جست‌وجوی استاد و پژوهشگر

• Infectious Diseases
• Maternal and Child Health
• Public Health
• +۷ مورد دیگر

Dr. John G. Ayisi is a prominent researcher in public health and infectious diseases, with affiliations including the Kenya Medical Research Institute (KEMRI), Johns Hopkins Bloomberg School of Public Health, and Amsterdam UMC – University of Amsterdam. His work focuses on maternal and child health in sub-Saharan Africa, particularly the interplay between malaria, HIV, and malnutrition during pregnancy. Kenya Medical Research Institute Johns Hopkins Bloomberg School of Public Health Amsterdam UMC - University of Amsterdam His research interests include infectious disease epidemiology, maternal immunology, and integrated public health interventions. He employs meta-analytic and field-based methodologies to assess the impact of preventive therapies and genetic factors on perinatal outcomes in malaria- and HIV-endemic regions. The recent publications show a consistent focus on pregnancy-associated malaria, genetic susceptibility to HIV transmission, and the combined burden of malnutrition and infection. His work often involves large-scale data synthesis and community-based trials, emphasizing evidence-based policy formulation for low-resource settings. Dr. Ayisi has received funding and support from leading global health institutions, including: National Institutes of Health (NIH) Centers for Disease Control and Prevention (CDC) National Research Foundation Natural Sciences and Engineering Research Council of Canada Department for International Development (UK) Association Française contre les Myopathies He has advised or collaborated on numerous research projects aimed at reducing maternal and child morbidity in Africa. While no formal students are listed, his leadership in multi-institutional studies suggests a mentorship and collaborative role. His research has been instrumental in shaping malaria prevention policies, particularly regarding intermittent preventive therapy in pregnancy (IPTp) and integrated maternal health programs. Dr. Ayisi has contributed to major initiatives such as the Maternal Malaria and Malnutrition (M3) program and has developed novel methodologies for placental immunology studies. His work bridges laboratory science, epidemiology, and public health implementation, often conducted in partnership with local and international research teams in Kenya and beyond.

Rachel Kennedyمشاهده پروفایل

استاد

• Marketing Science
• Advertising Effectiveness
• Brand Growth
• +۱۰ مورد دیگر

Professor Rachel Kennedy is a co-founder and Associate Director (Product Development) at the Ehrenberg-Bass Institute for Marketing Science, the world's largest center for marketing research. Based at the University of South Australia, she plays a pivotal role in translating cutting-edge research into actionable insights and industry products. Her work bridges academia and practice, serving global brands such as Unilever, Mars, Google, and HSBC through evidence-based marketing strategies. Research Interests: Rachel’s research is centered on marketing science, with a focus on advertising effectiveness, brand growth, consumer behavior, and neuromarketing. She investigates how advertising works using biometrics, attention metrics, and single-source data. Her work emphasizes evidence-based approaches, challenging industry myths and promoting scientific rigor in marketing decisions. Key areas include ad likeability, price promotions, packaging design, and the long-term effects of advertising cessation. The analysis of her recent publications reveals a consistent trend toward understanding measurable, long-term brand performance. Her work increasingly incorporates biometric and eye-tracking methods to assess attention and persuasion in advertising. Themes such as duplication of purchase, brand user profile similarity, and the validity of marketing metrics recur across her research, reinforcing foundational principles of marketing science. Scientific Awards and Recognition: Incorporated Society of British Advertisers award for advancing understanding of advertising Named one of 'Advertising’s Big Thinkers' by the UK Advertising Association Advising and Grants: While specific students are not listed, Rachel has mentored and collaborated extensively with researchers at the Ehrenberg-Bass Institute. Her role in product development implies leadership in research funding and industry sponsorship programs. She has led and contributed to numerous market research projects funded by global advertisers and media organizations, helping to embed evidence-based practices across industries. Labs and Teams: Rachel is a core member of the Ehrenberg-Bass Institute, a world-renowned research center with over 60 marketing scientists. The institute operates as a collaborative hub for empirical marketing research, offering executive programs like 'How Brands Grow – Live!' and conducting large-scale studies on consumer behavior, advertising, and brand strategy.

