS in Computer Science and Engineering and Mathematics Education, Korea University (1998, 1994) Dr. Hwang’s research spans Databases and Distributed Systems , with specific emphasis on graph database systems , trajectory data management , and fault-tolerant stream processing . His publications highlight advancements in Internet-scale data management , real-time analytics , and load balancing for dynamic environments. The 15 most recent publications reflect trends in graph algorithms , stream processing reliability , and trajectory compression . Key subfields include distributed graph storage , centrality estimation , non-relational stream models , and high-availability solutions for wide-area networks. Scientific Awards : NSF CAREER award (2012) Best Poster Award, IEEE ICDE (2014) Best Poster Runners-Up, ACM SIGSPATIAL GIS (2010) IBM Open Collaborative Faculty Award (2010) National Scholarship, South Korea (2001-2005) New Software Award, South Korea (2001) Dr. Hwang leads the DMS Lab , developing open-source systems like G* for graph storage and querying. He has authored patents, co-authored Korean translations of technical books, and contributed to foundational research in high-availability algorithms and stream processing engines .

Juan Carlos AugustoView profile

Professor

• Intelligent Environments
• Ambient Intelligence
• Sensor-based Computing
• +5 more

Professor Juan Carlos Augusto is a Professor of Computer Science and Head of the Research Group on Development of Intelligent Environments at Middlesex University, UK. His research focuses on sensor-based computing, ambient intelligence, smart environments, and context-aware systems. He has led numerous international conferences, including roles as General Chair for IE'25 and IE'24. He is Editor-in-Chief of multiple journals, including the Journal on Smart Cities and Society and the Journal on Ambient Intelligence and Smart Environments. With over two decades of teaching experience, he has taught undergraduate and postgraduate courses in artificial intelligence, formal methods, and software engineering. He has supervised a substantial number of PhD students and has been an external examiner for European PhD defenses. His work emphasizes user-centric design and co-creation of smart technologies for people with special needs, such as those with Down’s syndrome or dementia. He also collaborates with industry to innovate products and processes in healthcare, education, and urban planning.

Bernard IssaView profile

Assistant Professor

• Second Language Acquisition
• Attention Mechanisms
• Working Memory
• +4 more

Bernard Issa is an Assistant Professor of Spanish Linguistics in the Department of World Languages and Cultures at the University of Tennessee. He serves as First-Year Spanish Language Program Director and Language Training Coordinator for Graduate Students. His PhD in Second Language Acquisition was earned at the University of Illinois at Chicago, supported by National Science Foundation and Language Learning dissertation grants. Dr. Issa's research uses eye-tracking to investigate how individual differences (motivation, attention, working memory, L2 usage) interact with instructional interventions and learning contexts to impact second language grammar processing and acquisition. His work bridges cognitive psychology and language pedagogy, with special focus on study abroad programs and technology-mediated learning. His publication record demonstrates consistent methodological innovation in SLA research, particularly through eye-tracking and multisite replications. Recent work (2022-2025) shows expanded focus on technology-mediated TBLT, heritage bilingualism, ecological validity in assessment, and quantitative approaches to study abroad research. As program director, he oversees curriculum development for Spanish language training. His grant-supported dissertation examined attentional allocation during grammar learning, establishing foundational work for his ongoing research into cognitive aspects of L2 acquisition.

Haopeng ZhangView profile

Assistant Professor

• Natural Language Processing
• Generative AI
• AI4Science (Healthcare, Linguistics, Sensing)
• +3 more

Haopeng Zhang is an Assistant Professor in the Department of Information and Computer Sciences at the University of Hawaii at Mānoa, leading the ALOHA Lab. He holds a Ph.D. from the University of California, Davis (advised by Dr. Jiawei Zhang), dual M.S. degrees from Georgia Tech (Electrical Engineering and Computational Science), and a B.S. from UIUC (Electrical Engineering). His research focuses on NLP, Generative AI, AI4Science, and Graph Mining, emphasizing biomedical applications, multimodal reasoning, and workflow generation. Recent achievements include organizing workshops at EMNLP and ACL, receiving grants from NSF and OpenAI, and developing tools like StrucSum and MermaidFlow. Education: Ph.D., Computer Science, UC Davis (2024) M.S., Electrical Engineering & Computational Science, Georgia Tech B.S., Electrical Engineering, UIUC Research interests span structural summarization, LLM applications in healthcare and linguistics, and graph-based NLP systems. His work bridges theoretical advancements with practical tools, including the ALOHA Lab's contributions to reliable summarization systems and multimodal benchmarks. Notable contributions include the DomainSum benchmark and Wi-Chat wireless sensing framework. Key awards include UH travel grants, OpenAI credits, and NSF computing allocations. He actively serves on conference committees (ACL, KDD) and reviews for top journals (ACM TKDD, IEEE transactions). Teaching responsibilities include Advanced AI and Machine Learning courses at UH Mānoa. Lab activities focus on AI-driven solutions for scientific domains, with ongoing projects in biomedical event extraction and low-resource language support.

