جست‌وجوی استاد و پژوهشگر

Agnieszka Lasotaمشاهده پروفایل

استادیار

• Optimization of production processes
• Enterprise operations optimization
• Petri nets (P/T type and s-nets)
• +۵ مورد دیگر

Dr. Eng. Agnieszka Lasota is an Assistant Professor at the Institute of Mathematics, Faculty of Mathematics, Informatics and Econometrics, University of Zielona Góra, Poland. She is actively engaged in both research and teaching, supervising diploma theses and coordinating EU-funded projects. Research Interests Her scientific work focuses on the optimization and modelling of production processes and enterprise operations . She employs Petri nets of the P/T type and s-nets to analyse discrete-event systems and has a strong interest in fiber-optic and wireless telecommunications networks . Additional areas include the economic and legal analysis of statutory changes in the telecommunications investment process . Teaching Contributions She delivers courses on software engineering, web-application programming, databases in web applications, data warehouses, and multimedia in business. She also teaches investment market analysis, business-plan preparation, and investment financing, and runs diploma seminars for first-cycle (bachelor) students in Computer Science and Econometrics, Data Engineering, and Mathematics. Outreach & Service Member of the National Organizing Committee for the International Mathematics Competition "Mathematics Without Borders" (Junior & Senior categories) Delivers popular-science lectures for primary and secondary school pupils Promotes study programmes of the Faculty of Mathematics, Informatics and Econometrics and the University of Zielona Góra Facilitates cooperation between schools, industry, and the faculty Grants & Projects Dr. Lasota serves as author and coordinator of both “hard” and “soft” projects. She is a member of project-evaluation committees and acts as an economic expert for the National Centre for Research and Development. She has coordinated the EU Social-Fund project “Modern teaching and practical cooperation with entrepreneurs – development programme of the University of Zielona Góra” (POWR.03.05.0-00-00-Z014/18).

• Gravitational Lensing
• Cosmology
• Dark Matter
• +۳ مورد دیگر

Wolfgang Enzi serves as a Research Fellow at the Institute of Cosmology & Gravitation within the Faculty of Technology at the University of Portsmouth. His research is centered on gravitational lensing and its applications in cosmology, including the measurement of the Hubble constant and the study of dark matter properties through strong lensing systems. His research interests span several key areas: Gravitational Lensing (strong and microlensing) Cosmological Parameter Estimation Dark Matter and Substructure Supernovae as Cosmological Probes Machine Learning for Astrophysical Data Euclid Space Mission Data Analysis Enzi's recent publications (2025) demonstrate a strong focus on advancing gravitational lensing techniques. He has developed machine learning algorithms for identifying lenses in Euclid data and investigated systematic biases in time-delay cosmography. His work on double-source-plane lenses and microlensed supernovae provides novel methods for measuring cosmic distances and dark matter distributions, contributing significantly to observational cosmology. Scientific awards: No specific awards or fellowships are mentioned in the available information. There is no publicly listed information regarding students advised by Enzi or specific research grants he has led. However, his active role in the Euclid Collaboration suggests involvement in large-scale funded projects. Enzi is embedded within the Institute of Cosmology & Gravitation at Portsmouth, collaborating closely with the Euclid team. He participates in international workshops and outreach events, such as the Lensing Odyssey Workshop and Year 12 taster days, promoting gravitational lensing research and astronomy education.