Jenni Romaniukمشاهده پروفایل

استاد پژوهشی

• Marketing Science
• Brand Management
• Consumer Behavior
• +۱۱ مورد دیگر

Professor Jenni Romaniuk is a Research Professor of Marketing and Associate Director (International) at the Ehrenberg-Bass Institute for Marketing Science, formally affiliated with the University of South Australia through UniSA Business School. She is a leading authority in marketing science, particularly in brand growth, mental availability, and distinctive brand assets. Her research focuses on understanding how brands grow through empirical generalizations, with significant contributions to the measurement of brand health, category entry points, and advertising effectiveness. She has authored three major books: Building Distinctive Brand Assets , How Brands Grow Part 2 , and Better Brand Health , all published by Oxford University Press. The 15 most recent publications reveal a strong trend in consumer behavior across diverse contexts, including non-profits, luxury brands, co-branding, and emerging markets. Her work integrates quantitative modeling with behavioral insights, often using large-scale datasets to validate marketing laws such as the Pareto principle and mental availability theory. She frequently publishes in top journals like the European Journal of Marketing , International Journal of Market Research , and Journal of Advertising Research . She is a past editor and current member of the Senior Advisory Board of the Journal of Advertising Research , reflecting her leadership in the academic marketing community. Her collaborations span global researchers, contributing to foundational knowledge in brand equity, private labels, and word-of-mouth dynamics. Jenni Romaniuk has not disclosed any PhD or Master’s students in the provided text. She is actively engaged in research and has no indication of part-time status, retirement, or former staff designation. She is not listed with any specific email address in the text.

Greg Eisenhauerمشاهده پروفایل

پژوهشگر

• High Performance Computing
• Systems
• Enterprise Computing
• +۳ مورد دیگر

Dr. Greg Eisenhauer is a Senior Research Scientist at the Georgia Institute of Technology's School of Computer Science and affiliated with the Center for Experimental Research in Computer Systems (CERCS). His research focuses on high-performance computing (HPC), systems, and enterprise computing, with an emphasis on program monitoring, dynamic adaptation, performance evaluation, and I/O systems like ADIOS. Supported by NSF, DOE, DARPA, and industry grants, his work addresses challenges in HPC workflows, data management, and streaming analytics. He leads efforts in scalable data environments, metadata optimization, and exascale computing resilience.

• Traffic Systems Engineering
• Transportation Modeling
• Intelligent Transportation Systems
• +۳ مورد دیگر

Dr. V.L. Knoop is a Professor in Traffic Systems Engineering at Delft University of Technology's Civil Engineering & Geosciences school. His research focuses on advanced transportation modeling, autonomous vehicle systems, and data-driven mobility solutions. He has contributed over 250 publications and supervised multiple research projects. Notable awards include the Greenshields Prize (2012, 2015, 2016) and D. Grant Mickle Award (2016). Knoop has led editorial roles for Collective Dynamics and co-edited conference proceedings on Traffic and Granular Flow. His work bridges theoretical models with practical applications, addressing challenges in traffic efficiency, safety, and sustainable infrastructure. Recent media engagements highlight his expertise in traffic management solutions and autonomous vehicle technologies. Education: PhD in Civil Engineering (assumed) Research Interests: Development of macroscopic traffic flow models Integration of autonomous systems into existing transport networks Data analytics for traffic prediction and optimization Key Contributions: Large-scale car-following dataset analysis (Lyft Level-5 collaboration) Ramp metering optimization studies using empirical trajectory data Publications on adaptive cruise control and uncertainty-based decision-making in autonomous vehicles Labs/Teams: Traffic Systems Group at TU Delft Collaborations with Rijkswaterstaat (Dutch Ministry of Infrastructure) and Flitsmeister

Dominik Kopczynskiمشاهده پروفایل

پژوهشگر

• Lipidomics
• Mass Spectrometry
• Metabolic Pathways
• +۳ مورد دیگر

Dominik Kopczynski is a researcher affiliated with the Department of Analytical Chemistry at the Faculty of Chemistry. His work focuses on lipidomics, mass spectrometry, and the development of bioinformatics tools for lipid structure analysis and experimental standardization. He has contributed to initiatives like the lipidomics reporting checklist and Goslin nomenclature system. Active in organizing academic events such as the de.NBI Spring School for lipidomics bioinformatics and Keystone Symposia on lipid biology, he collaborates extensively with international researchers. Research Interests: Lipid metabolism, mass spectrometry-based analytical methods, lipid nomenclature standardization, proteomics, and computational tools for omics data analysis. His work bridges biochemical experimentation with bioinformatics to enhance reproducibility and interdisciplinary collaboration in lipidomics research. Activities: Organized 36 academic events including conferences, schools, and poster sessions. Notable contributions include co-organizing the 2025 de.NBI Spring School and contributing to the Keystone Symposia on lipid cellular function and disease. Engaged in both presenting research and fostering collaborative research networks. Labs/Teams: Collaborates within the Department of Analytical Chemistry and participates in international lipidomics consortia. His work often involves cross-disciplinary teams focused on integrating biochemical and computational approaches. Grants/Advising: While specific grants are not detailed, his extensive publication record and collaborative activities suggest involvement in funded projects related to lipidomics infrastructure development and analytical method standardization.

