Find Academic Supervisors

• Nursing Education
• Clinical Nursing Practice
• Pediatric Nursing
• +3 more

Amy Palma serves as an Assistant Professor in the Department of Nursing within McMaster University's Faculty of Health Sciences. Her academic career focuses on nursing education and clinical practice, with particular expertise in teaching methodologies and student-educator relationships in nursing education. Her research interests span multiple critical areas of nursing education and practice, with primary focus on Nursing Education methodologies, particularly problem-based learning approaches. She investigates Clinical Nursing Practice effectiveness, examining how students perceive and respond to different teaching styles in clinical settings. Additional research areas include Pediatric Nursing interventions, specifically pain management protocols, and Problem-Based Learning effectiveness in nursing curricula. Analysis of her scholarly publications reveals a consistent focus on educational dynamics within nursing programs. Her work primarily examines the relationship between nursing students and their educators, with particular attention to what makes clinical teaching effective. The publications show a trajectory from examining specific teaching methods (problem-based learning) to broader investigations of educator effectiveness in clinical practice settings. While limited in number (three publications between 2015-2016), these works represent meaningful contributions to nursing education literature. Amy Palma maintains an active teaching schedule across multiple foundational nursing courses at McMaster University. Her teaching portfolio demonstrates consistent involvement in core nursing curriculum components, particularly in introductory and professional practice courses that form the bedrock of nursing education. Her teaching responsibilities span numerous foundational nursing courses including Introduction to Nursing and Health I & II (NURSING 1F03, 1G03), Professional Nursing Practice I (NURSING 1J02), Introduction to Nursing Practice (NURSING 1I02), Community Engagement and Citizenship (NURSING 1K02), and Reintegration Course (NURSING 1RP0). She has also taught more advanced courses including Nursing Concepts in Health and Illness III & IV (NURSING 3SS3, 3TT3), Professional Community Nursing Practice (NURSING 3QQ3), and Professional Nursing Practice IV & V (NURSING 3X04, 3Y04). Her teaching record shows continuous engagement from 2015 through the projected 2025 academic year.

Alex CresswellView profile

Senior Lecturer

• Organic Chemistry
• Catalysis
• C-H Bond Functionalization
• +5 more

Alex Cresswell is a Reader in the Department of Chemistry at the University of Bath, where he leads research in synthetic organic chemistry. His work focuses on catalysis (metal and metal-free), C–H bond functionalization, and the use of reactive intermediates for sustainable synthesis. He is affiliated with the Institute of Sustainability and Climate Change and collaborates on projects like the Sustainable Chemicals and Materials Manufacturing Hub. M.Chem, University of Oxford (2008) D.Phil., University of Oxford (2012) Postdoctoral Research Associate, University of Illinois at Urbana-Champaign (2012–2014) Postdoctoral Research Associate, University of Edinburgh (2014–2016) His research interests center on developing new synthetic methods for organic chemistry, with an emphasis on photocatalysis, radical chemistry, and sustainable approaches. Key themes include photoredox-hydrogen atom transfer (HAT), gold-catalyzed C–H arylation, and iron-mediated cross-coupling reactions. His work contributes to UN Sustainable Development Goals like responsible consumption and climate action. Recent publications highlight advancements in photoredox-HAT catalysis, automated synthesis of spirocycles, and mechanistic studies using transient absorption spectroscopy. Collaborative projects involve optimizing radical C–C bond formation and exploring paired electrosynthesis for green chemistry. Scientific Awards Royal Society University Research Fellowship (2016) As an advisor, Alex has mentored doctoral students including Hannah Askey, Jacob Turner-Dore, Alison Ryder, and Anna Kinsella, with a focus on training the next generation of chemists in sustainable methodologies. His group also collaborates with institutions like the University of Illinois, University of Edinburgh, and the Royal Society.