Vikram R Paralkarمشاهده پروفایل

استادیار

• Hematopoiesis
• Leukemia
• Gene regulation
• +۵ مورد دیگر

Vikram R Paralkar, MD, serves as Assistant Professor of Medicine in the Division of Hematology-Oncology at the University of Pennsylvania's Perelman School of Medicine. His research program investigates transcriptional regulation of ribosomal RNA and ribosome biogenesis in normal hematopoiesis and leukemia, with affiliations spanning the Penn Epigenetics Institute, Department of Cell and Developmental Biology, Abramson Family Cancer Research Institute, and Abramson Cancer Center. Education: HSC, DG Ruparel College, Mumbai, India (1998) MD, Seth GS Medical College, Mumbai, India (2004) Dr. Paralkar's work integrates human patient samples, mouse models, and computational approaches to dissect gene regulation in hematopoietic stem cells and leukemic transformation. His lab specializes in ribosomal DNA mapping, nucleolar biology, and chromatin regulation, with particular focus on how transcription factors like PHF6 and CEBPA control RNA Polymerase I activity. Current projects examine ribosome biogenesis as a metabolic vulnerability in leukemia and develop bioinformatic tools for repetitive genome analysis. Analysis of his 2023-2025 publications reveals dominant themes in ribosomal RNA dynamics across the hematopoietic tree, leukemia stem cell regulation through chromatin complexes, and clinical translation of basic findings into AML risk assessment (e.g., tumor lysis syndrome criteria) and health disparity research. His work bridges molecular mechanisms with therapeutic applications, particularly in targeting nucleolar processes in myeloid malignancies. Dr. Paralkar actively mentors PhD candidates in Cancer Biology, Genetics and Epigenetics, and Developmental Biology programs, supervising projects ranging from spermidine metabolism in leukemia to computational genomics. His NIH-funded laboratory recruits researchers for studies on transcriptional regulation in hematopoiesis, with emphasis on both wet-lab and dry-lab approaches. The Paralkar Lab maintains a multidisciplinary team structure with dedicated computational biologists, research specialists, and administrative support. Current initiatives include developing customized genomes for ribosomal DNA mapping, investigating PHF6-mediated stemness suppression, and exploring nucleotide metabolism as a therapeutic target in AML, operating from the BRB II/III research facility at 421 Curie Boulevard.

• Neurobiology
• Neuroendocrinology
• Aging
• +۲ مورد دیگر

Kosara Smiljanić is a Senior Research Associate at the Department of Neurobiology, Institute for Biological Research 'Siniša Stanković' — National Institute of the Republic of Serbia, affiliated with the University of Belgrade. She earned her B.Sc. (2004) and Ph.D. (2012) in Biological Sciences from the Faculty of Biology, University of Belgrade. Education B.Sc. in General Biology, University of Belgrade (2004) Ph.D. in Biological Sciences, University of Belgrade (2012) Her research focuses on neurobiology, neuroendocrinology, aging mechanisms, dietary interventions, and brain cholesterol metabolism. She has participated in international collaborations including COST Actions (CA18201, CA22103) and projects like STRIMHealth, with postdoctoral work ongoing at NICHD/NIH (2018–2025). Recent publications analyze antioxidant properties of fruits, drug resistance in lung cancer models, and oxidative stress during cesarean anesthetics. Active in scientific events (e.g., lecturing on pituitary cell interactions) and cross-border initiatives like the Joint Chinese-Serbian Laboratory, her work spans interdisciplinary studies on aging, metabolic health, and neurodegenerative processes. She contributes to EU programs (HORIZON, COST Actions) and bilateral projects with Croatia, Greece, and the USA.

Omar Khadeer Hussainمشاهده پروفایل

دانشیار

• Logistics and Supply Chain Management
• Distributed and Grid Systems
• Decision Support
• +۳ مورد دیگر

Dr. Omar Khadeer Hussain serves as an Associate Professor and Deputy Head of School (Research) at the School of Business, UNSW Canberra. He has been with the School since February 2014, initially working as a Lecturer and Senior Lecturer before his current appointment. Prior to joining UNSW, he worked as a Senior Research Fellow at Curtin University. Dr. Hussain's educational background includes a Bachelor of Technology in Computer Science from JNTU (2002), a Master of Research in Computer Science from La Trobe University (2004), and a Doctor of Philosophy in Information Management from Curtin University (2008). His research focuses on Logistics and Supply Chain Management, with particular emphasis on Supply Chain Risk Management, Distributed and Grid Systems, Decision Support, and Group Support Systems. Dr. Hussain applies these areas to develop knowledge synthesis from data for business applications such as decision making, risk management, cloud service management, new product development, and milk quality management. His work incorporates predictive analytics to enable informed business decision making, with recent research increasingly integrating artificial intelligence and large language models for supply chain risk identification and management. Analysis of Dr. Hussain's recent scholarly output reveals a strong focus on applying cutting-edge AI techniques to supply chain challenges. His work spans systematic literature reviews on supply chain risk modeling, development of frameworks for SLA violation prevention in Cloud of Things environments, and innovative applications of explainable AI in various domains. There is a clear trend toward leveraging large language models for event identification in supply chain risk management and developing dual-sided decision frameworks that integrate multiple stakeholder perspectives. His research bridges theoretical advances with practical applications in logistics and business engineering. Curtin Business School New Researcher of the Year award for 2012 Prize for Early Career Researcher, Curtin Business School (2013) Chancellor's thesis commendation award, Curtin University (2008) Master Prize – Computer Science, La Trobe University (2004) Dr. Hussain has successfully secured multiple competitive research grants, including ARC Linkage Projects on 'Economically Efficient Green Logistics through Cyber Physical Systems' (2016) and 'Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources' (2015), both with Professor Elizabeth Chang as lead CI. He has also supervised 9 PhD students to completion, serving as both main and joint supervisor. While specific lab or team information isn't explicitly mentioned in the available text, Dr. Hussain's research appears to be conducted within the School of Business at UNSW Canberra, likely collaborating with colleagues across business disciplines and computer science to address complex supply chain and logistics challenges through interdisciplinary approaches.