Dmitry Korkinمشاهده پروفایل

استاد

• bioinformatics of complex diseases
• computational genomics
• systems biology
• +۷ مورد دیگر

Dmitry Korkin is a Professor of Computer Science at Worcester Polytechnic Institute (WPI) and holds the prestigious Harold L. Jurist '61 and Heather E. Jurist Dean's Professor title. He maintains strong interdisciplinary connections across campus, with formal affiliations in Bioinformatics & Computational Biology, Data Science, Biology & Biotechnology, and Mathematical Sciences departments. His educational background includes: Postdoctoral training in Bioinformatics & Computational Biology at the University of California, San Francisco (2007) PhD in Computer Science from the University of New Brunswick, Canada (2003) MS in Applied Mathematics from Moscow State University, Russia with High Distinction (1999) Professor Korkin leads an interdisciplinary research program at the intersection of computer science and biology. His lab specializes in applying machine learning, data mining, and massive data analytics to investigate molecular mechanisms underlying complex diseases including cancer, diabetes, and autism, as well as deadly infections like pandemic flu. The research integrates multi-omic, systems, and structural biology data to develop comprehensive models of disease mechanisms. A distinctive aspect of his work involves developing hardware-optimized algorithms for large-scale genome evolution analysis, enabling studies of animal and plant genomes at unprecedented scale. The lab maintains strong collaborative ties with experimental biologists to validate computational predictions through wet-lab experiments. His publication record demonstrates a clear evolution from foundational work in protein structure analysis toward increasingly complex systems biology applications. Early research focused on protein binding sites and structural classification, while more recent work addresses host-pathogen interactions and pandemic virus structure. The lab's work on SARS-CoV-2 represents a significant pivot toward immediate public health applications, developing what has been described as a 'periodic table' of structural elements for the virus. Key recognition: Harold L. Jurist '61 and Heather E. Jurist Dean's Professor Professor Korkin has secured multiple research grants including WPI President's Research Catalyst Grants and seed funding for early-stage projects. His work on SARS-CoV-2 structure was published in Viruses and featured in Nature Neuroscience. He maintains active collaborations both nationally and internationally, with research findings covered by major media outlets including Spectrum News 1, Phys.org, and Nautilus magazine. Notably, his lab's structural analysis of the COVID-19 virus led to a unique collaboration with Scottish artist Angela Palmer, resulting in a sculptural model displayed at the Oxford Museum of Natural History. He directs the Korkin Lab (korkinlab.org), which maintains a strong focus on computational approaches to biological problems. Beyond research, Professor Korkin has demonstrated significant humanitarian engagement, opening his home to the family of Ukrainian professor Vitaly Yurkiv amid the Russian invasion and working to help find academic positions for displaced Ukrainian scholars in the United States. His office is located in Unity Hall, Room UH460, and he can be reached at dkorkin@wpi.edu.

Stan Siebertمشاهده پروفایل

استاد

• Labour Economics
• Industrial Relations
• Wage Inequality
• +۷ مورد دیگر

Professor Stan Siebert is a distinguished academic in the Department of Management at the Birmingham Business School, University of Birmingham, where he has been a faculty member since 1980. He holds the position of Professor of Labour Economics and is actively engaged in research and teaching in personnel economics and industrial relations. PhD, London School of Economics Stan Siebert's research centers on labour economics, with a strong focus on wage issues, industrial relations, European labour market regulation, and vocational training. His work investigates critical topics such as the gender wage gap, minimum wages, wage inequalities, and the impact of labour policies on employment. He has conducted research on unskilled workers in OECD countries and has explored education feedback mechanisms in rural China. His recent publications span top-tier journals such as Management Science , Industrial & Labor Relations Review , and Oxford Economic Papers , covering themes like intergenerational income mobility, temporary employment regulation in Greece, and the consequences of piece-rate pay. His research often combines theoretical insights with empirical analysis using large-scale datasets. Evidence on intergenerational income transmission using complete Dutch population data Management Economics in a Large Retail Company The impact of Greek labour market regulation on temporary employment Work-life balance: promises made and promises kept The Consequences of a Piece Rate on Quantity and Quality: Evidence from a Field Experiment Professor Siebert is a member of IZA (Institute for the Study of Labour, Bonn), where his recent working papers are available. He teaches Personnel Economics at the undergraduate level and has co-authored influential texts including The Market for Labor: An Analytical Treatment and The Economics of Earnings . He has also edited Labour Markets in Europe: Issues of Harmonisation and Regulation . While no specific grants or scientific awards are listed, his sustained publication record and long-standing academic position reflect significant scholarly impact. He is involved in research projects examining the cost-effectiveness of education feedback in rural China and the employment effects of minimum wages and employment protection laws in OECD countries. His work bridges economic theory, policy analysis, and empirical research, contributing to both academic discourse and real-world labour market understanding.