Dajana VuckovicView profile

Professor

• analytical chemistry
• metabolomics
• lipidomics
• +7 more

Dajana Vuckovic, PhD, is a full Professor and Concordia University Research Chair in the Department of Chemistry and Biochemistry at Concordia University's School of Health. She directs the Centre for Biological Applications of Mass Spectrometry (CBAMS) and leads an active research group. Her education includes a PhD from the University of Waterloo and an NSERC Postdoctoral Fellowship at the University of Toronto. Dr. Vuckovic's research focuses on cutting-edge analytical chemistry methodologies with emphasis on: Advanced mass spectrometry techniques for metabolomics and lipidomics Innovative sample preparation approaches for complex biological matrices Biomarker discovery and validation for cardiovascular health and inflammation Development of standardized protocols for untargeted analysis Applications in nutrition and neurological research Her extensive publication record demonstrates a consistent focus on analytical method development, particularly in LC-MS based metabolomics and lipidomics. Recent works emphasize QA/QC standardization, tissue analysis advancements, and novel applications in neuroscience and cardiovascular research. Awards & Honors: PetroCanada Young Innovator Award As Director of CBAMS, she oversees interdisciplinary research in biological mass spectrometry. She actively contributes to professional organizations including the Metabolomics Association of North America (Board Member), Metabolomics Innovation Centre, and Metabolomics Quality Assurance and Quality Control Consortium (mQACC).

Marek PetrikView profile

Associate Professor

• Reinforcement Learning
• Robust Decision Making
• Risk-Averse Optimization
• +13 more

Marek Petrik is an Associate Professor in the Department of Computer Science at the University of New Hampshire, where he is also a member of the artificial intelligence research group. Prior to joining UNH, he was a Research Staff Member at IBM’s T. J. Watson Research Center. He received his Ph.D. in Computer Science from the University of Massachusetts Amherst in 2010 under the supervision of Shlomo Zilberstein. In 2022–2023, he was a visiting faculty researcher at Google Research. Education: Ph.D. in Computer Science, University of Massachusetts Amherst, 2010 His research focuses on robust, data-driven decision making , particularly in reinforcement learning with limited data, risk aversion, and Bayesian models of uncertainty. His work spans theoretical advances in robust Markov decision processes (MDPs), policy optimization, and imitation learning, with applications in natural resource management, agriculture, renewable energy, and space systems. Recent publications emphasize provable robustness, percentile optimization, and safe offline reinforcement learning. His recent work (2023–2025) demonstrates strong trends in risk-averse reinforcement learning , robust policy gradients , offline learning under uncertainty , and Bayesian approaches to decision-making . He frequently publishes in top venues such as NeurIPS, ICML, UAI, AAAI, and journals like JMLR and Mathematics of Operations Research. Scientific Awards: Best Student Paper Award, Uncertainty in Artificial Intelligence (UAI), 2015 Marek Petrik has advised numerous students and collaborators, particularly in the areas of robust RL and safe decision-making. His research has been supported by academic and industry collaborations, including IBM and Google. He is not currently accepting new PhD students. He is actively involved in developing methods for controlling invasive species , pest monitoring , and optimizing environmental systems . Labs and Research Groups: Artificial Intelligence Research Group, University of New Hampshire Former member: Mathematical Sciences Department, IBM T. J. Watson Research Center Visiting researcher: Google Research, 2022–2023

Rebecca L. CarrierView profile

Professor

• Intestinal Tissue Engineering
• Retinal Regenerative Medicine
• Oral Drug Delivery
• +4 more

Rebecca L. Carrier is a Distinguished Professor in the Department of Chemical Engineering at Northeastern University and affiliated faculty in Bioengineering and Biology. Her research focuses on biological systems-material interactions, spanning intestinal tissue engineering, retinal regenerative medicine, and oral drug delivery. Education: PhD in Chemical Engineering from MIT (2000), BS from Rensselaer Polytechnic Institute (1995) Research Interests: Carrier’s work advances understanding of compound transport in biological systems and develops biomimetic biomaterials. Key areas include lipid impact on oral absorption, mucus barrier mechanics, and retinal/intestinal tissue engineering. The Advanced Drug Delivery Research Lab employs engineering principles to create disease models and therapeutic delivery systems. Publication Trends: Recent articles highlight interdisciplinary approaches to drug transport modeling, mucosal barrier engineering, and biomaterials for organoid culture. Studies integrate chemical engineering, microbiology, and biomedical applications. Scientific Awards: Fellow, Controlled Release Society (2024) Distinguished Faculty Award (2024) AIMBE Fellow (2018) Søren Buus Outstanding Research Award (2017) NSF CAREER Award (2008) Advising & Grants: Carrier advises PhD and capstone design students, including Ronak Ansaripour’s award-winning team. She secured NIH grants for lipid absorption studies and a Spark Fund award for algorithm-driven drug delivery optimization. Collaborations include research with University College Dublin (2024). Labs & Teams: The Advanced Drug Delivery Research Lab (ADDRES) investigates retinal cell transplantation, gut microbiome interactions, and mucosal barrier dynamics. Lab values emphasize diversity, anti-racism, and ethical scientific collaboration.