• Software Defined Radio
• AI/ML for Wireless Communications
• Cyber Security
• +3 more

Ruolin Zhou is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Massachusetts Dartmouth, part of the College of Engineering. She joined UMass Dartmouth in 2018 after serving as a tenured Associate Professor at Western New England University from 2012 to 2018. Her research focuses on software-defined radio (SDR), AI/ML-driven wireless communications, spectrum sensing, cyber & electromagnetic spectrum security, and hardware security. Her work has been supported by grants from NSF, ONR, AFRL, ARL, and industry partners like Lockheed Martin. Dr. Zhou holds a PhD in Engineering from Wright State University (2012), an MS in Electrical Engineering (2007), and a BS in Electrical Engineering from Dalian Jiaotong University (2003). She teaches courses including Foundations of Cybersecurity, Digital Logic Design, and Software-Defined Radio. Her research has led to innovations in FPGA-accelerated deep learning architectures, real-time spectrum monitoring, and secure communication systems. Her contributions have been recognized with awards including the 2024 IEEE Region 1 Outstanding Teaching Award, ONR Summer Faculty Research Fellowships (2022-2023), and Best Demo Awards at GLOBECOM 2010. She actively serves in IEEE roles, including Vice President for Technical Activities within the IEEE Reliability Society (2025) and steering committee memberships in IEEE Future Networks and IoT Technical Communities.

Kenneth RomitoView profile

Assistant Professor

• Nursing Practice
• Infection Control
• Sterility Assurance
• +3 more

MAJ Kenneth Romito is an Assistant Professor in the Adult Gerontology Clinical Nurse Specialist Program at the Daniel K. Inouye Graduate School of Nursing, Uniformed Services University of the Health Sciences. He holds advanced certifications including APRN, AGCNS-BC, CNOR, and CSSM. His military career includes roles as a perioperative nurse, Clinical Nurse Specialist, and Infection Control Consultant at Walter Reed Army Medical Center, Tripler Army Medical Center, and other facilities. He earned his DNP from USUHS in 2019 and has been recognized as APRN of the Year (2022) and received the Board of Regents Award for clinical excellence. Education: Doctor of Nursing Practice (2019), USUHS Master of Science in Nursing (2014), Jacksonville University Bachelor of Science in Nursing (2008), University of Akron Research focuses on high-level disinfection, surgical site infection prevention, and pressure injury prevention. Key projects include optimizing sterilization workflows, improving OR efficiency via Lean Six Sigma, and advancing evidence-based infection control practices. His work has been presented at major conferences like AORN and recognized through awards like the 2019 DNP Project First Place at USUHS Research Days. Awards: Meritorious Service Medal Humanitarian Service Medal Army Commendation Medal APRN of the Year (2022) Leadership roles include Officer in Charge of Operating Room Specialist Course (2020–2022) and Deputy Commander for Surgical Services at Tripler AMC. He has collaborated on grants such as the Geneva Foundation-funded study on hydrocolloid barrier effectiveness (2022). Labs/Teams: Active in the Center for Nursing Science and Clinical Inquiry, MMESO Pacific, and interdisciplinary teams focusing on sterilization protocols and surgical safety.

• Laser Spectroscopy
• Cultural Heritage Science
• Material Science
• +3 more

Olga Kokkinaki is a Post-doctoral researcher at the Institute of Electronic Structure and Laser (IESL) of the Foundation for Research and Technology - Hellas (FORTH) since 2009, specializing in laser diagnostics for industrial, environmental, and cultural heritage applications. Her academic qualifications include: PhD in Physical Chemistry, University of Crete, Greece (2009) MSc in Optoelectronics-Microelectronics, University of Crete, Greece (2004) BSc in Physics, University of Crete, Greece (2002) Her research centers on advanced laser spectroscopy methodologies, with primary expertise in Laser-Induced Breakdown Spectroscopy (LIBS) and Laser-Induced Fluorescence (LIF) for material analysis. She develops optimization protocols for industrial environmental monitoring and designs LIF schemes to evaluate laser cleaning processes on artworks. Additional focus areas include Pump-Probe laser techniques, remote sensing, laser ablation mechanisms in molecular solids, and comparative LIBS-Mass Spectrometry studies for cultural heritage conservation. Publication analysis reveals consistent specialization in heritage science applications, particularly in developing reliable identification protocols for historical materials through time-resolved spectroscopic techniques. Her work bridges analytical chemistry, material science, and conservation practice with strong industrial applicability. No scientific awards or honors are documented in the provided materials. Information regarding student supervision or research grant leadership is not specified in the source text. Dr. Kokkinaki operates within IESL-FORTH's Diagnostic Methodologies and Instrumentation research group, contributing to photonics-based heritage science initiatives through collaborative projects focused on laser-material interaction analysis and conservation technology development.

