جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Advanced Analytics
• Operations Research
• +۵ مورد دیگر

Dr. Su Nguyen is a Senior Lecturer in AI and Analytics at RMIT University's Department of Accounting, Information Systems & Supply Chain, located at the City Campus in Australia. His research focuses on integrating artificial intelligence, analytics, and operations research to address challenges in sustainability, safety, and critical domains like healthcare and logistics. Key areas include transparent AI systems, simulation models for dynamic environments, and optimization algorithms for energy and transportation. His work emphasizes making AI systems accountable to mitigate risks such as discrimination and ensures fairness in autonomous decision-making. Collaborations span Australia, New Zealand, and the Asia Pacific region, promoting AI applications in industry. Supervised projects include topics like personalized care plans, workforce rostering optimization, and AI-driven solutions for supply chains and cyber-risk evaluation. Dr. Nguyen's research bridges theoretical advancements with practical industry engagement, aiming to enhance decision-making through advanced analytics and business optimization frameworks.

• Cloud Computing
• Networked Systems
• Cybersecurity
• +۷ مورد دیگر

Dr. Qiang Fu is a Senior Lecturer at RMIT University's School of Computing Technologies, specializing in Cloud, Networked Systems, and Security. He holds a PhD from The University of Queensland and is actively involved in industry collaborations. His research focuses on Internet and Cloud-based systems, including Content Delivery Networks (CDNs), data centre design, Cyber-Physical Systems (CPS)/IoT, virtualization, and SDN/NFV. Recent work emphasizes network telemetry, fault detection, and IoT workflow optimization. He has published extensively in top-tier journals and conferences like IEEE Transactions and IFIP NOMS. Dr. Fu supervises PhD/Master students in areas such as network security, cloud computing, and IoT. His projects are often industry-funded and address real-world challenges like network scalability and blockchain integration. He is open to supervising students in these domains through RMIT's scholarship programs.

Carlos Sotoمشاهده پروفایل

استادیار

• Differential Privacy
• Bioinformatics
• Statistical Analysis
• +۳ مورد دیگر

Carlos Soto is an Assistant Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. His research focuses on the intersection of differential privacy, bioinformatics, and statistical analysis, with an emphasis on genomic data, geometric modeling, and privacy-preserving techniques. He is recognized for award-winning teaching and has contributed to interdisciplinary projects involving chromosome structure analysis and Bayesian statistical methods. His research interests include developing mathematical frameworks for privacy in data analysis, analyzing three-dimensional chromosome conformations, and applying geometric and algebraic methods to biological problems. His work often bridges theoretical statistics with computational biology, addressing challenges in genomic data interpretation and structural bioinformatics. Key trends in his publications include advancements in differential privacy for healthcare and genomic data, Bayesian approaches to topological analysis of genomes, and statistical methods for comparing chromosomal shape populations. He has also explored applications of shape analysis in power systems fault detection and incremental learning. Award-winning teaching in mathematics and statistics Advising & Grants: No advising or grant details explicitly provided in the text. Labs/Teams: No specific lab or collaborative team affiliations mentioned.

• Computer-Aided Drug Design
• Molecular Dynamics Simulations
• Structural Biology
• +۳ مورد دیگر

Jacob Durrant is an Associate Professor in the Department of Biological Sciences at the University of Pittsburgh. His research focuses on computer-aided drug design (CADD), molecular dynamics simulations, and structural biology. He leads the Durrant Lab, which develops innovative computational tools for drug discovery, such as AutoGrow4 and ProteinVR. The lab investigates infectious diseases, cancer, and neurological disorders, emphasizing small-molecule ligand identification and molecular visualization. Key affiliations include the Molecular Biophysics and Structural Biology Graduate Program, the Department of Computational & Systems Biology, and the Joint CMU-Pitt PhD Program in Computational Biology. Durrant collaborates on projects like the RECOVERY trial, exploring treatments for severe COVID-19. His work integrates machine learning, cloud computing, and GPU acceleration to advance drug discovery. Research highlights include developing open-source tools (e.g., MolModa, FPocketWeb) and studying protein dynamics via molecular simulations. The lab’s ProteinVR project enables immersive virtual reality visualization of molecular structures for educational and collaborative purposes.