Kandler SmithView profile

Researcher

• Battery lifespan
• Battery microstructures
• Battery second use
• +5 more

Kandler Smith is a Researcher VI in Mechanical Engineering at the National Renewable Energy Laboratory (NREL), where he leads data science, modeling, and diagnostics efforts within the Electrochemical Energy Storage group. He has been with NREL since 2007, establishing himself as a key contributor to battery research and development. Smith holds a PhD in Mechanical Engineering from Pennsylvania State University, along with a Master's in Mechanical Engineering from the same institution, a Master's in Engineering Management from the University of Florida, and a Bachelor's in Mechanical Engineering from Virginia Tech. His educational background provides a strong foundation in both technical engineering principles and project management. His research focuses on advancing lithium-ion battery technology, with particular expertise in battery lifespan prediction, microstructure analysis, second-life applications, and multi-scale modeling approaches. Smith applies machine learning techniques to model identification, fast charging algorithms, and computational design of electrochemical/thermal/mechanical phenomena in batteries. His work spans energy storage systems and transportation/mobility applications, contributing significantly to the field of electrochemical energy storage. Smith maintains a robust publication record with over 200 research outputs, showing consistent growth in productivity with notable peaks in 2015 (19 publications), 2020 (21 publications), and 2022 (20 publications). His recent work demonstrates sophisticated approaches to battery technology challenges, including advanced modeling techniques and innovative material solutions. Invited to Finland by U.S. Ambassador Bruce Oreck to represent NREL and the U.S. Department of Energy in seminars and interviews (2009) NREL Distinguished Member of Research Staff Recipients (2022) NREL Outstanding Mentor Award (2014) NREL President's Award (2009) NREL Staff Award (2012) As recognized by his Outstanding Mentor Award, Smith plays an important role in developing the next generation of energy researchers. His work bridges fundamental battery science with practical applications in electric transportation and renewable energy integration, contributing to more sustainable energy solutions. His research fingerprint shows strong focus on lithium-ion batteries (100%), lithium ion battery material science (86%), and related areas including state of charge engineering and electric vehicle technology.

• Human-AI Interaction
• Explainable AI
• Ethical AI
• +5 more

Chiara Natali is a PhD Student in Computer Science at University of Milan-Bicocca (2022-present) and a Visiting Research Fellow at the Dalle Molle Institute for Artificial Intelligence USI-SUPSI, supported by a Swiss Government Excellence Research Fellowship. She serves as a Lecturer for Interaction Design Lab and Human-Computer Interaction courses at University of Milano-Bicocca, and as a Tutor for Advanced Data Management and Decision Support Systems and Human-System Interaction courses across multiple Italian universities. Her educational background includes: MA in Politics, Philosophy and Public Affairs at University of Milan (2020-2022) Master's in Digital Communication Strategy at IED, Milan (2019-2020) BSc in International Politics and Government at Bocconi University, Milan (2016-2019) Natali's research centers on the complex relationship between humans and AI systems, with particular focus on Human-AI Interaction, Explainable AI (XAI), Ethical AI, and her signature concept of Frictional AI. She investigates the multidirectional effects of AI on human cognitive faculties, examining the tension between Augmentation and Deskilling. Her work explores how intentional design friction can serve as a debiasing strategy against Automation Bias, promoting more thoughtful human-AI collaboration while preserving human agency and critical thinking. Her publication record reveals a strong emphasis on practical applications of XAI in high-stakes domains like healthcare, with particular attention to medical decision-making processes. Her research consistently addresses the challenge of designing AI systems that support rather than replace human expertise, exploring how explanations impact accuracy in hybrid decision-making and how to measure technology dominance in AI-supported environments. Her significant contributions have been recognized with: Best Paper Award at the World Conference on Explainable Artificial Intelligence (2024) Best Doctoral Consortium Award at CEUR Workshop Proceedings (2023) Natali actively shapes her field through academic service, serving as PUBLICITY & PROCEEDINGS CHAIR for HHAI 2025 and organizing multiple workshops on Human-Centred Machine Learning, Algorithmic Authority, and Frictional AI. She also contributes to gender equality in STEM as a Science Ambassador for her institution's Gender Equality Plan and previously served as PhD co-representative at the Department Board. Her interdisciplinary approach extends into creative domains, where she is developing an Interactive AI Opera on 'The Garden of (Un)Earthly AI's' funded by the University of Edinburgh's Generative AI Laboratory, and has curated projects exploring Human-AI Music Co-Creation and live-coding music performances.

