جست‌وجوی استاد و پژوهشگر

Anders Nørgaard Sørensenمشاهده پروفایل

پژوهشگر

• Bacteriophages
• Phage-host interaction
• Receptor binding proteins
• +۴ مورد دیگر

Anders Nørgaard Sørensen is a Postdoctoral Researcher at the University of Copenhagen's Faculty of Health and Medical Sciences, specifically within the Department of Veterinary and Animal Sciences and the Veterinary Clinical Microbiology section. He is actively engaged in bacteriophage research as a member of the PHAGEBio group led by Professor Lone Brøndsted. His educational background includes both a Master's and Bachelor's degree in Molecular Biology from Aarhus University. His academic training has provided a strong foundation for his current research in microbial genetics and bacteriophage biology. Sørensen's research primarily focuses on bacteriophage mechanisms, particularly examining phage-host interactions and receptor binding proteins. His expertise extends to phage engineering and CRISPR-Cas systems, with a strong emphasis on understanding and manipulating the molecular mechanisms that determine host specificity. His work has significant implications for developing alternative antimicrobial strategies against bacterial pathogens. His publication record shows a consistent output of high-impact research, with recent publications spanning from 2020-2024 in reputable journals including microLife , Frontiers in Microbiology , iScience , and Trends in Microbiology . His research demonstrates a clear trajectory toward engineering phages for targeted antimicrobial applications. Sørensen has been active in the academic community through various professional activities, including visiting researcher positions at KU Leuven (Belgium) in both 2022 and 2023, as well as at ETH Zürich (Switzerland) in 2023. He has presented his research on tail spike proteins at multiple conferences and completed pedagogical training through the Introduction to University Pedagogy course in 2023. His research is conducted within collaborative frameworks, as evidenced by his international co-authorships and visiting research appointments. The PHAGEBio group at the University of Copenhagen appears to be well-connected within the international phage research community, with collaborations spanning multiple European institutions.

Tufia C. Haddadمشاهده پروفایل

استاد

• Breast Cancer
• Experimental Therapeutics
• Clinical Trials
• +۷ مورد دیگر

Dr. Tufia C. Haddad is a Professor of Oncology at Mayo Clinic College of Medicine and Science, serving as a Consultant in the Division of Medical Oncology within the Department of Oncology. She holds leadership positions as Chair of Practice Innovation and Platform at the Mayo Clinic Comprehensive Cancer Center and Medical Director of Care at Home at the Center for Digital Health. With expertise spanning clinical oncology, research, and digital health innovation, Dr. Haddad directs her efforts toward transforming cancer care delivery through technology-enabled solutions while maintaining an active clinical practice focused on breast cancer. MD from Creighton University School of Medicine (2001) Residency in Internal Medicine at Mayo Clinic College of Medicine and Science (2004) Fellowship in Hematology, Oncology and Transplantation at University of Minnesota (2007) Dr. Haddad's research program centers on experimental therapeutics for breast cancer, particularly drug-resistant disease, with significant contributions to phase I/II clinical trial development and biomarker identification. Her work bridges traditional oncology with digital health innovation, exploring how connected health technologies and artificial intelligence can transform cancer care delivery. She has developed novel approaches to optimize endocrine therapy in breast cancer and has investigated mechanisms of resistance to targeted therapies. Her research extends to breast cancer survivorship, where she has pioneered technology-enabled models for post-treatment care. With 99 published research outputs, Dr. Haddad's scholarly work demonstrates consistent productivity with 11 publications in 2024 alone. Her research spans clinical trials, molecular mechanisms of drug resistance, digital health applications, and breast cancer survivorship. She has led significant grant-funded projects including a Congressionally Directed Medical Research Programs award targeting fatty acid synthase in drug-resistant breast cancer and National Cancer Institute-funded research on Aurora-A kinase. Multiple 'Top Performer' awards from Mayo Clinic (2020, 2022, 2024, 2025) HIMSS Future50 Clinical Leader (2021) Innovation Award from Mayo Clinic Midwest Clinical Practice Committee (2019) Multiple Excellence in Teaching Awards (2013, 2014, 2018) Best Doctors recognition by Minnesota Monthly (2015) Dr. Haddad mentors medical students, residents, and fellows while leading multiple research initiatives through her roles at the Mayo Clinic Comprehensive Cancer Center. She serves on the Health Care Delivery Scientific Program Committee of the American Society of Clinical Oncology and contributes to national efforts to transform cancer care delivery. Through her leadership in digital health innovation, she has developed remote patient monitoring programs and structured data capture systems that enhance cancer care quality and accessibility. As Director of the Practice Innovation and Platform component at the Mayo Clinic Comprehensive Cancer Center, Dr. Haddad leads initiatives that integrate cutting-edge technology with clinical care, focusing on decentralized clinical trials, connected health solutions, and artificial intelligence applications in oncology. Her work bridges the gap between traditional cancer treatment and the digital future of healthcare delivery.