• Treatment-Resistant Depression
• Psychopharmacology
• Electroconvulsive Therapy
• +۷ مورد دیگر

Sina Nikayin, MD, is an Assistant Professor Adjunct in Psychiatry at Yale School of Medicine and a psychiatrist at the Yale Interventional Psychiatry Service (IPS). He specializes in advanced modalities for treatment-resistant depression (TRD), including ketamine, esketamine, electroconvulsive therapy (ECT), and transcranial magnetic stimulation (TMS). His research focuses on the efficacy and safety of these interventions, particularly in bipolar and Parkinson's disease contexts. Education: MD from Tehran University of Medical Sciences. He is affiliated with the Center for Brain & Mind Health and contributes to clinical trials like the Ketamine Parkinson’s Disease (PD) trial. His research interests include catatonia, delirium, and patient-reported outcomes. Recent work explores ketamine vs ECT efficacy, psychedelic therapy expectations, and genetic factors in severe depression. Publications span 20+ peer-reviewed articles, emphasizing clinical trials and interventional psychiatry advancements. Collaborations include Gerard Sanacora and Samuel Wilkinson. No specific awards are listed, though his work reflects significant contributions to mental health innovation.

Arron Laceyمشاهده پروفایل

مدرس ارشد

• Health Data Science
• Machine Learning
• Natural Language Processing
• +۴ مورد دیگر

Dr Arron Lacey is a Senior Lecturer in Health Data Science and Natural Language Processing at Swansea University Medical School. He has been based at the SAIL Databank since 2011. His academic background includes a BSc in Physics, MSc in Computer Science, and a PhD in Healthcare Studies from Swansea University. Education: BSc Physics, Swansea University MSc Computer Science, Swansea University PhD Healthcare Studies, Swansea University Research Interests: Focuses on applying health data science and natural language processing (NLP) to healthcare challenges. Key areas include clinical data extraction from unstructured records, cardiovascular epidemiology, epilepsy outcomes analysis, and genomic data integration. His work emphasizes population-level data linkage and translational research. Recent Research Trends: Recent publications highlight NLP applications in extracting structured data from clinical letters, cardiovascular disease management post-intervention, and epilepsy mortality during the pandemic. His work bridges computational methods with real-world healthcare data to improve diagnosis, treatment monitoring, and public health policy. Grants & Collaborations: Led grants including HDR UK-funded NLP implementation projects (2017). Collaborates with multidisciplinary teams on initiatives like MedGATE for scalable NLP healthcare frameworks. Labs/Teams: Core member of the SAIL Databank, part of Swansea University's health data science ecosystem. Involved in the Center for Doctoral Training in Computation.

Sumit Sarkarمشاهده پروفایل

استاد

• Personalization and Recommendation Systems
• Crowdsourcing
• Sharing Economy
• +۶ مورد دیگر

Sumit Sarkar is the Charles and Nancy Davidson Chair Professor of Information Systems and Director of PhD Programs at the Jindal School of Management, University of Texas at Dallas. He also serves as the Academic Director of the International Center for Decision and Risk Analysis. His research focuses on personalization systems, crowdsourcing, data privacy, and software project management. He holds a PhD from the University of Rochester, an MBA from the Indian Institute of Management Calcutta, and a BTech from the Indian Institute of Technology New Delhi. Professor Sarkar’s research interests span multiple domains including recommendation systems, knowledge management, and the sharing economy. His work emphasizes practical applications such as privacy-preserving data sharing, optimal contest design for crowdsourcing platforms, and strategic pricing in digital markets. Notable contributions include frameworks for hiding sensitive association rules and methodologies for evaluating online review credibility. Education: PhD, University of Rochester, 1991 MBA, Indian Institute of Management Calcutta, 1982 BTech, Indian Institute of Technology New Delhi, 1979 His awards include the AIS Fellowship (2022), INFORMS President’s Service Award (2021), and the Davidson Chair appointment (2011–present). He has held leadership roles in professional organizations such as the Workshop on Information Technology and Systems and served on editorial boards of journals like MIS Quarterly and Management Science . Professor Sarkar’s work bridges theory and practice, addressing challenges in information systems through interdisciplinary approaches. His current projects explore AI-driven counterfactual explanations, competitive dynamics in search advertising, and the ethical implications of recommendation systems.