Ahmed Bin ZamanView profile

Assistant Professor

• computational biology
• evolutionary computation
• artificial intelligence
• +1 more

Ahmed Bin Zaman serves as an Assistant Professor in the Department of Computer Science at George Mason University, where his research bridges computational methods with biological discovery. His academic profile emphasizes innovative approaches to protein structure prediction and optimization challenges. His educational foundation includes: PhD in Computer Science, George Mason University (2021) Master of Science in Computer Science, George Mason University (2020) Zaman's research program centers on computational biology, with specialized expertise in evolutionary computation and artificial intelligence applied to protein conformation analysis. He develops stochastic optimization frameworks to enhance protein structure prediction accuracy, focusing on conformational space mapping and decoy ensemble generation. His methodology integrates evolutionary algorithms with multi-objective optimization to navigate complex molecular landscapes, contributing significantly to template-free protein structure determination. His publication trajectory from 2017-2022 reveals distinct research phases: initial work in cybersecurity threat detection evolved into a concentrated focus on computational structural biology. Thirteen protein-related publications demonstrate consistent innovation in conformational sampling techniques, while maintaining methodological rigor through evolutionary computation and machine learning integration. Key contributions include conformation space mapping frameworks and adaptive stochastic optimization systems that address decoy diversity challenges. Professional development shows progression from industry experience at Technext Limited (as team leader/researcher) and lecturing at Metropolitan University to his current academic role. His teaching philosophy emphasizes cultivating independent problem-solving capabilities in students through cognitive tool development.

Steffi KrauseView profile

Professor

• Electrochemical Sensors
• Photoelectrochemical Imaging
• Biosensors
• +5 more

Professor Steffi Krause serves as Professor of Electroanalytical Systems and Director of Academic Standards at Queen Mary University of London's School of Engineering and Materials Science. She leads the Electrochemical Sensors Group and maintains an active research program in electrochemical imaging and sensor development. Her academic career began with a PhD from Humboldt-University of Berlin in 1994, followed by postdoctoral research at Newcastle and Glasgow Universities. She served as Lecturer and EPSRC Advanced Research Fellow at Sheffield University's Chemistry Department from 1997-2004 before joining Queen Mary's Materials Department. Professor Krause's research focuses on photoelectrochemical imaging with high spatiotemporal resolution for functional imaging of living cells. Her group has developed advanced Light-Addressable Potentiometric Sensors (LAPS) and Scanning Photo-induced Impedance Microscopy (SPIM) techniques capable of measuring local changes in surface potential and impedance. Recent work demonstrates applications in cellular imaging, particularly for monitoring cardiomyocyte action potentials, calcium ion detection, and cell surface charge mapping with submicron resolution. Her publication record spans over three decades with recent high-impact work showing a clear trajectory toward increasingly sophisticated biomedical applications. The research demonstrates strong interdisciplinary integration of materials science, electrochemistry, and biomedical engineering principles. Professional distinctions include: Member of the Royal Society of Chemistry (MRSC) Member of the International Society of Electrochemistry Fellow of the Higher Education Academy (FHEA) Professor Krause actively mentors PhD students and has successfully guided numerous doctoral candidates to completion. Her current research is supported by significant funding from EPSRC, EU Horizon 2020, and industry partners including McGowan Sensor Labs Limited. She serves as module organizer for Clinical Sensors and Measurements courses (EMS706P/EMS706U) and delivered her inaugural lecture 'Sensing to seeing: an electrochemical approach' on March 5, 2025. The Electrochemical Sensors Group maintains strong industry and international collaborations, with research directions focused on developing next-generation sensor technologies for biomedical diagnostics and environmental monitoring applications.