• Human Activity Recognition
• Process Mining
• Transfer Learning
• +۶ مورد دیگر

Dr. Ian McChesney serves as a Senior Lecturer in the School of Computing at Ulster University, based at the Belfast campus (Room BC-05-128) and Jordanstown Campus. His research spans Human Activity Recognition, Process Mining, and Transfer Learning with significant contributions to Autonomic Computing and Open Data initiatives. Affiliated with the Faculty of Computing, Engineering and Built Environment , he actively collaborates on projects like the PwC Advanced Engineering and Research Centre and the Connected Health Living Lab. His research interests focus on Human Activity Recognition (91% fingerprint match), Process Mining (57%), and Transfer Learning (45%), with applications in smart homes, business processes, and healthcare. Key methodologies include semi-Markov models for IoT device management, synthetic data generation for autonomic systems, and semantic enrichment of HAR datasets. His recent work shows increasing emphasis on educational frameworks for competency-based computing education in the UK. Among his 49 research outputs and 3 datasets, notable contributions include the InSync dataset and research on dyslexia in programming. He received the Best Paper Award ICAS 2025 for work on synthetic data generation. His projects include the TRAXX Fusion consultancy (2014-2016) and current involvement in the PwC Advanced Engineering Centre (2021-2026). Supervision: Mentored 4 students through supervised research work Grants: Contributed to KTP Programme with MJM Marine Limited (2022-2025) and Connected Health Living Lab (2018) His work supports UN Sustainable Development Goals through applications in healthcare optimization, educational innovation, and industrial process improvement. Current projects focus on few-shot learning, large language models, and human activity recognition in connected health environments.

• Economic Geology
• Mineral Resources
• Gold Deposit Genesis
• +۷ مورد دیگر

Hartwig Frimmel is a Professor and Chair of Geodynamics and Geomaterials Research at the Institute of Geography and Geology, University of Würzburg. With an extensive academic career spanning over three decades, he has held positions at the University of Cape Town and the University of Vienna before his current appointment since 2007. His research focuses on economic geology, mineral resources, and Precambrian geology, with particular emphasis on gold deposit genesis and geodynamic processes. PhD in Geology and Petrology, University of Vienna (1987) Professor Frimmel's research interests span multiple domains of economic and Precambrian geology. His work on the genesis of the Witwatersrand gold deposits has significantly contributed to the ongoing debate about one of the most economically significant gold districts in history. He has developed a modified paleoplacer model that explains the available data on these deposits. His research extends to sediment-hosted base metal deposits, geodynamic evolution of southwestern Gondwana, Precambrian palaeoclimate reconstruction, and high-grade metamorphic terranes in Antarctica. His recent work increasingly incorporates machine learning techniques for mineral exploration and resource evaluation. An analysis of Professor Frimmel's recent publications reveals a strong focus on gold deposit genesis across different geological settings and time periods, with particular attention to the Witwatersrand Basin in South Africa. His work combines traditional geological methods with advanced geochemical and isotopic techniques, including detailed studies of fluid inclusions, trace element analysis, and zircon geochronology. There's also a growing trend toward integrating machine learning algorithms with traditional geological methods for resource estimation and exploration targeting. Member of the Academy of Geosciences and Geotechnologies, Germany Founding member of the Bavarian Georesources Centre (BGC) President of the Society for Geology Applied to Mineral Deposits (SGA) 2006-2007 Voting member of the Cryogenian subcommission of the international Commission on Stratigraphy (ICS) Goodwill ambassador of the Geological Society of Africa (GSAf) 2011-2017 Professor Frimmel has served in numerous advisory capacities, including as Advisor to the European Commission's European Innovation Partnership on Raw Materials (2013-2017) and as Dean for student affairs at the University of Würzburg (2013-2016). His research has been supported through various international collaborations and projects, including participation in the South African National Antarctic Programme and the DFG-supported priority programme on Antarctic research. He has coordinated international field workshops and short courses, demonstrating his commitment to advancing geological knowledge globally. As Chair of Geodynamics and Geomaterials Research, Professor Frimmel leads a research group focused on understanding the formation and evolution of mineral deposits within their broader geodynamic context. His team has conducted field studies across multiple continents, including Africa, Antarctica, South America, and Asia, contributing to our understanding of global geologic processes and resource distribution.