Malgorzata O'Reillyمشاهده پروفایل

دانشیار

• Applied Probability
• Stochastic Modelling
• Operations Research
• +۴ مورد دیگر

Malgorzata O'Reilly is an Associate Professor in Mathematics at the University of Tasmania's School of Natural Sciences. Her expertise lies in applied probability, stochastic modelling, and matrix-analytic methods (MAMs), with applications in healthcare systems optimization, evolutionary biology, and operations research. She leads the multidisciplinary team 'Designs for a Better Patient Journey' focused on healthcare system modeling. Her career includes roles from Lecturer (2005–2014) to Senior Lecturer (2014–2019) before her current position since 2019. Education: MSc in Mathematics and Education, Wroclaw University (1987) PhD in Applied Probability, University of Adelaide (2002) Research Interests Her research integrates theoretical and applied aspects of stochastic processes, including Markov-modulated models, healthcare system efficiency, and evolutionary gene duplication dynamics. She collaborates internationally on projects like MAM10 conference leadership and healthcare optimization with Tasmania's Department of Health. Key Contributions O'Reilly has pioneered work on two-dimensional and time-varying Markov-modulated models, contributing to algorithms for transient/stationary performance measures and numerical methods. She chairs MAM conferences and edits related proceedings, emphasizing interdisciplinary applications. Grants & Collaborations Her funding includes ARC Discovery and Linkage grants. Collaborations span healthcare modeling (e.g., emergency department wait times) and evolutionary genomics. She co-authored influential studies on GP co-payments' impact on hospital wait times and stochastic niche-based ecological models. Labs & Teams Leads the 'Designs for a Better Patient Journey' team, focusing on healthcare system modeling. Active in the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS).

Chulsoon Hwangمشاهده پروفایل

دانشیار

• Electromagnetic Compatibility (EMC)
• Signal Integrity
• Power Integrity
• +۵ مورد دیگر

Dr. Chulsoon Hwang is an Associate Professor of Electrical Engineering at Missouri University of Science and Technology (Missouri S&T) , part of the College of Engineering . He leads the EMC Laboratory and focuses on RF desensitization, signal/power integrity, machine learning in hardware design, and electromagnetic interference (EMI). His work bridges theoretical electromagnetics with practical applications in high-speed digital systems and hardware security. Education: Ph.D., M.S., and B.S. in Electrical Engineering from KAIST (Korea Advanced Institute of Science and Technology), Daejeon, South Korea. Prior to joining Missouri S&T in 2015, he worked as a Senior Engineer at Samsung Electronics (2012–2015). Research Highlights: Developed machine learning-driven simulators for signal integrity (e.g., High-speed Channel Transformer). Pioneered physics-assisted genetic algorithms for PDN decoupling optimization. Explored intentional EMI attacks (e.g., inaudible voice command injection into smart speakers). Advanced understanding of power supply-induced jitter (PSIJ) and EMI mitigation strategies. Recent Trends in Publications: Focus on AI-driven hardware optimization (deep learning/RL for PDN design), EMI/RFI modeling, and security vulnerabilities in IoT devices. Over 150 IEEE publications and multiple patents (e.g., inaudible voice command injection, laser foil printing for resonators). Awards and Recognition: Best Paper Awards (7 papers, 4 student papers). Dean’s Scholar Award (2022–2023) and IEEE EMC Society Technical Achievement Award (2023). Google Faculty Research Award (2020) and APEMC Young Scientist Award (2018). Grants and Labs: Active in securing research grants for AI-driven hardware design and EMI mitigation. The EMC Lab collaborates on industry-relevant projects, such as acoustic noise analysis in power distribution networks. Labs/Teams: Director of the EMC Laboratory at Missouri S&T, fostering interdisciplinary research in electromagnetics and hardware security.

