جست‌وجوی استاد و پژوهشگر

Dilum Bandaraمشاهده پروفایل

عضو هیئت علمی

• Distributed Systems
• Blockchain
• Cloud Computing
• +۱۳ مورد دیگر

Dilum Bandara is a Principal Research Scientist at CSIRO's Data61 in Australia and an Adjunct Senior Lecturer at the School of Computer Science and Engineering, Faculty of Engineering, University of New South Wales (UNSW). He has previously served as a Senior Lecturer at the University of Moratuwa, Sri Lanka, and has over two decades of experience in research, teaching, and consultancy in distributed systems, security, and software engineering. His academic qualifications include: PhD in Computer Science, Colorado State University, USA (2012) MS in Computer Science, Colorado State University, USA (2008) BSc Eng. (Hons) in Computer Science and Engineering, University of Moratuwa, Sri Lanka (2004) Dilum's research interests are centered on Distributed Systems (Blockchain, Cloud, P2P), Computer Security , Software Architecture , Data Engineering , Performance Engineering , and the Internet of Things (IoT) . He applies these technologies in multidisciplinary domains such as Supply Chains , Digital Finance , Environmental, Social, and Governance (ESG) , Fleet Management , and Weather Monitoring . His work emphasizes real-world impact through trusted data management in multi-party ecosystems. The analysis of his recent publications reveals a strong focus on blockchain for transparency and security, cloud-native performance engineering, IoT integration with edge and cloud, and data-driven solutions for smart cities and sustainability. His work consistently bridges theoretical innovation with practical deployment, particularly in national and international infrastructure projects. His scientific awards include: Best Paper Award at BPM 2024 Multiple CSIRO internal awards (Customer First, Engineering and Technology, Collaboration) from 2021–2023 Student Paper Award (Merit) at IEEE SOLI 2018 Award of Excellence for Outstanding Research at University of Moratuwa (2015–2018) Dilum has led and contributed to several research grants, particularly during his time at the University of Moratuwa, including projects on smart city integration, real-time data forecasting, and cloud platforms for scientific computing. He has also held leadership roles such as Director of the Engineering Research Unit and co-founder of VaticHub. He is actively involved in professional communities as a Senior Member of IEEE and a Chartered Engineer with IESL. At CSIRO, he serves as a Health and Safety Representative, reflecting his commitment to corporate citizenship. He has advised students and early-career researchers, though specific names are not listed in the provided text. His labs and research teams include the Architecture and Analytics Platforms (AAP) team at CSIRO Data61 and collaborations with academic institutions like UNSW and University of Moratuwa.

• Process and Manufacturing Engineering
• Chemical Engineering
• Electroplating and Corrosion Protection
• +۷ مورد دیگر

Professor Chike F. Oduoza is a distinguished academic in Process and Manufacturing Engineering at the University of Wolverhampton, Faculty of Science and Engineering, Department of Chemical Engineering. He holds the rank of Professor and serves as the academic lead for chemical engineering, with extensive leadership in research, teaching, and professional service. His educational background includes a PhD in Instrumentation and Control from UMIST (University of Manchester), an MBA from the University of Exeter, and multiple postgraduate qualifications in management, teaching, and chemical engineering. He is a Chartered Engineer, Fellow of the Institution of Chemical Engineers, and Senior Fellow of the Higher Education Academy. His research interests span chemical and manufacturing engineering, with a focus on electroplating, corrosion protection, reactor design, sustainability, life cycle engineering, oil and gas processing, and risk management in industrial and construction sectors. He has developed innovative models for SMEs, particularly in risk assessment and lean-excellence business management. The recent publications reflect a strong trend in sustainable energy systems, risk and safety management, digital transformation in manufacturing and oil & gas, and advanced materials. His work integrates computational modelling, experimental validation, and practical application across industries. Chartered Engineer (CEng), 1996 Fellow, Institution of Chemical Engineers, 2006 Senior Fellow, Higher Education Academy, 2020 Winner, West Midlands Construction Excellence Award (Innovation, 2017) Professor Oduoza has supervised over 30 PhD students and secured significant research funding from EPSRC, EU (FP7, Horizon 2020), and industry. He is currently leading the FLAREMANAGER and PROCEDURE consortia, focusing on flare gas utilization and future process design. His editorial roles include guest editor for Robotics and Computer Integrated Manufacturing and International Journal of Advanced Manufacturing Technology . He has chaired major conferences such as FAIM 2015 and the Electrochemistry and Sustainability Conference (2010). He leads the RiMaCon project, a €1M EU FP7 initiative that developed a risk management software system for SMEs in construction, which won a regional innovation award. His professional memberships include the Engineering Professors Council, SCI Electrochemical and Energy Groups, and the UK Royal Academy of Engineering Ethics Committee.