Davide La Vecchiaمشاهده پروفایل

استاد

• Time series analysis
• Robust and semiparametric inference
• Financial econometrics
• +۳ مورد دیگر

Davide La Vecchia is a Full Professor at the Research Institute for Statistics and Information Science (RISIS) at the University of Geneva, Switzerland. He holds dual PhDs in Statistics from Bocconi University (2007) and Economics from Università della Svizzera italiana (2011). His academic journey includes roles as an Assistant Professor at the University of St. Gallen and Monash University, and he has held visiting positions at Princeton University, the University of Copenhagen, and CREST (Paris). His expertise spans time series analysis, robust and semiparametric inference, financial econometrics, and spatial statistics. Key research contributions include work on saddlepoint approximations, optimal transportation methods, and latent variable models. Davide has led multiple grants, including from the Swiss National Science Foundation and the Australian Research Council. He serves as a referee for top-tier journals in statistics and econometrics. Teaching focuses on advanced statistical methods, including probability theory, time series analysis, and multivariate inference. His recent work emphasizes high-dimensional data modeling, spatio-temporal factor models, and applications to commodities trading networks. He has been honored with editorial roles and speaker invitations at global conferences, reflecting his leadership in statistical methodology.

Minsu Parkمشاهده پروفایل

استادیار

• Computational Social Science
• Human-centered Data Science
• Cultural Consumption
• +۹ مورد دیگر

Minsu Park is an Assistant Professor of Social Research and Public Policy at New York University Abu Dhabi (NYUAD), with affiliate status at the Center for Data Science at New York University (NYU). He holds a PhD in Information Science from Cornell University, where he was advised by Michael W. Macy and Mor Naaman. His academic work bridges computational techniques and social science theory, focusing on cultural consumption, social networks, and human-centered data science. PhD in Information Science, Cornell University His research centers on understanding how individuals form cultural preferences through social and psychological mechanisms, particularly in domains like music, food, fashion, and science. He leverages large-scale digital trace data—including social media, streaming platforms, and physiological signals from smart devices—to model behavior. His interdisciplinary approach draws from sociology, social computing, and data science, aiming to uncover both individual and global patterns in cultural dynamics. Key themes include variety-seeking behaviors, affective preferences, and the interplay between social position and taste. The 15 most recent publications reflect a strong trend toward using computational methods to explore sociocultural phenomena. Topics span affective preference rhythms in music, testing sociological theories like cultural omnivory, imputing user attributes from digital behavior, and enhancing model interpretability. These works are published in high-impact venues such as Nature Human Behaviour and ICWSM, indicating recognition in both computer and social sciences. Minsu Park is deeply committed to responsible data science, addressing issues like algorithmic bias, transparency, fairness, data privacy, and research ethics. He emphasizes mixed-methods approaches and critical reflection on data generation and usage. Published in Nature Human Behaviour Presented at ICWSM Focus on ethical and interpretable AI Advocate for reproducibility and data curation He mentors students through capstone projects in computer science and teaches courses such as Human-Centered Data Science and Textual Analysis for the Social Sciences. While specific grants are not detailed in the text, his research program suggests involvement in interdisciplinary, data-intensive projects likely supported by academic or scientific funding bodies. His technical expertise includes Python, R, machine learning frameworks (TensorFlow, Keras), and tools like Gephi and AWS. He leads or contributes to research initiatives involving smartwatch-based data collection, surname-based ethnicity matching, and global music consumption analysis, as evidenced by his public GitHub repositories. These projects highlight his commitment to open science and collaborative research.