Janet S. DufekView profile

Professor

• Biomechanics
• Locomotion
• Injury Prevention
• +5 more

Janet S. Dufek, Ph.D., is a Professor at the University of Nevada, Las Vegas (UNLV) in the Department of Kinesiology and Nutrition Sciences . She also serves as Vice Provost for Faculty Affairs and holds adjunct appointments at the University of Nebraska at Omaha and Rocky Mountain University of Health Professions . Her career spans leadership roles including Associate Dean of the School of Integrated Health Sciences and Director of the Interdisciplinary Health Sciences Ph.D. Program . Education: Ph.D. in Biomechanics (University of Oregon, 1988) M.S. in Scientific Foundations of Kinesiology (Illinois State, 1982) B.S. (Summa Cum Laude) in Physical Education (University of Wisconsin-Superior, 1981) Research Interests focus on biomechanical mechanisms of locomotion , injury prevention , and clinical gait assessment . She specializes in jump-landing dynamics , movement variability , and performance enhancement for clinical populations , advocating for interdisciplinary approaches to solve complex health science problems. Her 15 most recent publications (2019-2024) reflect trends in concussion biomechanics , autism spectrum disorder gait analysis , machine learning applications in diabetes progression , and advanced sensor technology for movement studies . Articles explore topics from head acceleration effects on lower extremity function to weighted vest interventions in autism therapy . Scientific Awards include: Fellow, American College of Sports Medicine UW-Superior Hall of Fame (Scholar-Athlete, 2007) Membership in Phi Kappa Phi and Sigma Xi honor societies As a dedicated mentor , she supervises graduate research projects and advises on interdisciplinary health sciences . Her lab ( REBEL Research Group ) pioneers work in biomechanical injury prevention and gait variability assessment , utilizing pressure-measuring insoles and wearable inertial sensors.

• Flexible spacecraft
• Flight control systems
• Robotic systems
• +7 more

Elisa Capello is a Full Professor of Flight Mechanics at Politecnico di Torino, Department of Mechanical and Aerospace Engineering (DIMEAS). She serves as Contact person for internationalization of innovation and technology transfer, Member of the Interdepartmental Center PIC4SeR (PoliTO Interdepartmental Center for Service Robotics), and Deputy Coordinator of the Doctoral College in Aerospace Engineering. With over 100 publications, her work spans aerospace engineering, control systems, and robotics. Her research focuses on flexible spacecraft, flight control systems, robotic systems, and unmanned aerial vehicles. She designs guidance, control and navigation systems for aircraft and spacecraft, develops control systems for wind turbines and wind farms, studies flight mechanics of fixed and rotary wing aircraft, tests unmanned aerial systems, and plans mission control for autonomous systems. Her work bridges theoretical control systems with practical aerospace applications, with strong emphasis on experimental validation. Her recent publications demonstrate a strong focus on advanced control techniques for aerospace applications, particularly in UAV control, spacecraft formation flying, and robotic systems. There's a clear trend toward integrating machine learning with traditional control methods, as seen in transformer-based MPC and multimodal learning approaches. Her work spans theoretical development, simulation, and experimental validation across multiple platforms. Member of the Editorial Board of IEEE Control Systems Society (2019-) Member of the Scientific Committee - IEEE Technical Committee Aerospace Control (2016-) International FAI Judge for Helicopter Championship (2009-2015) Professor Capello supervises numerous PhD students working on topics including autonomous aerial vehicles, path planning, risk analysis, spacecraft dynamics, and control. She leads multiple research projects including CREATEFORUAS (2019-2022), Assessment of drag free control systems for L3 gravity wave observatory (2018-2019), and Guidance, Navigation and Control algorithms for in-Orbit servicing (2020-2021). Her international collaborations include institutions in the USA, Japan, and Germany. She is actively involved with the Flight Dynamics, Control and Simulation research group at DIMEAS and the DRAFT (DRones Autonomous Flight Team) at PoliTo, where she mentors students in developing autonomous flight capabilities for various applications.