• Wireless Communications
• Information Theory
• Communication Networks
• +۱۸ مورد دیگر

Cenk Gursoy is a Professor in the Department of Electrical Engineering and Computer Science at the College of Engineering and Computer Science, Syracuse University. He previously served as a faculty member at the University of Nebraska-Lincoln from 2004 to 2011. He holds a Ph.D. in Electrical Engineering from Princeton University and a B.S. from Bogazici University, Turkey. His research spans wireless communications, information theory, signal processing, and networking. Key areas include 5G/6G technologies, millimeter-wave communications, UAV-assisted networks, energy efficiency, intelligent reflecting surfaces, and machine learning for networking. He has made significant contributions to finite blocklength communications, QoS provisioning, and secure wireless transmissions. The recent publications highlight a strong trend in integrating machine learning—particularly deep reinforcement learning—into wireless resource allocation, network slicing, UAV trajectory planning, and anomaly detection. His work increasingly bridges theoretical information-theoretic models with practical implementations in emerging wireless systems such as RIS-aided networks, NOMA, and edge computing. NSF CAREER Award, 2006 2020 IEEE Region 1 Technological Innovation (Academic) Award IEEE Green Communications & Computing Technical Committee Best Journal Paper Award EURASIP Journal of Wireless Communications and Networking Best Paper Award IEEE PIMRC Best Paper Award Maude Hammond Fling Faculty Research Fellowship All-University Doctoral Prize (awarded twice to his students) Dr. Gursoy has advised over 20 Ph.D. and M.S. students, many of whom now hold positions at leading universities and tech companies. His research has been funded by multiple National Science Foundation grants as Principal or Co-Principal Investigator, focusing on fundamental limits of wireless systems, millimeter-wave networking, and green cloud platforms. He serves as an Area Editor for IEEE Transactions on Vehicular Technology and as an Editor for several other IEEE Transactions journals. He leads the Wireless Communications & Networking Lab and the Smart Vision Systems Lab at Syracuse University, fostering interdisciplinary research in smart networks, IoT, and intelligent sensing systems.

Alfredo Bensoمشاهده پروفایل

استاد

• Bioinformatics
• Systems Biology
• Artificial Intelligence
• +۱۶ مورد دیگر

Alfredo Benso is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab. He has been continuously involved in the Doctoral College for Computer and Systems Engineering since 2008, guiding PhD education across numerous cycles. His academic roles span teaching and research leadership in bioinformatics, systems biology, and computer engineering. Research interests: Bioinformatics and computational biology Systems biology and gene regulatory networks Artificial intelligence and machine learning in biomedicine Molecular modeling and multiscale simulation Biological database systems and data integration Health informatics and public health modeling His recent publications reflect a strong trend in applying AI and machine learning to biological and medical challenges, including protein function prediction, Alzheimer’s and Multiple Sclerosis modeling, food fraud detection, and viral genome analysis. These works span journals and conferences in bioinformatics, computational biology, and biomedical engineering, demonstrating interdisciplinary innovation. Scientific Awards: BIOINFORMATICS 2014 BEST PAPER AWARD (INSTICC, United Kingdom) Advising and Grants: He supervises PhD students, including Sofia Ostellino, and leads major research initiatives such as the BIGMECH (2023–2025) and FISHUB (2016–2018) projects. He has served as Scientific Director for collaborative agreements with public administrations and as Principal Investigator on EU, national (PRIN), and regional research grants focused on bioinformatics, space systems, and reliable digital technologies. Labs and Teams: He is a key member of the SBG - System Biology Group (DAUIN) and contributes to PolitoBIOMed Lab, fostering collaborative research in biomedical engineering and computational biology.

Soo Wooi Kingمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Network Security
• Wireless Networks
• +۳ مورد دیگر

Soo Wooi King serves as a Senior Teaching Fellow at Monash University Malaysia's School of Information Technology, contributing to both academic instruction and research in information technology systems. His professional profile centers on practical applications of computational methods in security and network optimization. His research spans Machine Learning, Network Security, Wireless Networks, and Natural Language Processing, with emphasis on implementing Naive Bayes classifiers for real-world problem solving. Key application areas include malware detection systems, news credibility assessment tools, and telecommunications network management solutions where algorithmic precision directly impacts operational reliability. Publication trends from 2017-2022 reveal consistent specialization in machine learning deployment across cybersecurity and networking domains. His highly cited 2018 survey on wireless load-balancing (18 Scopus citations) demonstrates significant field impact, while recent malware classification research shows evolving technical sophistication in feature engineering approaches. Work consistently bridges theoretical algorithms with industry-specific implementation challenges.