• Engineering Management
• Technology Management
• Systems Thinking
• +۶ مورد دیگر

Mehran Shahhosseini is a Professor in the Applied Engineering & Technology Management department at Indiana State University's Bailey College of Engineering & Technology, currently serving as PhD Coordinator since October 2023. With over 25 years of academic experience since earning his Ph.D. in 1999, he previously directed the College from 2014-2021 and has held Graduate Faculty status since 2009 with Chair Status since 2015. His interdisciplinary career bridges engineering practice, academic leadership, and cutting-edge research in technology management. His educational foundation includes: Ph.D. in Mechanical Engineering, Lamar University (1999) M.S. in Materials Engineering, Isfahan University of Technology (1991) B.S. in Metallurgical Engineering, Tehran University (1988) Shahhosseini's research integrates systems thinking with emerging technologies, focusing on AI applications in workforce development, engineering education innovation, and quality management systems. His work pioneers concept mapping techniques for diagnostic skills training and examines AI's transformative impact on middle-skilled labor markets. Recent publications reveal a strategic shift toward practical AI implementation frameworks and curriculum modernization for technology management education, addressing critical gaps between academic preparation and industry needs. His publication trajectory demonstrates growing emphasis on machine learning applications in healthcare administration, defense systems, and sustainable materials engineering, with increasing interdisciplinary collaboration across computer science, industrial engineering, and public policy domains. This evolution reflects his commitment to solving complex real-world problems through technological innovation and educational transformation. Key recognitions include: Outstanding Faculty Council Service of Bailey College of Engineering & Technology (2023) First Destination Survey recognition for student success contributions (2020) Outstanding Supervisor Award (2018) Shahhosseini has secured over $2.5 million in competitive funding, primarily from NSF, including the $999,019 'Upskilling and Reskilling Middle-skilled Workers for Jobs Created by AI' grant and the $999,999 STARS II scholarship program. His leadership extends to advising PhD candidates, directing curriculum revisions for doctoral programs, and developing assessment tools for systems thinking evaluation. Current projects focus on AI infrastructure integration and workforce adaptation strategies. He actively shapes academic policy through service on the Faculty Affairs Committee, Strategic Planning Steering Committee, and as former Secretary of the Graduate Council, demonstrating sustained institutional commitment beyond his research and teaching responsibilities.

• Mechanical Design
• Robotics
• Uncertainty Modeling
• +۶ مورد دیگر

Nicolas Binaud is a Lecturer at Paul Sabatier University (UPS), where he is a member of the Modeling of Mechanical Systems and Microsystems group (MS2M) at Espace Clément Ader in Toulouse, France. His research focuses on multidisciplinary design in uncertain environments with emphasis on robustness, reliability, and sensitivity analysis of mechanical systems. His research interests span across: Multidisciplinary design under uncertainty Modeling of uncertainties and variations of design variables Sensitivity analyses for mechanical systems Development of performance indices for preliminary design Mechanical and computer-aided design Digital tools for mechanics Probability and reliability engineering Dr. Binaud's scholarly work demonstrates expertise in mechanical systems design with particular strength in cable-driven parallel robots, structural reliability, and predictive maintenance. His research shows strong interdisciplinary connections between mechanical engineering, aerospace applications (particularly airframe maintenance), and materials science (especially electrostatic interactions in microsystems). Analysis of his publication record reveals consistent output with recent work focusing on sensitivity analysis of robotic systems and electrostatic characterization techniques. His notable contributions include: Development of comprehensive methods for sensitivity analysis of cable-driven parallel robots Research on model-based prognostics for fatigue crack growth in aircraft structures Studies on 3D charge localization in thin dielectric materials using atomic force microscopy Applications of Kalman filtering techniques for structural health monitoring Cost-driven optimization of predictive maintenance policies for aerospace structures