Ross BuckView profile

Professor

• Nonverbal Communication
• Emotional Expression
• Social-Ecological Systems
• +4 more

Ross Buck is a Professor of Communication and Psychology at the University of Connecticut, affiliated with the College of Liberal Arts and Sciences and the Department of Communication. His research focuses on nonverbal communication, emotional expression, and their roles in human behavior, social structure, and adaptation. He has contributed extensively to understanding the evolution of emotional communication, cognitive-emotional interactions, and cross-cultural variations in emotional expression. Dr. Buck holds a Ph.D. from the University of Pittsburgh (1970). His work integrates biological, psychological, and social perspectives, exemplified in his books such as Human Motivation and Emotion and Emotion: A Biosocial Synthesis . He has been funded by prestigious agencies like the National Science Foundation and the National Institute of Mental Health. Research interests include empathy measurement, technology-mediated emotion, and the impact of spatial distance on emotional communication. He leads the UConn Communication Technology, Emotion, and Culture Lab and teaches courses like Motivation and Emotion, Nonverbal Communication, and graduate-level seminars. His recent projects explore brain mechanisms of empathy and cultural variations in primary social emotions. Notable grants include funding from the National Institute of Mental Health, Harry Frank Guggenheim Foundation, Russell Sage Foundation, and National Science Foundation. He blogs for Psychology Today and has been featured in ABC’s 20/20. His articles address topics like drone system trustworthiness, password manager adoption, and crisis communication in corporate reputations.

• Engineering Education
• Student Academic Success
• Educational Technology
• +3 more

Farshid Marbouti is an Assistant Professor in General Engineering within the Charles W. Davidson College of Engineering at San José State University (SJSU). He serves as former co-chair for the Senate Student Success Committee and focuses on engineering education research, particularly student academic success and educational technology. His work includes developing early warning systems for at-risk students and improving teaching methodologies through grants like NSF-funded RHYTHM and SJSU's Engineering Student Success Pathways initiatives. Education: Ph.D. in Engineering Education, Purdue University (2016) M.A. in Educational Technology and Learning Design, Simon Fraser University (2012) M.S. in Computer Engineering (AI), Amirkabir University of Technology (2005) B.S. in Computer Engineering (Software), Sharif University of Technology (2002) Research Interests: Predictive modeling for student success Active learning pedagogies Engineering design feedback mechanisms Online discussion forum analytics Technology-enhanced learning environments Grants: NSF IUSE RHYTHM Project ($78k SJSU share, $300k total) SJSU College of Engineering Endowment Fund ($56k) NSF-funded design feedback research ($300k as postdoc/GRA) Labs/Teams: Leads applied computing for behavioral/social sciences initiatives, collaborating across institutions on interdisciplinary education projects.

Lynne LafaveView profile

Professor

• Nutrition
• Child Health
• Healthy Eating Environments
• +3 more

Dr. Lynne Lafave is a Professor in the Department of Health and Physical Education at Mount Royal University. Her academic work focuses on improving nutrition and physical activity environments in early childhood settings through evidence-based research and community engagement. She developed the CHEERS tool for evaluating child care environments and led the Garden2Plate initiative to enhance food literacy among disadvantaged preschoolers. PhD in Nutritional Sciences, University of Manitoba Bachelor of Human Ecology, University of Manitoba Her research priorities include healthy eating behaviors, physical literacy promotion, and organizational change strategies in early education. Key projects involve collaboration with Alberta Health Services and provincial ministries to create scalable public health interventions. Dr. Lafave has presented at international conferences on topics ranging from pandemic impacts on child care to professional development for early childhood educators. Dr. Lafave’s work emphasizes community partnerships, having served on provincial advisory committees for dietary guidelines and contributed to educational resources for teachers. Her 2019 Mount Royal University Community Engagement Award recognizes this impactful community-focused scholarship. Awards: 2019 Mount Royal University Community Engagement Award Labs/Teams: CHEERS Research Collaboration Network