Hwanhee HongView profile

Associate Professor

• Bayesian Statistical Methods
• Comparative Effectiveness Research
• Network Meta-Analysis
• +5 more

Hwanhee Hong is an Associate Professor in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine and a member of the Duke Clinical Research Institute. Affiliated with the Biostatistics, Epidemiology, and Research Design (BERD) Methods Core and the B&B Faculty, Dr. Hong maintains an active research program focused on statistical methodology development for clinical applications. Dr. Hong's educational background includes a Ph.D. in Biostatistics from the University of Minnesota (2013), an M.S. in Biostatistics from Harvard University (2010), and a B.S. in Statistics from Chung-Ang University, Korea (2008). Prior to joining Duke, they completed a postdoctoral fellowship at Johns Hopkins Bloomberg School of Public Health under Dr. Elizabeth A. Stuart. Research interests center on Bayesian statistical methods for comparative effectiveness research, network meta-analysis, causal inference, measurement error correction, and data integration across multiple sources. Their work emphasizes adaptive information borrowing to address clinical and public health questions, particularly in developing flexible Bayesian modeling frameworks that synthesize diverse data streams for evidence generation. Analysis of recent publications reveals consistent methodological focus on network meta-analysis techniques, causal inference with error-prone covariates, generalizability assessment, and time-to-event analysis. The research spans applications in pediatrics, cardiology, obesity treatment, and vaccine effectiveness, demonstrating strong translational impact across medical domains. Dr. Hong actively collaborates with biostatisticians, epidemiologists, clinicians, and health policymakers through multiple funded projects, though no formal awards or fellowships are documented in the provided materials. Participant, Faculty Success Program, National Center for Faculty Development & Diversity (2023) Participant, Faculty Curriculum on Anti-Racism, Duke Office of Faculty Advancement (2021) Teaching responsibilities include BIOSTAT 719: Generalized Linear Models. Current grant funding spans eight major projects totaling over $20 million, primarily from NIH and PCORI, addressing pediatric care coordination, mental health interventions, obesity treatment, diabetes management, and advanced biostatistical methodology development. Dr. Hong's laboratory work focuses on computational approaches for data integration, maintaining active collaborations with the Duke Clinical Research Institute and multiple external institutions including Johns Hopkins University and North Carolina State University.

Ruben SnellingsView profile

Professor

• Sustainable Metals and Minerals
• Cementitious Materials
• Mineral Carbonation
• +7 more

Ruben Snellings is a Professor at the KU Leuven , affiliated with the Institute for Sustainable Metals and Minerals and the Division of Geology . His research focuses on sustainable cementitious materials, mineral carbonation, and valorization of industrial by-products in construction. He actively contributes to RILEM technical committees, including TC 309-MCP and TC 267-TRM, establishing terminology and testing protocols for carbonation-based construction products. Research Highlights Advancing low-carbon binders through co-calcination of waste materials Investigating hydration kinetics and reactivity of supplementary cementitious materials (SCMs) Developing CO2 mineralization techniques for sustainable construction Technical Contributions Co-developing standardized R3 reactivity tests for SCMs Leading interlaboratory validation studies for binder performance Environmental Focus Reducing environmental leaching via carbonation of metallurgical slags Optimizing circular economy approaches for concrete recycling

• Dynamics, Vibration and Vibration Control
• Machine Condition Monitoring and Mechanical Engineering Asset Management
• Renewable Energy and Sustainability
• +10 more