• Machine Learning
• Parallel and Distributed Computing
• Graph Theory
• +۶ مورد دیگر

Giuseppe Agapito is an Associate Professor and senior research scientist at Magna Graecia University of Catanzaro, working within the Department of Law, Economics and Sociology. His academic profile spans both teaching responsibilities and active research in computational fields. His research focuses on computational intelligence techniques applied to complex real-world problems, particularly in machine learning, parallel and distributed computing, and graph theory. His work demonstrates strong interdisciplinary applications, especially in biology and omics sciences where he develops methods to leverage the vast amounts of data being produced. Agapito has published over 100 papers in international journals and conference proceedings. His recent publications show a strong focus on graph-based machine learning approaches, sentiment analysis techniques, and bioinformatics applications. His research trajectory indicates a progression from bioinformatics applications toward more general machine learning frameworks with applications across multiple domains. As an active member of the academic community, he serves as a reviewer for scientific journals and participates as chair and program committee member for national and international conferences. His editorial work for PeerJ Computer Science demonstrates his standing in the academic community. His teaching responsibilities include courses on Computer Science and Data Analysis within the Department of Law, Economics and Sociology, suggesting an interdisciplinary approach that applies computational methods to social sciences domains.

Rafael Sánchez Medranoمشاهده پروفایل

دانشیار

• Mining Engineering
• Geotechnical Engineering
• Environmental Rehabilitation
• +۲ مورد دیگر

Rafael Sánchez Medrano serves as an Associate Professor specializing in Mining Engineering and Geotechnical Safety. His research bridges regulatory frameworks, environmental rehabilitation of mining sites, and practical safety protocols for industry operations, with particular focus on Spain's Murcia region. His research interests demonstrate consistent evolution from foundational geotechnical studies (e.g., Barton-Choubey slope modeling) toward contemporary sustainability challenges. Key areas include mineral resource governance, innovative waste rehabilitation using industrial byproducts (marble sludge/pig slurry), abandoned mine risk management, and integrated safety education systems. His work uniquely connects academic theory with industry implementation through specialized training curricula for quarry operators and academic safety frameworks. Publication analysis reveals a 34-year trajectory (1989-2023) transitioning from hydrochemical modeling to 21st-century regulatory challenges. Core thematic clusters include environmental remediation (31% of output), geotechnical stability (25%), safety training systems (22%), and regional mining economics (13%), demonstrating sustained focus on practical solutions for mining sustainability. Recent work emphasizes circular economy applications in waste management and adaptive regulatory frameworks. His advising impact is reflected through industry-academia safety training programs developed for mobile machinery operators and natural stone specialists, though formal student lists aren't documented. Grant activities appear concentrated in applied research for regional mining authorities and industry rehabilitation projects, particularly in post-mining land restoration initiatives. Laboratory work centers on geotechnical testing facilities and mineral processing safety simulations, with field applications in Murcian quarries and tailing ponds. Current research trajectories indicate growing emphasis on EU regulatory compliance and climate-resilient mining practices.

