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Bahram ParvinView profile

Professor

• Cancer Therapeutics
• Computational Biology
• Medical Imaging
• +3 more

Bahram Parvin is a Professor at the University of Nevada, Reno, with a laboratory at Lawrence Berkeley National Laboratory (LBNL). His work focuses on developing novel cancer therapeutics through epithelial-stromal signaling research and creating computational methods to identify tumor heterogeneity biomarkers. He teaches courses in Bioimaging, Tissue Engineering, Deep Learning, and Digital Signal Processing (DSP), bridging interdisciplinary research between biomedical and computational domains. Research Interests: Cancer therapeutics, tumor heterogeneity, 3D cell culture models, deep learning for medical imaging, and computational biology. Awards: Received an R&D100 Award in 2014 for BioSig3D, a pioneering system for high-content screening of 3D cell culture models. Key Contributions: BioSig3D, CSTA-NET, MAT3D, and algorithms for nuclei segmentation in histology images. His recent publications (2025–2014) emphasize advancements in 3D medical image analysis, particularly in oncology and histopathology. Parvin’s work combines experimental and computational approaches to address challenges in tumor profiling and cellular imaging.

Mark LudwigView profile

Researcher

• Sports Communication
• Media and Sports
• Visual Communication
• +7 more

Dr. Mark Ludwig is a researcher at the Institute for Communication and Media Research at the German Sport University Cologne. He is actively involved in research on sports communication, media in sports, visual communication, and sports scandals, with a strong publication and project portfolio. His work spans academic research, teaching, and public engagement. German Sport University Cologne – Institute for Communication and Media Research Mark Ludwig’s research focuses on the intersection of media and sports, particularly in digital environments. His work explores audience behavior, visual design in broadcasts, and the social impact of sports scandals. He investigates how media shapes public perception of sports and how platforms like Instagram are used by sports organizations and journalists. His research integrates communication theory, psychology, and media studies, contributing to both academic knowledge and practical applications in sports media. The recent publications of Mark Ludwig highlight a consistent focus on visual and digital aspects of sports media. Themes include Instagram use in sports journalism, visual parameters in live broadcasts, and media coverage of scandals. His work combines empirical research with theoretical analysis, often in collaboration with colleagues. The articles reflect interdisciplinary trends, bridging communication, psychology, and sports sociology. Mark Ludwig has received several academic honors: Best Paper Award of the Visual Communication Section of the German Society for Journalism and Communication Studies (DGPuK), 2012 Teaching Award of the German Sport University Cologne (1st place in Seminars category), 2017 Offermann-Hergarten-Preis for his dissertation, University of Cologne, 2011 Dr. Ludwig has supervised and collaborated on multiple research projects, often funded by third parties or self-financed. He has served on academic committees, including the Commission for Quality Improvement in Teaching and Studies. He regularly participates in national and international conferences such as ICA and DGPuK, and engages in peer review and guest lectures. His work demonstrates a strong commitment to both research excellence and educational quality. Mark Ludwig is involved in collaborative research networks, particularly with scholars like Inga Oelrichs and C. Bertling. He contributes to academic governance through committee membership and is active in professional associations related to communication and sports. His research projects often involve interdisciplinary teams and focus on contemporary issues in sports media.