• Requirements Engineering
• Conceptual Modeling
• Software Engineering
• +۴ مورد دیگر

Maria Dolors Costal Costa is an Associate Professor in the Department of Service and Information Systems Engineering at the Facultat d'Informàtica de Barcelona, Universitat Politècnica de Catalunya (UPC). She is a key member of the GESSI and inSSIDE research groups, focusing on software and service engineering. Her research interests include: Requirements Engineering Conceptual Modeling Model-Driven Development Non-Functional Requirements Open Source Software Ecosystems Goal-Oriented Requirements Engineering Her recent publications (2019–2024) reflect a strong focus on conceptual modeling, requirements engineering, and software quality, particularly in agile and ML-based systems. She frequently contributes to top-tier conferences like ER and CAiSE, and her work integrates empirical methods with modeling frameworks. She has received recognition for her research, including the Best Paper Award at CIbSE 2021. Her involvement in numerous competitive R&D+i projects demonstrates sustained research funding and leadership. She actively mentors and collaborates with researchers such as Javier Franch and Cristina Gómez. Her work is supported by participation in EU and national research initiatives like HORIZON 2020 and Plan Estatal de Investigación. She is involved in several research labs and teams, including: GESSI - Group of Software and Service Engineering inSSIDE - integrated Software, Services, Information and Data Engineering inLab FIB

Anahita Khojandiمشاهده پروفایل

دانشیار

• Decision Making Under Uncertainty
• Reinforcement Learning
• Markov Decision Processes
• +۹ مورد دیگر

Anahita Khojandi is an Associate Professor in the Department of Industrial and Systems Engineering at the University of Tennessee, Knoxville, where she also holds the Heath Endowed Faculty Fellow in Business & Engineering title. She is also a Joint Associate Professor at the Bredesen Center for Interdisciplinary Research and Graduate Education and served as the Director of the Reliability and Maintainability Engineering Program from 2021 to 2024. Her interdisciplinary research spans healthcare, transportation, environmental engineering, and advanced manufacturing. Education: PhD in Industrial Engineering, University of Pittsburgh MS in Industrial Engineering, University of Pittsburgh BS in Industrial Engineering, Sharif University of Technology, Tehran, Iran Her research focuses on decision-making under uncertainty, reinforcement learning, Markov decision processes, and predictive analytics. These methodologies are applied to critical domains such as sepsis prediction, Parkinson’s disease treatment using wearable sensors, intelligent transportation systems, nuclear safety, and green infrastructure resilience. She integrates machine learning with stochastic modeling to improve real-time decision-making in complex systems. The recent publications highlight a strong trend toward AI-driven solutions in healthcare and infrastructure, with emphasis on explainability, anomaly detection, and real-time adaptation. Her work frequently appears in high-impact journals such as Management Science , IEEE Transactions , and Nuclear Technology , reflecting both methodological rigor and practical relevance. Scientific Awards and Honors: AAAS Rapid Response AI Fellow (2024) NIH AIM-AHEAD Fellowship in Leadership (2023) First Place, Harvey J. Greenberg Research Award (INFORMS, 2022) Best Paper Award, OMEGA Journal (2020, 2021) INFORMS Senior Member (2024) Teaching Award, IISE DAIS Division (2024) Khojandi has advised numerous graduate students and postdoctoral researchers, many of whom are co-authors on her publications. Her research has been supported by the National Science Foundation (NSF), National Institutes of Health (NIH), Department of Energy (DOE), and other federal and institutional grants. She actively contributes to professional service, including leadership roles in INFORMS, where she served as Chair of the Diversity, Equity, and Inclusion Committee and currently serves as Vice President of Membership and Professional Recognition. She leads research initiatives at the intersection of industrial engineering and data science, often in collaboration with the Health Innovation Technology & Simulation (HITS) Lab and the Center for Transportation Research. Her lab focuses on developing AI-enabled decision support tools for clinical and operational environments, with future work targeting autonomous systems, personalized medicine, and climate-resilient infrastructure.