Wang Ziganمشاهده پروفایل

دانشیار

• Finance
• Economics
• Applied Microeconomics
• +۱۳ مورد دیگر

Wang Zigan is a Tenured Associate Professor in the Department of Finance at Tsinghua University's School of Economics and Management, with additional appointments at the Shenzhen Institute of Economics and Management and the Institute of Innovation Management at Tsinghua University Shenzhen International Graduate School. His research spans international finance, corporate finance, and environmental economics, with a focus on empirical analysis of financial markets and corporate behavior. Education PhD in Economics, Columbia University (2009-2015) Master of Philosophy in Economics, Columbia University (2009-2012) Master of Arts in Economics, Columbia University (2009-2011) Bachelor of Economics, Tsinghua University (2005-2009) Research Focus Professor Wang's research examines critical intersections between financial markets and real economic activity. His primary expertise lies in foreign exchange dynamics, corporate investment behavior under regulatory constraints, and banking network structures. He employs advanced computational methodologies including machine learning and network analysis to address complex questions in international finance and corporate governance, with particular attention to how institutional contexts shape market outcomes. Publication Trends His recent scholarly output demonstrates a sophisticated integration of traditional finance theory with cutting-edge data science techniques. Wang's work increasingly examines how digital transformation impacts financial markets, with growing emphasis on financial technology security and high-dimensional econometric methods. His publications in premier journals including Journal of International Economics and Journal of Financial Economics reveal consistent methodological innovation while addressing fundamental questions about market efficiency and corporate decision-making. Professional Experience Assistant Professor, School of Business, The University of Hong Kong (2015-2023) Visiting Professor, State University of New York (2014) Teaching Responsibilities At Tsinghua University, Professor Wang teaches graduate-level courses including Seminars on Advanced Topics in Finance, Research on Frontier Issues in Finance, and Cryptography and Network Security. His curriculum emphasizes both theoretical foundations and practical applications of computational methods in modern finance, preparing students for careers at the intersection of finance and technology.

Rajan Dhakalمشاهده پروفایل

پژوهشگر

• Animal Nutrition
• Rumen Microbiology
• Methane Emission Reduction
• +۳ مورد دیگر

Rajan Dhakal serves as a Guest Researcher in the Department of Veterinary and Animal Sciences within the Faculty of Health and Medical Sciences at the University of Copenhagen. His research focuses on advancing sustainable livestock production through innovative studies on rumen fermentation dynamics and methane mitigation strategies using in-vitro systems. Dr. Dhakal's primary research interests include animal nutrition, rumen microbiology, methane emission reduction, and sustainable livestock production systems. He employs in-vitro rumen fermentation models to investigate how chemical compounds, Nepalese fruits, dietary oils, and direct-fed microbials influence nutrient degradation kinetics, microbial community structure, volatile fatty acid profiles, and methane output. His work bridges fundamental microbiological research with practical applications for improving feed efficiency in ruminants while reducing environmental impacts. Analysis of his recent publications (2022-2025) reveals a cohesive research trajectory centered on decoupling feed efficiency from methane production. His studies demonstrate that rumen microbiome composition does not consistently predict methane emissions, challenging conventional assumptions. Key methodological approaches include temporal monitoring of fermentation parameters with maize silage, evaluation of novel feed additives from traditional sources, and translation of in-vitro findings to calf and goat production systems. Dr. Dhakal maintains active international collaborations across multiple countries, as evidenced by his co-authorship network and external research partnerships. His work has generated significant academic engagement with 26 research outputs including 17 peer-reviewed journal articles, attracting citations on Scopus and readership on Mendeley, particularly for studies on rumen microbiome dynamics and methane mitigation strategies.

• River Engineering
• Hydraulics
• River Mechanics
• +۳ مورد دیگر

Masato Sekine is a Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, specializing in hydraulic engineering with a focus on urban flooding, river mechanics, and sediment transport. He holds a Doctor of Engineering degree from Waseda University and maintains an active research profile with numerous publications and ongoing projects. His research interests encompass River Engineering, Hydraulics, River Mechanics, and Hydroengineering, with particular emphasis on urban flood risk assessment, sediment transport in mixed-grain rivers, and levee stability. Sekine's work bridges theoretical hydraulic principles with practical urban flood management applications, especially in Tokyo's complex urban environment. Sekine's recent research output demonstrates a strong focus on urban flooding phenomena, with numerous papers analyzing flood processes in Tokyo's 23 wards, Kawasaki, and Yokohama during extreme rainfall events. His work examines the interactions between river systems, sewer networks, and urban infrastructure during flood events, providing critical insights for flood risk management in densely populated areas. Waseda University Teaching Award President's Award (2018) Japan Society of Civil Engineers Hydraulic Engineering Paper Award (2016) Japan Society of Civil Engineers Hydraulic Engineering Paper Award (2015) Japan Society of Civil Engineers Hydraulic Engineering Paper Award (2004) Professor Sekine leads several significant research projects including 'Reconstruction of sediment transport models on riverbeds consisting of materials ranging from clay to large gravels' (2020-2023) and 'Real-time prediction and management control of urban flood risk' (2017-2020). His work has practical applications for urban flood management systems and infrastructure design in Japan's densely populated coastal regions.