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +7 more

Xinchao Wang is an Assistant Professor and Presidential Young Professor in the Department of Electrical and Computer Engineering at the National University of Singapore (NUS), College of Design and Engineering. He leads the xML Lab, focusing on machine learning and artificial intelligence. Prior to joining NUS, he was an Assistant Professor at Stevens Institute of Technology in the Department of Computer Science and a Postdoctoral Researcher at the Beckman Institute, University of Illinois Urbana-Champaign, under the late Professor Thomas Huang. He earned his Ph.D. in Computer Vision from École polytechnique fédérale de Lausanne (EPFL) under Professor Pascal Fua and a B.Sc. in Computing from the Hong Kong Polytechnic University with first-class honors and a perfect GPA. His research spans machine learning, computer vision, and artificial intelligence, with a focus on diffusion models, vision-language models, 3D generation, and dataset distillation. His recent publications demonstrate strong trends in efficient generative modeling, including acceleration techniques for diffusion models, 3D scene reconstruction, and novel architectures for vision and language tasks. His work frequently appears in top-tier conferences such as CVPR, NeurIPS, ICCV, ECCV, and ICLR. AI's 10 to Watch, IEEE (2025) Young Research Award, NUS (2025) Young Research Award, NUS CDE (2024) Best Paper Award, IEEE VCIP 2022 Outstanding Early Career Award, NUS CDE (2023) College Teaching Excellence Award, NUS CDE (2023) He actively advises Ph.D. students, many of whom have received prestigious awards including the Google Fellowship and ByteDance Scholarship. He has served as an Associate Editor for IEEE Transactions on Image Processing since 2023. His lab is actively recruiting Ph.D. students, postdocs, visiting scholars, and research assistants in machine learning and AI. He teaches core courses at NUS including Introduction to Machine Learning, Deep Learning, and Pattern Recognition.

Tevfik DemirciftciView profile

Assistant Professor

• Revenue Management
• Hospitality Technology
• Tourism Management
• +5 more

Tevfik Demirciftci serves as Assistant Professor of Hospitality Management at Colorado Mesa University, bringing dual PhD credentials in Hospitality Administration (University of Nevada Las Vegas) and Tourism Management (Istanbul University), plus an MSc in Hospitality Management from the University of Delaware. His academic appointment is housed within the university's hospitality programs despite no explicitly stated college/school affiliation. His educational journey features: PhD in Hospitality Administration, University of Nevada Las Vegas PhD in Tourism Management, Istanbul University MSc in Hospitality Management, University of Delaware Demirciftci's research centers on revenue management systems, hospitality technology adoption, and consumer behavior analysis within casino/hotel operations. He investigates critical gaps between academic curricula and industry requirements in revenue management, while pioneering methodologies like LIWC text analysis of online reviews and conjoint analysis for pricing strategies. His work consistently bridges theoretical frameworks with practical applications in luxury hospitality segments. Analysis of his 15 most recent publications reveals three dominant research trajectories: (1) Technology integration through IoT, robotics, and AI in guest experiences; (2) Revenue management optimization for casino buffets and luxury hotels using behavioral data; (3) Destination competitiveness studies for MICE and golf tourism with emphasis on Istanbul's market dynamics. These streams demonstrate methodological diversity spanning quantitative modeling, sentiment analysis, and cross-cultural comparisons. Professional recognition includes Microsoft Office Expert certification in Excel, though no major scientific awards or fellowships appear in current records. His industry experience informs practical research approaches without formal grant disclosures. With 22 years of hands-on industry experience across MGM, Marriott, and Ritz-Carlton properties in Bahrain, Turkey, and the US, Demirciftci maintains strong industry-academia connections. While graduate student supervision isn't documented, his publications suggest collaborative research networks across international institutions. His professional practice focuses on translating revenue management theory into operational solutions for complex hospitality environments. No dedicated research laboratories or formal teams are mentioned, though his publications indicate frequent international collaborations, particularly with Turkish and US-based scholars in hospitality technology and destination marketing fields.

Ahmed AliaView profile

Researcher

• Artificial Intelligence
• Deep Learning
• Crowd Dynamics
• +3 more

Ahmed Alia is a researcher at Forschungszentrum Jülich GmbH, affiliated with the Institute for Advanced Simulation (IAS) and specifically the Civil Safety Research (IAS-7) department. His work focuses on applying artificial intelligence and deep learning to complex data analytics, with a strong emphasis on crowd dynamics and safety in public spaces. Education: PhD in Artificial Intelligence from the University of Wuppertal (2024) Alia's research develops intelligent frameworks for analyzing crowd behavior, including pushing detection in videos, real-time trajectory prediction, and dataset creation for deep learning applications. He employs machine learning, large language models, and visualization techniques to model pedestrian interactions and improve safety at event entrances and railway platforms. His publications highlight a trend toward integrating deep learning with social psychology and civil engineering principles, creating systems for early pushing detection in crowded environments, 3D motion analysis, and benchmark datasets like RPEE-Heads. These works have been published in journals such as Complex & Intelligent Systems , IEEE Access , and Frontiers in Social Psychology . Scientific Awards: Best Presenter Award at CompAuto 2023 Alia contributes to projects including CrowdDNA, CroMa, and Pushing in Crowds, collaborating with teams like PeTrack on optical head tracking software. His work bridges technical innovation with behavioral insights to address safety challenges in dense public spaces.