• Distributed Systems
• Embedded Systems
• Real-Time Systems
• +۳ مورد دیگر

Brian Nielsen is an Associate Professor at Aalborg University's Department of Computer Science, under The Technical Faculty of IT and Design. His research focuses on Distributed Systems, Embedded Systems, Real-Time Systems, Model Checking, IoT Networks, and Autonomous Vehicles. He has been actively involved in projects such as domOS (operating system for smart buildings), FED (Flexible Energy Denmark), and compositional verification of multicore avionics systems. His work emphasizes model-based validation, formal methods, and industrial applications, particularly in safety-critical systems. Recent research highlights include energy-efficient motion planning for autonomous vehicles, comparative analysis of network simulators, and sigfox-based IoT modeling. He has received awards including the Application Coordinator Pool and START funds (both in 2007). Key Projects: domOS, FED, compositional verification of multicore systems Grants: Multiple EU-funded projects (e.g., Horizon Europe) and industry collaborations Awards: Application Coordinator Pool (2007), START funds (2007) His publications span over 80 articles, with a focus on real-time systems, IoT interoperability, and model-driven development. He has advised two PhD students and has been actively involved in organizing international conferences and workshops.

Mike Koenigsمشاهده پروفایل

استاد

• Mental Health in Incarcerated Populations
• Psychopathy
• Emotion Processing
• +۷ مورد دیگر

Dr. Mike Koenigs is a Professor in the Department of Psychiatry at the University of Wisconsin–Madison, where he leads the Incarceration & Mental Health Lab. His research focuses on improving mental healthcare and well-being for currently and formerly incarcerated individuals through community engagement, intervention development, and clinical trials. He collaborates extensively with the Wisconsin Department of Corrections and individuals with lived incarceration experience. University: University of Wisconsin–Madison School: School of Medicine and Public Health Department: Department of Psychiatry Academic Rank: Professor Dr. Koenigs' research integrates neuroscience, clinical psychology, and community-based methodologies. His work explores emotion processing, decision-making, psychopathy, and trauma in forensic populations. He employs fMRI, lesion studies, and behavioral assessments to understand the neurobiological underpinnings of psychopathology. His lab also conducts clinical trials of psychotherapies such as Cognitive Processing Therapy (CPT) within prison settings. His recent publications (2020–2025) show a strong focus on psychopathy, neural correlates of emotion, community-academic partnerships, and mental health interventions in incarcerated populations. Key trends include the use of machine learning in recidivism prediction, functional connectivity in psychopathy, and the role of lived experience in research design. Dr. Koenigs mentors graduate students through both the Clinical Psychology and Individualized Graduate Major (IGM) PhD tracks. He values qualities such as empathy, collegiality, and commitment to marginalized populations in his advisees. He has advised numerous PhD and master’s students, including Mickela Heilicher, Tatiana Ray, Phil Deming, and Julian Motzkin, among others. His lab emphasizes community engagement, partnering with peer specialists and advisory boards composed of formerly incarcerated individuals to co-develop and co-lead mental health interventions.

• Database Systems
• Data Management
• Cloud Computing
• +۵ مورد دیگر

Abdelkader Hameurlain is an active academic researcher specializing in database systems, data management, and cloud computing with a prolific publication record spanning over three decades (1990-2025). He has authored or co-authored more than 170 publications and serves as an editor for the prestigious 'Transactions on Large-Scale Data- and Knowledge-Centered Systems' series published by Springer as part of the Lecture Notes in Computer Science. His research interests focus on database systems, data management, cloud computing, query optimization, data replication, and big data analytics. Hameurlain has made significant contributions to multi-tenant database management systems, SLA-aware query optimization, data replication strategies in cloud environments, and knowledge-based systems. His work bridges theoretical foundations with practical applications in large-scale data processing environments. Analysis of his recent publications (2021-2025) reveals a continued focus on cloud database performance optimization, with particular emphasis on multi-tenant systems, SLA compliance, and cost-effective resource allocation. His research demonstrates a consistent trajectory from traditional database systems toward cloud-native and distributed data management solutions, reflecting the evolving landscape of data-intensive computing. Hameurlain has established long-term collaborations with prominent researchers including Franck Morvan (63 joint publications), Roland R. Wagner (50 joint publications), Josef Küng (40 joint publications), and A Min Tjoa (26 joint publications), indicating his central position in the database research community. As an editor of the Transactions on Large-Scale Data- and Knowledge-Centered Systems series, he has played a significant role in shaping research directions in data management through numerous special issues covering database technologies, big data analytics, cloud computing, and knowledge systems. His editorial work spans multiple volumes from TLS-DCS XIII (2014) through TLS-DCS LVI (2024), demonstrating sustained leadership in the field.