• Cardiovascular Biology
• Computational Drug Discovery
• Epigenetics
• +۳ مورد دیگر

Dr. Tom Karagiannis serves as an Adjunct Research Fellow at the Baker Department of Cardiovascular Research, Translation and Implementation within La Trobe University's Faculty of Health Sciences. His research bridges computational biology and cardiovascular/diabetes pathophysiology through advanced in silico methodologies. His primary research interests focus on Cardiovascular Biology , Computational Drug Discovery , and Epigenetics , with significant contributions to understanding SARS-CoV-2 mechanisms, diabetes-related cellular regeneration, and hypertension pathways. His work frequently employs molecular dynamics simulations, structural modeling, and epigenetic modifier investigations to address complex biomedical challenges. Analysis of his 15 most recent publications (2023-2025) reveals a dominant research trajectory centered on viral pathogenesis (particularly SARS-CoV-2 spike protein dynamics and antiviral targeting), epigenetic regulation in diabetes (EZH2 inhibitors for β-cell regeneration), and computational pharmacology (mineralocorticoid receptor antagonists for hypertension). His publications consistently integrate structural biology with disease mechanisms across cardiovascular, metabolic, and infectious disease domains. Scientific contributions include: 185 total research outputs with significant citations in high-impact journals Key publications in Journal of the American Society of Nephrology (12 citations), Signal Transduction and Targeted Therapy (19 citations), and Computers in Biology and Medicine (22 citations) Frequent collaborations with researchers including Pitsillou E, Liang JJ, and Hung A His academic service includes editorial contributions to specialized fields such as sulforaphane research in Frontiers in Nutrition. While no formal advising roles or grant details are documented in available materials, his extensive publication record demonstrates active engagement in collaborative biomedical research projects with translational implications for cardiovascular disease, diabetes, and antiviral development.

• Flood Risk Management
• Hydraulic Structures
• Dam Safety
• +۵ مورد دیگر

Sebastiaan N. Jonkman is a full Professor in Hydraulic Structures and Flood Risk at Delft University of Technology's Faculty of Civil Engineering & Geosciences. His research focuses on flood risk assessment, hydraulic infrastructure reliability, and climate adaptation strategies for flood-prone regions. He leads major research initiatives including the NWO Perspectief-funded Future Flood Risk Management Technologies (Future FRM Tech) program addressing flood-resilient landscapes and innovative coastal/riverine solutions. Jonkman's research spans dam safety, flood modeling, and infrastructure vulnerability, with significant contributions to understanding flood fatalities through global analyses (1975-2022). His work integrates engineering, climate science, and policy development, particularly for the Netherlands' complex water management challenges. Recent projects examine healthcare facility resilience during floods and multi-scale AI applications for flood prediction. His scientific contributions include over 335 research outputs and 14 datasets, with notable recognition for Dutch coastal flood risk management approaches applicable to Venice. Media engagement shows extensive public communication through NOS, NPO Radio, and print media on topics including sea-level rise adaptation, flood protection alternatives to sandbags, and lessons from the 1953 North Sea flood. NWO Perspectief grant for Future FRM Tech program Leadership in 5-year healthcare flood preparedness project Texas A&M University research collaboration on storm surge barriers Contributions to open letters on urgent sea-level rise strategy Jonkman actively supervises research and contributes to national water policy through committee memberships including gemeente Molenlanden. His work bridges academic research with practical flood risk management solutions for Dutch and international contexts.