HAYRİ ABARView profile

Associate Professor

• Quantitative Decision Methods
• Data Analytics
• Heuristic and Metaheuristic Techniques
• +5 more

Associate Professor Hayri Abar is affiliated with Gaziantep University , Faculty of Economics and Administrative Sciences, Department of Economics and Department of Economic History. His career spans institutions including Atatürk University and University of Gent (post-doctoral 2024). Active in Quantitative Decision Methods , Data Analytics , and Heuristic Techniques , he integrates econometric rigor with real-world policy applications. Doctorate in Econometrics (Atatürk University, 2014) Master’s in Economic Theory (Atatürk University, 2011) Bachelor’s in Statistics & Computer Sciences (Karadeniz Technical University, 2007) Post-Doctoral Research (University of Gent, 2024) Abar’s research bridges financial econometrics and public health economics , with recent work applying Multivariate Probit models to mental health policy and machine learning to stock price forecasting. His 20 articles emphasize Turkey case studies in tobacco consumption, migration patterns, and energy economics. Key trends: Integration of LSTM/ML with traditional econometric models Focus on regional disparities in health and economic outcomes Policy-oriented spatial econometrics applications Analysis of ICT adoption and housing demand determinants Advising spans PhD and Master’s theses on topics like health expenditures, stock market volatility, and gender-based violence. Projects include technology-enhanced econometrics education and regional migration studies under national funding.

• place marketing
• tourism marketing
• branding strategy
• +7 more

António Joaquim Araújo de Azevedo is an Associate Professor at the Department of Management, School of Economics and Management, University of Minho, Portugal. His academic career spans over two decades, focusing on marketing and tourism-related research. PhD in Management Sciences (2003, University of Minho) BEng in Chemical Engineering (1989, University of Porto) His primary research interests include place marketing , tourism marketing , branding strategy , consumer behavior , and crisis communications . His work often intersects with sustainable tourism , destination branding , and digital marketing applications. Recent publications analyze therapeutic landscapes , lighthouse tourism , servitization in business , and celebrity endorsement . Articles frequently employ geotagged photo analysis , case studies , and content analysis methodologies. António has secured research contracts and grants from Fundação para a Ciência e a Tecnologia (2021-2025) and participated in earlier doctoral grants (1998-2003). He actively contributes to academic peer review for journals in marketing , tourism , and sustainability domains.

• Sound Recognition
• Deep Neural Networks
• Ontology Development
• +7 more

Yeni Plasencia Calaña is an Assistant Professor at the Faculty of Science and Engineering , Maastricht University, and affiliated with the Institute for Digital Smart Society and Brightlands Institute for Smart Society (BISS) . Her research focuses on sound recognition, deep learning, ontology development, and biometric identification systems. University: Maastricht University School: Faculty of Science and Engineering Rank: Assistant Professor Her research integrates semantic modeling with deep neural networks , particularly in auditory perception and face recognition. Recent work includes ontologies for everyday sounds and human-aware AI in educational assessment. Key publication areas include: 2023-2025: Automated essay scoring and sound recognition via semantic deep learning 2022: Taxonomies of everyday sound semantics 2018: Persistent homology for gait recognition and metric learning 2016-2017: Dissimilarity space methods for face recognition and chemical data Scientific recognition includes the 2024 NWO-SGW Open Competition grant for the project "Am AI right?", emphasizing ethical and legal AI integration. She actively contributes to academic events, co-organizing the 2021 Women in Data Science Maastricht Conference . Her work spans applied machine learning, from low-resolution imaging to semantic modeling.