Professor JC Ji is a distinguished academic at the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), where he was promoted to Professor on January 3, 2025, after serving as an Associate Professor since January 1, 2016. He serves as the Theme Research Director at the Centre for Audio, Acoustics and Vibration (CAAV) at UTS and is an active member of the Faculty of Engineering and Information Technology. Professor Ji holds a PhD in Mechanical Engineering from Australia and a Graduate Certificate from UTS, along with CPEng NER certification from Engineers Australia since 2018. Professor Ji's research spans multiple interdisciplinary areas with significant practical applications. His primary research interests include Dynamics, Vibration and Vibration Control (focusing on wind turbine dynamics, rotor-bearing systems, and vibration isolation); Machine Condition Monitoring and Asset Management (specializing in fault diagnostics, prognostics, and digital twin-based modeling); Renewable Energy and Sustainability (particularly in vibration-based energy harvesting and battery circular economy); Mechanical and Vehicle Systems; Robotic and Multi-Agent Systems; and Ecological Systems. His work demonstrates a strong integration of theoretical foundations with practical engineering solutions for real-world problems. Analysis of Professor Ji's recent publications reveals a clear research trajectory focused on advanced vibration control systems, condition monitoring techniques, and digital twin applications. His work increasingly integrates machine learning with traditional mechanical engineering approaches, particularly in bearing and gear health management. A significant portion of his recent research focuses on quasi-zero stiffness vibration isolators using innovative structural designs including origami-inspired mechanisms. His publications show strong international impact with numerous high-citation articles in top mechanical engineering journals. Stanford University's World's Top 2% Scientists List for both career-long impact and single-calendar year impact in 2023 and 2024 CPEng NER Chartered Engineers certification from Engineers Australia (2018-present) Professor Ji actively supervises research students and has secured substantial funding for his work, including multiple ARC Discovery and Linkage Projects. He serves as an Associate Editor for Mechanical Systems and Signal Processing (Q1 journal), Journal of Vibration and Control (Q2 journal), and International Journal of Bifurcation and Chaos (Q2 journal). He is also an active assessor for ARC grant applications since 2007 and for international funding bodies including Hong Kong RGC, Belgium FNRS, and New Zealand MBIE. His industry collaborations include projects with Zip Heaters, Alstom Transport, and Coal Services Health and Safety Trust. As Theme Research Director at the Centre for Audio, Acoustics and Vibration (CAAV) at UTS, Professor Ji leads a research team focused on advancing vibration control technologies and their applications. His laboratory work includes developing innovative vibration isolators, condition monitoring systems for industrial machinery, and energy harvesting technologies. The research group maintains strong connections with industry partners to ensure practical implementation of their theoretical advancements.

Erin ComartinView profile

Professor

• Criminal Justice Social Work
• Mental Health Interventions in Justice Settings
• Sex Offender Policy and Management
• +4 more

Erin Comartin is a Professor at Wayne State University School of Social Work, where she has served on faculty since 2016 after transitioning from Oakland University. Her scholarship critically examines social welfare policies and interventions for vulnerable populations within the criminal legal system, with particular emphasis on behavioral health needs and systemic reform initiatives. Her educational foundation includes: Ph.D. in Social Work from Wayne State University MSW from Wayne State University Post-Graduate Diploma of Arts in Community & Family Studies from University of Otago, New Zealand BA in Sociology from Oakland University Comartin's research program integrates clinical expertise from her prior work with homeless youth and domestic violence survivors to address critical gaps in justice-involved behavioral health services. She specializes in sex offender management policies, jail diversion interventions, and Behavioral Threat Assessment teams designed to prevent mass violence. Her methodological expertise spans qualitative, quantitative, and mixed-methods program evaluation with strong community engagement components. Analysis of her 15 most recent publications (2023-2025) reveals intensified focus on suicide prevention in correctional settings, overdose response systems, and law enforcement behavioral health training efficacy. Her work increasingly employs journey mapping and multi-site trial designs to evaluate systemic interventions across rural-urban divides, reflecting evolving priorities in criminal legal health services research. As principal investigator for Center for Behavioral Health and Justice initiatives, Comartin leads community-engaged projects including veteran reentry evaluations and Sequential Intercept Model implementation assessments. Her teaching portfolio encompasses advanced policy analysis, macro practice theory, and program evaluation within Wayne State's social work curriculum.