Kexin Peiمشاهده پروفایل

استادیار

• Security
• Software Engineering
• Machine Learning

Kexin Pei is a Neubauer Family Assistant Professor at the Department of Computer Science, University of Chicago. She received her PhD from the Department of Computer Science at Columbia University. Her academic career spans research and teaching in the fields of Security, Software Engineering, and Machine Learning. Her educational background includes: PhD in Computer Science from Columbia University Dr. Pei's research interests focus on developing data-driven program analysis to improve the security and reliability of both traditional and AI-based software systems. She is particularly interested in creating machine learning models that can reason about program structure and behavior to precisely and efficiently analyze, detect, and fix software bugs and vulnerabilities. Her work bridges the gap between theoretical computer science and practical security applications, with significant contributions to binary analysis, program understanding, and AI security. Her research output shows a strong trend toward integrating machine learning with traditional program analysis techniques. Many of her recent publications explore how neural networks and language models can enhance software security and reliability, particularly in binary analysis, vulnerability detection, and code understanding. Her work often involves developing novel frameworks that combine execution traces, code structure, and semantic understanding to create more robust analysis tools. Dr. Pei has received several prestigious awards for her research: Best Paper Award at MASEC@NeurIPS 2023 Best Paper Award Runner-Up in CSAW 2018 Top-10 Finalist of Applied Research Competition ACM SigMobile Research Highlight MLSec @NIPS'17 CACM research highlight Distinguished Artifact Award at FSE 2016 Dr. Pei actively mentors students and has advised several PhD and Master's students. Her group includes PhD students Jie Zhu, Weichen Li, and Jun Yang (with Shan Lu), as well as MS students Sam Huang and Yiming Cheng (with Junchen Jiang). She has also worked with numerous student collaborators and visiting students from institutions including MIT, Georgia Tech, and UChicago. Her research has been supported by grants from various sources, including collaborations with Google DeepMind and Microsoft Research where she completed internships. Dr. Pei is involved in several research labs and teams, including collaborations with the CUMLSec group (as seen in repositories like trex and XDA on GitHub). Her work often involves interdisciplinary teams combining expertise in security, machine learning, and software engineering to tackle complex problems in program analysis.

• Mathematical modeling
• Cell motility
• Agent-based modeling
• +۶ مورد دیگر

Professor Franziska Matthäus is a theoretical biologist at Goethe University Frankfurt and a Fellow at the Frankfurt Institute for Advanced Studies (FIAS). Her research focuses on mathematical modeling of spatiotemporal processes in biological systems, particularly cell motility and pattern formation. She leads an active research group within the Life- and Neurosciences department, collaborating extensively with experimental partners to develop models that bridge microscale cellular processes with population-level behavior. Dr. Matthäus earned her doctorate summa cum laude from the University of Warsaw in 2005 after studying biophysics at Humboldt University of Berlin. She held postdoctoral positions at the University of Heidelberg, where she became head of the research group "Complex Biological Processes" in 2011. In 2016, she accepted a junior professorship at the University of Würzburg before joining Goethe University Frankfurt and FIAS, where she currently holds a Giersch endowed professorship. Her research employs agent-based models, partial differential equations, and image analysis techniques to study cell motility, pattern formation, and tissue dynamics. Her group develops mathematical models describing individual cells and large cell populations, incorporating internal signaling processes and interactions with chemical and mechanical environments. Current projects investigate embryo development, cancer cell migration, organoid dynamics, and pattern formation in biological systems. They use advanced computational methods including GPU implementations for efficient simulations and have developed specialized tools like a Julia package for 3D particle image velocimetry. Professor Matthäus has organized significant academic initiatives including "The Beauty of Theoretical Biology" project with Springer Publishing, which collects scientific images from theoretical biology research for publication and exhibition. Her publication record shows consistent output across mathematical biology, with recent work focusing on vertex models, pattern formation mechanisms, and advanced image analysis techniques for studying cellular dynamics. Giersch endowed professorship at Goethe University She actively supervises PhD students including Camile Kunz, Zoë Lange, Tim Liebisch, Marc Pereyra, and Rutian Zhou, guiding them in research projects that combine mathematical modeling with biological applications. Her teaching includes courses in computational biology, bioinformatics, and theoretical biology for both bachelor's and master's students at Goethe University. She offers specialized modules in the Physical Biology of Cells and Cell Interactions (PBioC) program, emphasizing hands-on research experience with data analysis, modeling, and simulation techniques. Professor Matthäus maintains strong international collaborations and has contributed to numerous interdisciplinary research projects, particularly those bridging mathematics, physics, and biology. Her work has applications in understanding metastasis formation, parasite-host interactions, and embryonic development processes.