• Bioprocess Engineering
• Downstream Processing
• Industrial Biotechnology
• +۷ مورد دیگر

Rainer Hahn is an Associate Professor in Biochemical Engineering at the Institute of Biochemical Engineering, Department of Biotechnology and Food Sciences, University of Natural Resources and Life Sciences, Vienna (BOKU). He also serves as Head of the Downstream Processing Unit at the BioIndustrial Pilot Plant and is a key researcher at the Austrian Center of Industrial Biotechnology (ACIB). His work is centered on bioprocess engineering with a strong focus on downstream processing and biopharmaceutical purification. University: University of Natural Resources and Life Sciences, Vienna (BOKU) School: Department of Biotechnology and Food Sciences Department: Institute of Biochemical Engineering Role: Associate Professor, Head of Downstream Processing Unit His research interests span Bioprocess Engineering , Downstream Processing , Industrial Biotechnology , Pharmaceutical Technology , and Chemical Biology . He investigates advanced purification techniques, particularly in chromatography and protein separation processes. His recent work emphasizes multicomponent adsorption, protein A affinity systems, and purification of complex biomolecules like secretory immunoglobulin A (sIgA). The trend in his recent publications reveals a strong emphasis on protein purification , chromatographic modeling , and process optimization in biopharmaceutical manufacturing. His work integrates experimental analysis with mathematical modeling to improve efficiency and predictability in downstream operations, especially in multi-component systems. Topics such as continuous chromatography , pH transients , and affinity resin development reflect his leadership in advancing industrial bioprocessing. His notable scientific awards include: HOUSKA PRIZE (Recognition Award) - 2016 Dissertation Prize of the Austrian Society for Biotechnology - 2002 Rainer Hahn has been actively involved in numerous research projects funded by FWF, national enterprises, and private foundations, focusing on biopharmaceutical purification and process development. He mentors students and contributes to academic training through lectures and supervision. He is also a dedicated reviewer for leading journals such as Journal of Chromatography A , Biotechnology and Bioengineering , and Separation and Purification Technology . His work is closely tied to industrial applications, particularly in the development of scalable and efficient biomanufacturing processes. He is associated with the BioIndustrial Pilot Plant and collaborates with ACIB, contributing to innovation in industrial biotechnology. His research group focuses on developing robust downstream strategies for next-generation biopharmaceuticals.

• Operations Research
• Supply Chain Management
• Pharmacy Administration
• +۲ مورد دیگر

Bahram Alidaee is a tenured Professor at the University of Mississippi's School of Business Administration, holding the School of Business Fellow Endowed Position. He has been affiliated with the Department of Marketing, Analytics and Professional Sales since joining Ole Miss in 1995, offering expertise in Operations, Supply Chain Management, and Pharmacy Administration. Education: B.S. in Business Administration, University of Tehran (1975) MBA in Industrial Management, University of North Texas (1980) Ph.D. in Mathematics (Operations Research concentration), University of Texas at Arlington (1988) His research focuses on applying operations research to large-scale industrial problems, with consulting experience spanning Casino Gaming, Furniture Industries, NAVY Personnel Assignment, Hospital Quality Management, and Blood Services. He has secured over $5.4 million in research grants through collaborations. Scientific Recognition: Outstanding Senior Researcher of the Year (School of Business Administration, 2×) Editorial board member for multiple journals Alidaee has directed 11 doctoral dissertations and taught operations/supply chain courses at all academic levels (undergraduate, MBA, PMBA, Ph.D.).

• Atmospheric Aerosols
• Environmental Spectrochemistry
• Air Quality Monitoring
• +۷ مورد دیگر

Satoshi Takahama is an Adjunct Professor at the Laboratory for Environmental Spectrochemistry (LESC) within the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL). He also contributes to teaching through the SSIE - Teaching unit at EPFL and serves on the PhD program committee for Civil and Environmental Engineering. His research is centered on the measurement, analysis, and modeling of atmospheric aerosols and their impacts on air quality and climate. Research Interests: Measurement and modeling of atmospheric aerosols Application of Fourier-transform infrared (FTIR) spectroscopy for aerosol characterization Functional group analysis of organic particulate matter Development of computational and chemometric tools for environmental data analysis Climate and air quality impacts of biomass burning and urban emissions His recent publications reflect a strong focus on the chemical evolution of aerosols, instrumental development (e.g., electrostatic collectors), and data-driven approaches to emission inventories and monitoring. These works span atmospheric chemistry, environmental engineering, and analytical method development. Scientific Awards: No awards listed in the provided text. Advising and Grants: Supervised multiple PhD students including Virginia Tadei, Gözde Bitlislioglu, Eirini Boleti, Nikunj Dudani, Giulia Ruggeri, and Amir Yazdani. Involved in large-scale monitoring network studies (e.g., IMPROVE, SEARCH) and international field campaigns (e.g., Cal-Mex, SOAS). Contributed to the development of open platforms such as AIRSpec for infrared spectroscopy analysis. Labs and Teams: Laboratory for Environmental Spectrochemistry (LESC), EPFL Collaborations with research groups in the U.S. and Europe on aerosol characterization and modeling Active participant in international conferences and research networks in aerosol science.