Thomas Willمشاهده پروفایل

دانشیار

• Geodynamics
• Metamorphic Petrology
• Structural Geology
• +۳ مورد دیگر

Thomas Will is an Associate Professor at the Chair of Geodynamics and Geomaterials Research within the Institute of Geography and Geology at the University of Würzburg's Faculty of Philosophy. With an academic career spanning over three decades, he has established himself as a leading expert in metamorphic petrology, structural geology, and geodynamics, particularly focused on the European Variscides and South Atlantic correlations. His research interests encompass the geodynamic evolution of the Mid-German Crystalline Zone through integrated petrological, structural, geochemical, and geochronological studies. Notable contributions include the discovery of eclogite-facies rocks in the Odenwald, recognition of Variscan terrane boundaries, and correlation of Neoproterozoic orogenic belts across the South Atlantic. His work has revealed that the CDT basement in Uruguay represents displaced fragments of southwest Africa, forming the 'Arachania' microplate that separated from the Kalahari Craton during Rodinia breakup. Will's recent publications (2021-2024) demonstrate continued research productivity with significant contributions to understanding ultrahigh-pressure metamorphism, Ediacaran-Cambrian tectonomagmatic events in SW Gondwana, and the geodynamic evolution of the Variscan orogen. His work shows a clear progression from regional structural studies to broader continental-scale tectonic reconstructions using advanced geochronological techniques. Jubilee Medal (Best paper award), Geological Society of South Africa (2005) Heisenberg Scholarship, German Research Foundation (1996) Listed in Marquis' Who's Who in the World and Science and Engineering (since 2010) As an educator, Will supervises doctoral students working on advanced petrological topics while teaching Petrology and Advanced Thin Section Microscopy. His international collaborations span institutions in Uruguay, China, South Africa, and Sweden, reflecting the global significance of his research. Will's work bridges fundamental geological processes with practical applications in understanding continental evolution and resource formation.

• Machine Learning
• Artificial Intelligence in Healthcare
• Digital Health & mHealth
• +۷ مورد دیگر

Maryam Tayefi Nasrabadi is an Associate Professor of Machine Learning in the Department of Physics and Technology at UiT The Arctic University of Norway (Tromsø). She applies advanced machine-learning techniques to solve pressing challenges in digital health, clinical informatics, and chronic-disease prevention. Research Interests Artificial-intelligence-driven clinical decision support Multimodal fusion of wearable, imaging, and electronic-health-record data Explainable AI for endocrinology, cardiology, and nutrition Telehealth, mHealth usability, and large-scale eHealth adoption Population-health data mining for risk-factor discovery Across more than 60 peer-reviewed publications (2019-2025) she has consistently explored how robust machine-learning models can be translated into routine clinical workflows, emphasising interpretability, fairness, and user-centred design. Grants & Collaborative Networks While specific grant numbers are not detailed in the provided text, her extensive multinational co-authorship (Norway, Spain, Iran, Canada, USA, UK, Italy, Lithuania, etc.) signals participation in large-scale funded consortia focused on AI in healthcare and digital epidemiology. Selected Professional Contributions Member of editorial boards and peer-review panels for leading journals in medical informatics and AI Active contributor to Norwegian national reports on AI implementation in healthcare (2022-2023) Frequent speaker at international conferences on machine learning in medicine

Jiani Huمشاهده پروفایل

دانشیار

• Magnetic Resonance Imaging
• Magnetic Resonance Spectroscopy
• Neurological Disorders
• +۵ مورد دیگر

Dr. Jiani Hu serves as an Associate Professor in the Department of Radiology at Wayne State University School of Medicine, where she conducts research at the MR Research Facility. Her work focuses on applying advanced MRI and MRS techniques to diagnose, prognose, and monitor lesions in neurological disorders and cancers using both human and small animal models. Her primary research areas include cardiac MRI radiomics for myocardial infarction risk stratification, glymphatic system investigations in aging and diabetes, and neuroimaging of cerebral waste clearance. She actively collaborates with Dr. Mark Haacke to develop non-invasive imaging biomarkers for clinical applications in cardiology and neurology. Analysis of her recent publications reveals dominant trends in cardiac tissue characterization using extracellular volume radiomics and glymphatic dysfunction studies linking vascular physiology to neurodegenerative disorders. Her surgical outcome meta-analyses on bariatric and gastric procedures demonstrate methodological versatility across clinical domains. As a key contributor to the MR Research Facility, Dr. Hu advances quantitative MRI methodologies with direct clinical translation potential. Her interdisciplinary work bridges engineering, data science, and medicine to address unmet needs in cardiovascular and neurological disease management.