Christiana CharalambousView profile

Lecturer

• Biostatistics
• Medical Statistics
• Pain Perception
• +4 more

Christiana Charalambous is a Lecturer in Statistics at The University of Manchester. Her research focuses on developing advanced statistical methodologies for medical and health-related applications, particularly in pain perception mechanisms and longitudinal data analysis. She is a core member of the Digital Futures research platform, contributing to statistical innovations in healthcare analytics. Her educational background includes a PhD in Statistics (2011) with a thesis titled Variable Selection in Joint Modelling of Mean and Variance for Multilevel Data , supervised by Professor Jianxin Pan. This work laid the foundation for her subsequent research in joint modelling frameworks. Key research interests span: (1) Biostatistical Modelling including copula-based joint models, longitudinal-survival analysis, and latent class models; (2) Pain Perception Dynamics exploring Bayesian estimation of pain-related traits and their neurophysiological correlates; (3) Infection Dynamics involving stochastic models for within-host disease progression and public health applications. Her methodological work integrates advanced statistical theory with clinical and epidemiological data. Recent articles highlight innovations in Gaussian copula frameworks, Burr distribution applications for infection timing analysis, and boundary effects of expectation in pain perception. Her work frequently bridges statistical theory with practical clinical challenges, such as optimizing biomarker variability analysis in longitudinal studies. As Principal Investigator of the Statistical Advisory Unit (SAU) project, she leads multidisciplinary collaborations advancing statistical methodologies across university departments. No scientific awards are explicitly mentioned in her profile. Her advisory contributions include supervising her own PhD research but no listed advisees. Research outputs are concentrated in statistical methodology with strong interdisciplinary medical applications, reflecting her role in the intersection of statistics and healthcare research.

Prateek SAXENAView profile

Associate Professor

• Computer Security
• Machine Learning Security
• Trustworthy AI
• +4 more

Prateek SAXENA is an Associate Professor in the Computer Science Department at the School of Computing, National University of Singapore. He serves as Co-Director of the CRYSTAL Centre and teaches courses including CS3235 Computer Security and CS5562 Trustworthy Machine Learning. His research spans multiple domains within computer security and systems. Dr. SAXENA earned his Ph.D. in Computer Science from the University of California, Berkeley (2012), an M.S. in Computer Science from Stony Brook University (2007), and a B.E. in Computer Engineering from the University of Pune, India (2004). His research focuses on building better security and privacy in practical systems through principled approaches combining formal reasoning, tools and ideas from several computer science domains. Current research thrusts include machine learning security, decentralized systems security, security processors, and automatic program translation. His work has resulted in several practical artifacts powering real-world systems, including spinoffs like Zilliqa and Kyber Network. His publication record demonstrates consistent high-impact research across security domains including web security, blockchain, trusted execution environments, and machine learning security. His work shows a progression from foundational web security research to cutting-edge work on blockchain systems and machine learning security. MIT Technical Review, Top 10 Innovators under 35, Asia - 2017 Security and Privacy Research Award, 2018 Young Research Award, NUS, 2017 David J. Sakrison Memorial Prize for outstanding doctoral work, UC Berkeley, 2012 AT&T Best Applied Security Research Paper Award 2010 Dr. SAXENA has advised numerous successful PhD students who have gone on to prominent positions at Microsoft Research, Georgia Tech, ETH Zurich, and industry leaders like Zilliqa and Kyber. His research has been generously supported by CISCO Research, Google, Intel, Symantec, MoE-Singapore, DSO Labs, and NRF-Singapore. He leads the KISP Lab (Keep It Secure and Private), which has produced influential research in blockchain, trusted execution environments, and security tools.

Umang MathurView profile

Assistant Professor

• Formal Methods
• Logic in Computer Science
• Programming Languages
• +3 more

Umang Mathur is an Assistant Professor at the National University of Singapore's School of Computing, specializing in Formal Methods, Logic, and their applications to Programming Languages, Software Engineering, and Computer Systems. He received his PhD from the University of Illinois at Urbana-Champaign, where he was advised by Mahesh Viswanathan, and previously worked as a Research Scientist at Meta and a Research Fellow at the Simons Institute for the Theory of Computing. At NUS, he leads the FOCS Lab and is affiliated with PLSE@NUS. His research focuses on developing algorithmic techniques for analyzing concurrent software and exploring decidability horizons in verification, synthesis, and formal logic contexts. He has been recognized with prestigious awards including a Google PhD Fellowship, Google Research Award, and multiple ACM SIGSOFT/SIGPLAN Distinguished and Best Paper Awards (ESEC/FSE'18, ASPLOS'22, POPL'23). Scientific Awards Google PhD Fellowship Google Research Award ACM SIGSOFT Distinguished Paper Award (ESEC/FSE'18) Best Paper Award (ASPLOS'22) ACM SIGPLAN Distinguished Paper Award (POPL'23) He supervises PhD students Zhendong Ang, Tianyu Li, Huan Zhao, Grace Tan, and Zihan Zhou, along with Master’s students like Zheng Shi. His taught courses include CS4211 Formal Methods for Software Engineering, CS4269/CS5469 Foundations of Logic in Computer Science, and CS6217 Topics in Prog. Languages & Software Engineering (focusing on Automata Theory, Logic, and Games).