Jia Wangمشاهده پروفایل

دانشیار

• VLSI Design Automation
• Embedded Systems
• Algorithm Design
• +۴ مورد دیگر

Jia Wang is an Associate Professor in the Department of Electrical and Computer Engineering at Illinois Institute of Technology (IIT), affiliated with the Armour College of Engineering. He joined IIT in 2008 after completing his Ph.D. in EECS from Northwestern University. His research focuses on VLSI design automation, embedded systems, and algorithm design, with particular emphasis on power grid analysis, cloud computing security, and hardware-software co-design. Education: B.S., Electronic Engineering, Tsinghua University (2002) M.S., Electrical and Computer Engineering, Northwestern University (2005) Ph.D., Electrical Engineering and Computer Science, Northwestern University (2008) Research Interests: Dr. Wang’s work addresses challenges in VLSI design automation, including sequential optimization, floorplanning, and design for manufacturability. He explores synthesis techniques for embedded systems and distributed systems, and develops algorithms for secure cloud computing and energy-efficient systems. Key areas include power grid verification, secure outsourcing of computations, and scalable simulation methods. Courses Taught: ECE 429: Introduction to VLSI Design ECE 587: Hardware/Software Co-Design ECE 449: Object-Oriented Programming and Computer Simulation ECE 586: Fault Detection in Digital Circuits ECE 473: Cloud Computing and Cloud Native Systems Professional Contributions: He leads the ACG Floorplanner project , a widely referenced tool for floorplan optimization. His research has been published in top-tier journals and conferences such as IEEE Transactions on Computer-Aided Design, DAC, and ICCAD. He actively contributes to education through curricula development in VLSI, cybersecurity, and cloud computing.

Tayfun Kucukyilmazمشاهده پروفایل

مدرس

• Web Search Engines
• Machine Learning
• Parallel and Distributed Systems
• +۳ مورد دیگر

Dr. Tayfun Kucukyilmaz is a Lecturer at the Rotterdam School of Management, Department of Technology and Operations Management. Previously, he served as an Assistant Professor at the University of Turkish Aeronautical Association and TED University (Computer Engineering Departments) from 2012 to 2021. His expertise spans Web Search Engines, Machine Learning, and High Performance Computing. Educational Background: B.S. in Computer Science and Engineering (Bilkent University, 1995–2000) M.S. in Computer Engineering (Bilkent University, 2000–2003) Ph.D. in Computer Engineering (Bilkent University, 2006–2012) Research Focus: His work emphasizes optimizing search engine performance, developing metaheuristic algorithms, and enhancing information retrieval systems. Current research integrates machine learning techniques with parallel/distributed computing for real-world applications like healthcare diagnostics. Collaborations: Active collaborations span global institutions, particularly in areas of optimization algorithms and search engine efficiency.

Cihan H. Dagliمشاهده پروفایل

استاد

• Systems Engineering
• Cyber-Physical Systems
• Machine Learning
• +۷ مورد دیگر

Cihan H. Dagli is a Professor of Systems Engineering and Engineering Management at Missouri University of Science and Technology (Missouri S&T). He is the founder of the Systems Engineering Graduate Program at Missouri S&T and directs the Smart Engineering Systems Lab (SESL). He serves as a Senior Investigator in the DoD Systems Engineering Research Center-URAC. His academic journey includes a Ph.D. in Applied Operations Research from the University of Birmingham (UK), with early work on water resource systems and evolving into systems engineering, cyber-physical systems, and machine learning. Research interests span systems architecting, computational intelligence, and deep learning applications in complex systems such as transportation, energy, and healthcare. He has secured over $25 million in grants, including a $10M DoD grant for the Systems Engineering Research Center-UARC. With 450+ publications and an h-index of 31, he is a Fellow of INCOSE (2008), IIE (2009), and IFPR (2019). He chairs the Complex Adaptive Systems conference series and advises over 35 PhD students across Engineering Management, Computer Science, and Systems Engineering. Recent work focuses on AI-driven kidney transplant optimization, meta-architectures for cyber-physical systems, and system-of-systems resilience. His educational contributions include developing the SEEE portal for systems engineering education and pioneering courses like Advanced Neural Networks and Complex System Modeling. Education: Ph.D., Applied Operations Research, University of Birmingham, UK (1979) Key Roles: Director of SESL, INCOSE Fellow, Omega Alpha Society Board Chairman Scientific Awards: Fellow of INCOSE (2008) Fellow of IIE (2009) Fellow of IFPR (2019) Member of Omega Alpha Association (2013) Advising and Grants: Advised 26 Engineering Management, 1 Computer Science, and 9 Systems Engineering PhD students Total grants: $25M+ from federal, industrial, and academic sources Labs/Teams: Smart Engineering Systems Lab (SESL) DoD Systems Engineering Research Center-URAC Complex Adaptive Systems conference organizer

Arjun P. Athreyaمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Digital Health
• Precision Medicine
• +۶ مورد دیگر