• Mathematical Statistics
• Stochastic Processes
• Finance and Actuarial Science
• +۳ مورد دیگر

Yasutaka Shimizu is a Professor at the Department of Applied Mathematics , Waseda University , with prior positions at Osaka University and as Visiting Professor at the Institute of Statistical Mathematics. His work bridges mathematical statistics , stochastic processes , and actuarial science . Education : Ph.D. in Mathematical Science (University of Tokyo, 2007) Key Research : Survival energy models for mortality prediction, threshold estimation for jump-diffusions, ruin theory, fractional Brownian motion inference Recent Publications focus on high-frequency data analysis, survival energy hypothesis applications, and statistical methods for financial/actuarial risks. His 2023 work includes threshold estimation under small noise and survival energy models with functional data analysis. Scientific Awards include the Research Achievement Award (Japan Statistical Society), Ogawa Research Encouragement Award , and Competition Outstanding Report Award . Grants from Japan Society for the Promotion of Science cover topics like statistical modeling of stochastic processes, mortality prediction, and financial risk measurement. He maintains professional memberships in the Japan Statistical Society, Mathematical Society of Japan, and Institute of Actuaries of Japan.

• Space Physics
• Solar Physics
• Astrophysics
• +۳ مورد دیگر

Rami Vainio is a Professor of Space Physics at the University of Turku's Department of Physics and Astronomy, where he serves as head of the Space Research Laboratory (SRL). SRL conducts experimental, theoretical, and computational research on high-energy space phenomena, with focus areas including solar energetic particles (SEPs) and collisionless shocks. The laboratory maintains active collaborations with international research groups. Professor Vainio's research examines: SEP physics : Acceleration mechanisms during solar eruptions and transport through interplanetary space Collisionless shocks : Energy dissipation and particle acceleration in space plasmas Space weather impacts : Radiation risks to technology and humans in space He leads curriculum development for Space Physics and teaches courses including: Mathematical Methods in Physics II (BSc) Space Physics (BSc) Hydrodynamics and Hydromagnetics (MSc) Plasma Astrophysics (MSc) Under his direction, SRL develops particle detection instrumentation and simulation codes. Recent publications focus on SEP forecasting, shock wave analysis using Solar Orbiter data, and radio burst observations with LOFAR.

José Fragoso Santosمشاهده پروفایل

استادیار

• JavaScript
• Separation Logic
• Symbolic Execution
• +۲ مورد دیگر

José Fragoso Santos is an Assistant Professor in the Department of Computer Science and Engineering at Instituto Superior Técnico, University of Lisbon, and a member of INESC-ID where he conducts research as part of the SAT group. His research focuses on embedding formal methods into software development processes, with particular emphasis on JavaScript program analysis and verification. His educational background includes: PhD in Computer Science from University of Nice Sophia Antipolis (2014) Master's degree in Information Systems and Computer Engineering from Instituto Superior Técnico, Universidade de Lisboa (2008) Dr. Santos' research centers on JavaScript verification, symbolic execution, and secure information flow. He led the development of JaVerT, the first separation-logic-based tool for JavaScript analysis and testing, which has gained significant interest from both industry and academia. His work bridges theoretical formal methods with practical applications, particularly in web security and program analysis. He has made substantial contributions to understanding JavaScript semantics, symbolic execution techniques, and secure information flow in web applications, with publications in premier venues like PLDI, POPL, and ECOOP. His recent publications demonstrate a strong focus on symbolic execution for JavaScript and related languages, with applications in web security and program verification. The research shows progression from foundational work on information flow security to advanced techniques like compositional symbolic execution and multi-language analysis platforms. His work on JaVerT and Gillian has established significant research directions in program analysis for dynamic languages. His notable scientific achievements include: Facebook research award for the JaVerT project Dr. Santos has supervised numerous graduate students on projects related to JavaScript verification, symbolic execution, web security, and formal methods. His research has practical applications, as evidenced by the collaboration with Amazon R&D engineers to verify critical components of the AWS Encryption SDK using JaVerT. He has served on program committees for major conferences including PLDI, OOPSLA, and IJCAI, demonstrating his standing in the programming languages community. As a member of the SAT group at INESC-ID, Dr. Santos collaborates with researchers working on formal methods, program verification, and software security. His current projects include extending JavaScript symbolic execution to Web Workers, developing formal semantics for JavaScript regular expressions, and creating first-order solvers for program analysis. He continues to push the boundaries of what's possible in JavaScript program analysis and verification.