• Computational Chemistry
• Structural Bioinformatics
• Chemoinformatics
• +۵ مورد دیگر

Dr. Bono Lučić is a Senior Research Associate and Professor at the Ruđer Bošković Institute's NMR Centre in Zagreb, Croatia. He holds an honorary Associate Professor position at J. J. Strossmayer University in Osijek since 2022 and teaches PhD courses in Structural Bioinformatics at multiple Croatian institutions. His educational background spans Electronics (B.Sc.), Physics (M.Sc.), and Chemistry (Ph.D.), creating a unique interdisciplinary foundation. His research focuses on computational approaches to structural bioinformatics, chemoinformatics, and free radical chemistry, with emphasis on protein modeling, molecular descriptor development, and antioxidant mechanisms. Lučić's publication record shows consistent output in computational chemistry and bioinformatics, with recent work emphasizing machine learning applications in toxicity prediction, solubility modeling, and kinase inhibitor target mapping. His research demonstrates strong methodological development in QSAR modeling and validation techniques. Associate Professor (honorary) at J. J. Strossmayer University (2022) Member of IUPAC Committee on Publications and Cheminformatics Data Standards (2012-2019) President of Croatian Biophysical Society (2022-) As a mentor, he has supervised two PhD dissertations, one MSc thesis, and three BSc theses across physics, chemistry, and pharmacy disciplines. His editorial roles include membership on the Editorial Board of Croatica Chemica Acta (2000-) and Editor position (2011-). He has co-edited special journal issues honoring prominent scientists like Nenad Trinajstić and Douglas Jay Klein.

• Bioinformatics
• Genomics
• Metagenomics
• +۵ مورد دیگر

Bent Petersen serves as a Senior Researcher at the Section for Hologenomics within the Globe Institute at the University of Copenhagen. With over 13 years of professional experience in Bioinformatics, he is a key member of the Computational Biodiscovery group where he applies machine learning techniques to projects focused on deciphering the medicinal potential of the Rainforest. His primary expertise lies in genomics and metagenomics with extensive work involving Next Generation Sequencing data analysis. His educational background includes: PhD in Bioinformatics from the Technical University of Denmark (DTU), with dissertation on "Prediction of protein structural features by use of artificial neural networks" (2011) Master's degree in Biotechnology from DTU, with thesis on "Prediction of local structural elements by use of artificial neural networks" (2007) Petersen's research interests span multiple cutting-edge fields including bioinformatics, genomics, metagenomics, machine learning applications in biology, and the study of host-microbiota interactions. His work bridges computational approaches with biological discovery, particularly in areas related to rainforest biology, phage therapy, and agricultural microbiome research. He actively collaborates with scientific groups worldwide to expand research portfolios in NGS, phage biology, rainforest biology, supercomputing, and machine learning applications. With 76 research outputs including journal articles, letters, and preprints, Petersen's publication record shows a strong focus on genomic analyses across diverse biological systems - from African hunting dogs and Galápagos plants to agricultural systems and microbial communities. His recent work demonstrates particular interest in host-microbiota interactions, phage therapy applications, and the genomic basis of plant domestication and adaptation. Petersen has significant teaching experience, having previously served as Head of Studies at DTU. He is recognized for his excellent educational skills and has conducted international mobile workshops in NGS, metagenomics, and bioinformatics across Brazil, China, Colombia, Egypt, India, Malaysia, and the Faroe Islands. His external positions include Adjunct Lecturer and Deputy Director at the Asian Institute of Medicine, Science and Technology, as well as Editorial Board Member for Scientific Reports since 2017. He is actively involved in research collaborations worldwide and serves as a member of the Chairmanship of the Biological Corps for external examiners (Censorkorpset) since 2019. His ORCID identifier is 0000-0002-2472-8317, and his research has been referenced across multiple platforms including news outlets, social media, and academic readership services.