Arjun P. Athreya, Ph.D., M.S., is an Associate Professor at Mayo Clinic's Department of Molecular Pharmacology and Experimental Therapeutics , specializing in Artificial Intelligence and Digital Health for precision medicine. With a background in Electrical and Computer Engineering, he bridges engineering ecosystems with clinical practice to optimize treatment selection and management through data integration from genomics , wearables , and electronic health records . Ph.D., University of Illinois Urbana-Champaign (Electrical and Computer Engineering) M.S., Carnegie Mellon University (Computer Software Engineering and Electrical and Computer Engineering) B.E., RV College of Engineering, VTU (Electrical and Telecommunication Engineering) His research spans precision care for chronic conditions like major depressive disorder and bipolar depression , digital health technologies for pediatric mental health , and provider well-being solutions. He leads projects on multi-omic biomarker discovery for diseases such as primary sclerosing cholangitis and pancreatic ductal adenocarcinoma , integrating AI with clinical workflows. Dr. Athreya’s work emphasizes participatory design in decentralized digital health studies and ethical AI applications. Current projects include National Institute of Nursing Research -funded studies on smartwatch adherence for burnout prediction and National Science Foundation initiatives to implement patient-specific therapy profiles in EHRs for genomic medicine. His research team collaborates with psychiatrists, gastroenterologists, and bioethicists across Mayo Clinic. Scientific Awards: American Society for Clinical Pharmacology and Therapeutics Presidential Trainee Award (2017-2019) Jason Morrow Memorial Award (2017) IEEE Best Paper Awards (2016, 2017) Rambus Computer Engineering Fellowship (2017) Carnegie Mellon Dean’s Fellowship (2011-2013)

Fabien Crausteمشاهده پروفایل

پژوهشگر

• Biomathematics
• Mathematical Immunology
• Delay Differential Equations
• +۴ مورد دیگر

Fabien Crauste is a Director of Research at CNRS, affiliated with MAP5 UMR 8541 at the University of Paris Cité. His work bridges applied mathematics and biomedical research through multi-scale modeling. Math Bio Santé Thematic Network Director Organizer of Modeling, Analysis, Simulations working group Co-organizer of mathematical modeling in life sciences seminar Member of PEPR Maths-Vives Program Committee Active in AMIES and MAP1.5 environmental initiatives Research focuses on mathematical immunology , delay differential equations , and cell population dynamics with applications to CD8 T cell responses, B cell differentiation, and diseases like chronic lymphocytic leukemia and atopic dermatitis . Special emphasis on stochastic modeling and inter-individual variability in immune responses. Current projects include AI4scMED (multiscale AI for precision medicine), DCComm (dendritic-T cell communication), and Digi-DermA (dermatitis modeling). Supervises multiple postdocs and PhD students on these topics. Contributions include developing the Simuscale framework for multi-cell modeling and analyzing erythropoiesis dynamics and germinal center B cell differentiation .

• Network Programmability
• Network Virtualization
• Routing
• +۷ مورد دیگر

Géraldine Texier is a Professor at the Network Systems, Cybersecurity and Digital Law (SRCD) department of IMT Atlantique, a member of the Adopnet research team at IRISA, and affiliated with the Advanced Connectivity lab of the b com Institute. Her research focuses on network programmability, virtualization, Quality of Service (QoS), inter-domain routing, and IoT. She contributes to academic activities through teaching networking courses and co-developing three MOOCs. Her research spans advanced topics in Software Defined Networking (SDN) Network Function Virtualization (NFV) QoS in inter-domain contexts IoT routing protocols Genetic algorithms for network optimization Fuzzy reputation systems for 5G infrastructure with a particular emphasis on scalable solutions and trust mechanisms. The 15 most recent publications highlight her work in network tomography, federated learning, and 5G slicing. Key trends include AI-driven network service placement reputation systems for RAN sharing genetic algorithms for monitoring optimization inter-domain path computation QoS in virtualized environments collaborative security frameworks In her advisory role, she has directed multiple PhD students including Masoud Taghavian (NFV in 5G Edge) Cedric Morin (SDN-NFV QoS algorithms) Rabah Guedrez (Segment Routing) Pascal Thubert (Deterministic Networks) and maintains active involvement in EU projects and industry collaborations.