• Swimming Biomechanics
• Sports Performance Analysis
• Training Protocols in Swimming
• +3 more

Dr. Gracia López Contreras is a Full Professor at the University of Granada's Faculty of Sports Sciences, specializing in the Department of Physical Education and Sports. Her research focuses on swimming biomechanics, performance analysis, and training protocols, with particular emphasis on load-velocity profiling, underwater undulatory swimming, and postactivation potentiation. Key research areas: Swimming kinematics, force application analysis, detraining effects Recent work: Comparative studies on sprint swimming, thermal physiology in aquatic environments Methodological contributions: Development of technical evaluation rubrics, service-learning integration Her publications span biophysical analysis, adaptive swimming, and competitive performance optimization. She has supervised tutoring sessions at the university pool facility and contributed to swimmer performance assessments at major events like the European Swimming Championships.

Edward AvezovView profile

Professor

• Neuroscience
• Cell Biology
• Dementia Research
• +4 more

Edward Avezov serves as a Professor and Group Leader in the Department of Clinical Neurosciences at the University of Cambridge's School of Clinical Medicine. He is affiliated with the UK Dementia Research Institute and Cambridge Neuroscience, focusing on neuronal cell biophysics within the research themes of Neurons, Circuits and Networks, Beyond the Neuron, and Lifelong Brain Development and Brain Ageing. His research investigates endoplasmic reticulum (ER) structure-function relationships in neuronal physiology and dementia pathogenesis. Avezov's laboratory employs advanced techniques including super-resolution microscopy, genetically encoded biosensors, iPS cell models, and computational modeling to study organelle interactions, cellular neurophysiology, and protein homeostasis. Key clinical conditions under investigation include Alzheimer's disease, hereditary spastic paraplegia, and motor neurone disease. Analysis of Avezov's publication record reveals a consistent focus on ER dynamics in neurodegeneration. His work demonstrates how ER morphology regulation (e.g., via RTN4), luminal transport mechanisms, and stress responses contribute to neuronal dysfunction in dementia. Recent publications highlight innovative methodological developments like ERnet for quantitative ER topology analysis and discoveries regarding ER-mitochondria crosstalk, calcium signaling limitations, and stress-induced protein disaggregation. Avezov maintains active collaborations with leading Cambridge researchers including Michele Vendruscolo, Cahir O'Kane, John Skidmore, Clemens Kaminski, Gabriele Kaminski Schierle, David Rubinsztein, and David Klenerman. His laboratory actively participates in neuroscience community events such as NeuroBioUK and CellBio conferences, as evidenced by their social media presence.

Marta Perlado Lamo de EspinosaView profile

Professor

• Media Planning
• Audience Research
• Digital Communication
• +3 more

Marta Perlado Lamo de Espinosa is a Professor and Dean of the Faculty of Communication and Arts at Nebrija University since 2013. She holds a PhD in Information Sciences from Complutense University of Madrid (1999) and a degree in the same field (1989). Since December 2024, she has directed the BELSILVER Chair (Nebrija-L'Oréal Group), focusing on communication, image, and well-being for the Silver Generation. Her career spans 30 years at Nebrija University, with additional teaching roles at Complutense University of Madrid. Education : PhD in Information Sciences (Cum Laude), Complutense University of Madrid (1999) Degree in Information Sciences (Advertising and Public Relations), Complutense University of Madrid (1989) Expert Diploma in Senior University Management, Nebrija University (2015) Her research focuses on media planning, audience research, digital communication, and professional profiles in the digital society. She leads studies on the Silver Generation's communication behaviors and digital competencies for disabled individuals. Her work includes projects like COMPENSA (digital employability for disabled people) and TICOMCOR (communication education in Spain). Article trends show expertise in digital media transformation, social audience dynamics, AI applications in communication , and inclusive education . She has authored/co-authored books such as "Mass Media Planning" and "Audiences and Digital Media: Beyond Data." Academic Leadership : Dean, Faculty of Communication and Arts (2013-present) Director of BELSILVER Chair (2024-present) Former Head of Advertising Studies and Director of Advertising and Marketing Department