Adrian Spătaruمشاهده پروفایل

مدرس

• Cloud Computing
• Distributed Systems
• Edge Computing
• +۴ مورد دیگر

Adrian Spătaru serves as a Lecturer at the Faculty of Mathematics and Computer Science, West University of Timisoara, Romania, with his office located in room 058. He maintains active academic engagement through direct contact channels including email (adrian.spataru@e-uvt.ro) and phone ((0256) 592 157), reflecting ongoing institutional affiliation and research activities within computer science. His research centers on the integration of edge, cloud, and high-performance computing resources within the cloud continuum framework. Key focus areas include service orchestration, resource management, blockchain applications for decentralized systems, and AI-driven optimization of cloud infrastructures. His work addresses critical challenges in heterogeneous platform integration, fault tolerance, and predictive maintenance across large-scale distributed environments, with notable contributions to container deployment and accelerator-aware application specification. Analysis of his publication trends reveals sustained emphasis on the edge-cloud-HPC continuum since 2018, evolving toward intent-based AI orchestration and heterogeneous hardware integration in recent works. His research bridges theoretical distributed systems concepts with practical applications in environmental monitoring (solar forecasting, freshwater quality assessment) and industrial cloud reliability, demonstrating both academic rigor and real-world impact. No scientific awards are documented in the provided institutional information. Details regarding student supervision, research grants, or laboratory affiliations are not specified in the available materials. Current research directions appear focused on advancing the edge-cloud-HPC continuum through heterogeneous platform integration, with 2025 publications indicating active development in this domain.

Henrik William Bindnerمشاهده پروفایل

پژوهشگر

• Power Engineering
• Distributed Energy Systems
• Electric Power Distribution
• +۳ مورد دیگر

Henrik William Bindner serves as Senior Researcher and Head of Section at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), specializing in distributed energy systems and power grid innovation. His work directly supports UN Sustainable Development Goals through renewable energy integration and grid resilience research. Research Focus: Power Engineering and Distributed Energy Systems form the core of his expertise, with deep specialization in Electric Power Distribution, Smart Grids, and Energy Flexibility. His investigations into consumer behavior during energy crises, industrial flexibility services, and renewable integration address critical challenges in modern power systems. Publication Trends: Recent works (2024-2025) reveal concentrated efforts in grid flexibility mechanisms, including consumer-driven demand response, green hydrogen pathways, and industrial ancillary services. These studies consistently explore market design innovations and uncertainty management in distribution grids transitioning to high renewable penetration. Supervision & Funding: PhD Supervision: Bak, B. S. (Data-driven grid investments), Yousefi, G. (EV flexibility services) Active Projects: ROADNET (Resilient Distribution Networks, 2025-2028), e2flex (Enabling Flexibility, 2023-2026) Consultancy: South African EV infrastructure development (2024) Team Leadership: As Head of Section, he directs DTU's Distributed Energy Systems research group, coordinating cross-institutional collaborations on grid flexibility, renewable integration, and market design. The team maintains active partnerships with European grid operators and industrial energy consumers to validate real-world applications of their frameworks.

Rob Bastenمشاهده پروفایل

دانشیار

• Operations Management
• Behavioral Operations Management
• Maintenance Optimization
• +۷ مورد دیگر