Junhao Wenمشاهده پروفایل

استادیار

• Computational Neuroscience
• Artificial Intelligence in Healthcare
• Medical Imaging Analysis
• +۷ مورد دیگر

Dr. Junhao Wen is an Assistant Professor of Computational Neuroscience at the Department of Radiology, Columbia University Irving Medical Center. He is also an Affiliated Member of the Health Analytics Center. His interdisciplinary work bridges advanced artificial intelligence and biomedical data to investigate human aging and disease mechanisms. Dr. Wen's research focuses on integrating AI and machine learning with multi-organ imaging (e.g., brain MRI) and multi-omics data (including genetics and proteomics). His work aims to uncover biomarkers and mechanistic insights into neurodegenerative diseases and aging processes. This positions him at the forefront of computational biomedicine and precision health analytics. His scientific approach combines deep learning, statistical modeling, and large-scale biomedical datasets to develop predictive models of disease progression. These methods are applied across diverse populations to enhance early diagnosis and intervention strategies. The Health Analytics Affiliation underscores his role in advancing data-driven healthcare solutions at Columbia. While no specific publications or awards are listed in the source text, his research trajectory reflects strong engagement with cutting-edge computational methodologies in medicine. Dr. Wen has previously held positions as a postdoctoral researcher at the University of Pennsylvania and as an Assistant Professor at the University of Southern California. He earned his Ph.D. from Sorbonne University in 2019, establishing a foundation in computational methods applied to neuroscience and biomedical data. He advises graduate students and may lead a research laboratory focused on AI-driven health discovery, though specific advisees are not named. His work likely involves collaboration across departments and institutions, supported by grants in AI, neuroscience, and aging research, although specific funding sources are not mentioned. Dr. Wen's laboratory, accessible via https://labs-laboratory.com/ , serves as a hub for interdisciplinary research in computational neuroscience and health analytics.

Milos Nikolicمشاهده پروفایل

مدرس

• Databases
• Data Management
• Incremental Computation
• +۷ مورد دیگر

Milos Nikolic is a Lecturer in Database Systems at the School of Informatics, University of Edinburgh. He is a member of the Database Group and the Laboratory for Foundations of Computer Science. Prior to joining Edinburgh, he was a Departmental Lecturer in the Department of Computer Science at the University of Oxford. He holds a PhD in Computer Science from EPFL. Research Interests: Milos Nikolic's research focuses on databases and large-scale data management, with emphasis on incremental computation, in-database learning, stream processing, and query compilation. His work explores how complex analytical queries—such as SQL, linear algebra, and machine learning tasks—can be efficiently maintained and evaluated in dynamic and distributed environments. He develops novel techniques in query optimization and compilation to enable real-time analytics over evolving data. His recent publications demonstrate a strong trend in dynamic query evaluation, particularly around conjunctive and hierarchical queries under updates, incremental view maintenance (e.g., F-IVM), and scalable processing of nested and biomedical data. His work often leverages theoretical foundations to achieve worst-case optimal performance, grounded in conjectures like the Online Matrix-Vector Multiplication (OMv) hypothesis. Scientific Awards: Best Paper Award, ICDT 2019 Advising and Grants: Milos is actively seeking PhD students to work on data management topics. While no formal list of advisees is provided, he collaborates extensively with researchers such as Dan Olteanu, Ahmet Kara, and Haozhe Zhang. His projects, including Adaptive Query Processing , Incremental Maintenance of Complex Analytics , and Declarative Data Pipelines (industry-supported), suggest ongoing grant and industry collaborations. Labs and Teams: He is a key member of the Database Group and the Laboratory for Foundations of Computer Science at the University of Edinburgh, contributing to cutting-edge research in foundational and applied database systems.