Sven LončarićView profile

Professor

• Computer Vision
• Image Processing
• Medical Imaging
• +5 more

Academician Professor Sven Lončarić serves as a Full Professor in the Department of Electronic Systems and Information Processing at the Faculty of Electrical Engineering and Computing, University of Zagreb. With his office located in room D-119 and contactable via phone at 6129-891, he maintains an active presence in both teaching and research activities within the institution. His work bridges theoretical computer science with practical applications across multiple domains. Professor Lončarić's research spans computer vision, image processing, and deep learning with significant contributions to medical imaging, particularly in retinal analysis using optical coherence tomography. His work in color constancy and illumination estimation has advanced techniques for handling multi-illuminant scenes, while his research in ultrasound image analysis has practical applications in non-destructive testing. He also explores computer security aspects of machine learning models, particularly in backdoor detection and removal. His recent publications demonstrate a strong trend toward applying deep learning techniques to solve complex problems in medical imaging, retail automation, and industrial applications. The concentration of work in retinal imaging and color constancy shows his commitment to advancing computer vision fundamentals while simultaneously addressing practical challenges in healthcare and industry. His research increasingly incorporates anomaly detection methods and robust security practices for machine learning systems. Professor Lončarić actively contributes to the academic community through organizing events like the Croatian Computer Vision Workshop and the First Croatian Symposium on Artificial Intelligence, providing platforms for knowledge exchange in his fields of expertise. His work on astronomical data processing demonstrates the versatility of his methodological approaches across diverse scientific domains. Within the Department of Electronic Systems and Information Processing, he participates in the Center of Excellence for Computer Vision, contributing to the institution's research profile in artificial intelligence and computer vision. His work on medical imaging applications connects the faculty with healthcare institutions, facilitating interdisciplinary collaborations that translate technical advances into medical practice.

• Optimization
• Data Analytics
• Metaheuristic Methods
• +10 more

Professor Regina Berretta is an Honorary Professor at the University of Newcastle's School of Information and Physical Sciences, specializing in Computing and Information Technology. With expertise spanning computer science, mathematics, and applied optimization, she has established herself as a leading researcher in metaheuristic methods for solving complex combinatorial problems. Currently serving as a Chief Investigator at the ARC Training Centre for Food and Beverage Supply Chain Optimisation, she applies her mathematical modeling skills to address critical challenges in food industry supply chains, with the Centre receiving over $2 million in funding to train next-generation researchers. Professor Berretta earned her PhD, Master of Engineering (Electrical), Bachelor of Mathematics, and Teachers Certificate from Universidade Estadual de Campinas in Brazil. Her educational background in computational and applied mathematics has provided the foundation for her extensive research career focused on integer programming and metaheuristic approaches to optimization problems. Her academic journey includes progression from Lecturer at the University of Newcastle (2003-2007) to various leadership positions including Head of Discipline of Computer Science and Software Engineering (2011-2014) and Assistant Dean of Equity, Diversity and Inclusion (2019-2022). Her research expertise centers on the design of mathematical models and development of efficient computational techniques to tackle large and complex combinatorial optimization problems across diverse application areas. Professor Berretta has made significant contributions to bioinformatics through her work on genetic signature identification from gene expression datasets, and to supply chain optimization through her research on perishable food inventory management, lot sizing, and scheduling problems. Her methodological specialties include memetic algorithms, evolutionary computation, and integer programming approaches that have proven effective for problems that are otherwise computationally intractable. Analysis of her recent publications reveals a strong interdisciplinary focus, with optimization techniques increasingly applied to food supply chain challenges while maintaining connections to bioinformatics applications. Her work demonstrates a consistent pattern of translating theoretical optimization methods into practical solutions for industry problems, particularly in the agricultural sector. Additionally, her more recent publications show growing engagement with gender equity issues in STEM fields, reflecting her leadership in relevant initiatives. Co-founder of HunterWISE, promoting girls and women in STEM Leader of Google CS4HS project for five consecutive years Recipient of over $4 million in research funding through 35 grants Author of more than 80 papers and book chapters Chief Investigator at ARC Training Centre for Food and Beverage Supply Chain Optimisation Professor Berretta has demonstrated exceptional leadership through her administrative roles and community initiatives. As co-founder of HunterWISE, she has developed a comprehensive approach to increasing female participation in STEM through school programs and professional networking events. Her leadership of the Google CS4HS project has directly impacted high school computer science education in the Hunter region. Her research collaborations span multiple disciplines and institutions, reflecting her ability to bridge theoretical computer science with practical industry applications, particularly in the food supply chain sector where her optimization models have demonstrated significant cost and waste reduction potential.