Rob Basten is an Associate Professor in the Department of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology (TU/e). He has been with TU/e since October 2014, initially as an Assistant Professor before being promoted. His work focuses on operations management and behavioral operations management, with particular expertise in maintenance, spare parts supply, and after-sales services for high-tech equipment. Basten's research is highly applied, often conducted in collaboration with industry partners such as ASML, NXP, Canon Production Printing, Marel Poultry, and the Ministry of Defence. Dr. Basten's educational background includes: Master's in Industrial Engineering and Management (2004) from University of Twente Master's in Computer Science (2005) from University of Twente PhD in Operations Management (2010) from University of Twente Rob Basten's research centers on improving after-sales services for high-tech equipment, with a focus on incorporating new technologies such as 3D printing and IoT. His work spans both analytical and empirical approaches, with increasing emphasis on behavioral operations management as human decision-makers interact with AI-based decision support systems. Basten investigates how to design and control after-sales service supply chains when spare parts can be 3D printed, and how to optimize maintenance policies for complex systems. His interdisciplinary research bridges operations management, maintenance engineering, and human behavior. Analysis of Basten's recent publications reveals a strong focus on the application of new technologies in after-sales services. Key trends include the integration of additive manufacturing in spare parts supply chains, condition-based and predictive maintenance driven by Industry 4.0 technologies, and the behavioral aspects of human-AI collaboration in maintenance decision-making. His work frequently addresses challenges in high-tech manufacturing contexts, particularly semiconductor equipment, with a growing emphasis on Industry 5.0 concepts that integrate human-centered approaches with advanced technologies. Dr. Basten has received recognition for his work, including: Finalist for the 2020 Daniel H. Wagner Prize for Excellence in Operations Research Practice ISIR Best Student Paper Award 2018 Rob Basten actively supervises numerous PhD students and has led several major research projects. He currently supervises nine PhD students including Maryam Azani, Ragnar Eggertsson, Bibi de Jong, Zhao Kang, Niccolò Maccarini, Aran Nasiri, Bas van Oudenhoven, İpek Tanıl, and Alireza Yazdani. He has successfully guided six PhD students to completion. Basten has been project leader and work package leader in significant research initiatives including ProSeLoNext (funded by NWO with industry co-funding), PrimaVera, SINTAS, and OCPROM projects. His research is consistently supported by both public funding agencies and industry partnerships, reflecting the practical relevance of his work. Basten is an active member of the Operations, Planning, Accounting & Control group at TU/e and contributes to the EAISI High Tech Systems initiative. He has organized key academic events including the first two editions of the Maintenance Research Day and the Behavioral Operations Conference 2019. His work connects academic research with industry practice through ongoing collaborations with leading high-tech companies, creating a dynamic research environment focused on solving real-world challenges in maintenance and service logistics.

• Operations Management
• Quality Control
• Process Improvement
• +۵ مورد دیگر

Prof. dr. Jeroen de Mast is a faculty member at the University of Amsterdam (UvA) , affiliated with the Faculty of Economics and Business and the Section Business Analytics . His research focuses on Lean Six Sigma , statistical engineering , and diagnostic problem solving , with applications in healthcare operations and industrial processes. He has authored numerous publications on topics such as variation reduction, measurement systems, and quality improvement frameworks. Academic Rank: Professor Contact: j.demast@uva.nl Research Trends (2019–2025): His work spans operational excellence , appointment scheduling optimization , and statistical validation , emphasizing interdisciplinary collaboration between statistics, healthcare, and business analytics. Key methodologies include DMAIC , DAPS diagrams , and adaptive polynomials .

James Morizioمشاهده پروفایل

استاد مدعو

• Analog CMOS Microelectronics
• Neural Interfaces
• Acoustofluidics
• +۴ مورد دیگر

James Morizio serves as an Adjunct Professor in the Department of Electrical and Computer Engineering at Duke University, leveraging 35+ years of expertise in analog CMOS microelectronics for biomedical applications. His research bridges electrical engineering with neuroscience through disruptive sensor interface technologies for neural recording/stimulation and ultrasonic microfluidics. His educational background includes a Ph.D. in Electrical Engineering from Duke University (1995) M.S. in Electrical Engineering from University of Colorado, Boulder (1984) B.S. in Electrical Engineering from Virginia Polytechnic Institute and State University (1982) Morizio's research focuses on developing high-performance neural interfaces and acoustofluidic systems. Key areas include wireless neural instrumentation for closed-loop electrophysiology, CMOS-based ultrasonic transducers for microfluidic manipulation, and low-power VLSI design for implantable devices. His work emphasizes translating microelectronics innovations into biomedical solutions for neuroscience and diagnostics. His publication portfolio demonstrates consistent contributions to neural engineering and microfluidics, with recent trends showing increased focus on acoustofluidic diagnostics (e.g., AIMDx chip) and osseointegrated neural interfaces for prosthetic control. The research spans fundamental circuit design to translational applications in cancer metabolism and neuroprosthetics. Scientific recognition includes 15-year service award from Triangle BioSystems International/Harvard Bioscience Inc. (2016) Current research is supported by major grants including Neuro-CROWN (ultra-flexible electrode arrays), digital acoustofluidic systems for biomedical automation, and osseointegrated neural interfaces for prosthetic control. His teaching portfolio spans advanced VLSI design and special topics courses, though specific advising roles are not documented. Collaborative work involves interdisciplinary teams in neuroscience and biomedical engineering, particularly through partnerships with Triangle BioSystems International and translational projects using ovine models for neural interface validation.