Marie-Françoise LacassagneView profile

Professor

• Social Psychology
• Sports Management
• Discrimination
• +4 more

Marie-Françoise Lacassagne is a Professor at Université de Bourgogne and Director of the Socio-Psychology and Sports Management Laboratory (SPMS). Her research focuses on identities and identity management strategies , particularly in the contexts of partitions, discrimination, language, and sports . She employs interdisciplinary approaches blending social psychology, sociolinguistics, and sports management to analyze intergroup dynamics and communication patterns. Academic Rank: Professor University: Université de Bourgogne Research Fields: Social Psychology, Discrimination, Sports Sociology, Identity Studies Email: marie-francoise.lacassagne@u-bourgogne.fr Lacassagne's work spans three phases: early studies on language's role in cognitive alienation, mid-career exploration of racial and intergenerational discrimination, and recent focus on sports-related identity strategies. She has collaborated internationally on projects like the 62-nation GLOBE leadership study and France-Morocco comparative analyses of sports representations. Her methodological innovations include discourse analysis, social representation theory, and psychosocial semiology frameworks. Key article trends reveal interdisciplinary engagement with topics like fan group violence , racial categorization in soccer academies , parental involvement in youth sports , and linguistic markers of discrimination . These works highlight how identity partitions (statutory, oppositional, communal) manifest in sports contexts, linking them to broader sociocultural phenomena. Her research perspectives aim to integrate subordinate (individual), intermediate (social), and supr-ordinate (cultural) identity levels within sports frameworks. This includes studying how victory/defeat cycles influence identity strategies and how intergroup discourse shapes social cohesion or conflict in athletic environments.

Nikita AraslanovView profile

Researcher

• Computer Vision
• 3D Reconstruction
• Semantic Segmentation
• +3 more

Dr. Nikita Araslanov is a Postdoctoral Researcher at the Technical University of Munich (TUM) in the School of Computation, Information and Technology, Department of Informatics 9 (Computer Vision Group). He also serves as a visiting faculty member at Google. His research focuses on semantic and 3D visual inference from video data, aiming to bridge perception and understanding in complex visual scenes. Dr. Araslanov earned his PhD in Computer Science from TU Darmstadt in the Visual Inference Lab, graduating with highest distinction. He holds a Master's degree in Computer Science from the University of Bonn, where he graduated with distinction in 2016. His research spans multiple areas of computer vision, with a particular emphasis on 3D reconstruction, semantic segmentation, and deep learning approaches for visual understanding. His work often combines theoretical insights with practical applications, addressing challenges in dynamic scene understanding, vision-language correspondence, and unsupervised learning paradigms. He has made significant contributions to bundle adjustment for dynamic scenes, hierarchical semantic segmentation using hyperbolic geometry, and novel approaches to unsupervised panoptic segmentation. Dr. Araslanov's research has been recognized with several prestigious awards, including being selected as a Best Paper Candidate at ICCV 2025 for his work on dynamic scene reconstruction, and having his Scene-Centric Unsupervised Panoptic Segmentation paper designated as a Highlight Paper at CVPR 2025 (top 3% of submissions). He has also received multiple oral presentation awards at major computer vision conferences including GCPR 2024, CVPR 2024, and ICLR 2024. Actively involved in the academic community, Dr. Araslanov serves as an Area Chair for CVPR 2025. He is committed to mentoring the next generation of researchers and regularly supervises master's theses, guided research projects, and research assistant positions (HiWi). His teaching includes courses on Deep Learning for Spatial AI (Summer Semester 2025) and Computer Vision 3: Segmentation, Detection and Tracking (Winter Semester 2024/25). As a member of the Computer Vision Group led by Prof. Dr. Daniel Cremers at TUM, Dr. Araslanov collaborates with a diverse team of researchers working on cutting-edge computer vision problems. The group maintains strong connections with industry partners and contributes significantly to the advancement of computer vision research through publications at top-tier conferences and journals.