Konstantinos Kallasمشاهده پروفایل

استادیار

• Computer Systems
• Compilers
• Programming Languages
• +۱ مورد دیگر

Konstantinos Kallas serves as Assistant Professor of Computer Science at the University of California, Los Angeles (UCLA), commencing his appointment in January 2025. Previously affiliated with the University of Pennsylvania as evidenced by his 2020 PLDI contribution, his research bridges theoretical formal methods with practical systems engineering across multiple high-impact conferences including PLDI, POPL, and SPLASH. His research program centers on enhancing computational efficiency and correctness in systems software, with three flagship projects defining his trajectory: PaSh for automatic shell script parallelization, Durable Functions for stateful serverless computing semantics, and DiffStream for differential testing of stream processing. These efforts consistently target the intersection of programming language theory and real-world systems constraints, particularly in parallelism, concurrency, and cloud-native environments where correctness guarantees are challenging to implement. Analysis of his publication history since 2020 reveals a methodological pattern: developing formal semantic models to enable practical optimizations in distributed systems. His work increasingly focuses on serverless architectures and data-intensive pipelines, with recent contributions emphasizing automated verification techniques. The evolution from shell script optimization (2020-2021) to serverless state management (2021-2022) demonstrates strategic expansion into cloud computing's hardest problems. Dr. Kallas actively contributes to the academic community through program committee service for PLDI (2022, 2025), POPL (2021, 2022, 2023), and SPLASH (2020-2023), including leadership roles as Publicity Co-Chair for PLDI 2025 and 2026. His June 2024 announcement confirms recruitment for Fall 2025 students at UCLA, targeting researchers interested in systems, compilers, and programming languages who can advance his work on correctness-preserving parallelization and serverless computing.

Marian-Andrei Rizoiuمشاهده پروفایل

دانشیار

• Behavioral Data Science
• Misinformation and Disinformation Analysis
• Information Operations
• +۱۲ مورد دیگر

Marian-Andrei Rizoiu is an Associate Professor leading the Behavioral Data Science lab at the University of Technology Sydney's Data Science Institute, Faculty of Engineering and Information Technology. He holds concurrent appointments as an Honorary Lecturer at Australian National University and Honorary Research Scientist at Data61. Previously, he has held visiting professor positions at Imperial College London, Jean Monnet University, and Max Planck Institute for Software Systems. Associate Professor in Behavioral Data Science, UTS Data Science Institute (Jan 2024 - present) Senior Lecturer in Behavioral Data Science, UTS Data Science Institute (Jul 2021 - Jan 2024) Lecturer in Computer Science, UTS Faculty of Engineering and Information Technology (Feb 2019 - Jul 2021) Dr. Rizoiu's research focuses on interdisciplinary work crossing computer and social sciences, blending psycholinguistics, digital communication, and stochastic modeling to understand human attention dynamics online, the emergence of influence, and opinion polarization. His key contributions include developing theoretical models for online information diffusion that can account for complex social phenomena, and building skill-based real-time occupation transition recommender systems that link social media-predicted personality profiles with occupation skill requirements. His research outputs reveal strong trends in misinformation detection, social influence measurement, and online radicalization pathways. Recent publications demonstrate sophisticated modeling approaches including state space models for early misinformation prediction, multivariate Hawkes processes for analyzing partially interval-censored data, and ideology detection pipelines. His work spans computational social science, machine learning, and practical applications for countering harmful online content. Excellence Award and Academic of the Year at the 2023 Australian Defence Industry Awards ADMA'22 Best Application Paper Dr. Rizoiu has successfully secured over $2.9 million in research funding from selective funders including Meta Research, Defence Science and Technology Group, Department of Home Affairs, and Defence Innovation Network. He has supervised 3 PhD students to completion and more than 10 Honours students, most achieving High Distinction. His research has been applied in real-world contexts including serving as an expert for NSW government's Defamation Law Reform and providing evidence for Australian Federal Senate inquiry into media diversity. He leads the Behavioral Data Science lab which focuses on modeling human behavior in online environments, with particular emphasis on mis- and disinformation detection and labor market analysis. The lab has developed tools like TRACK, UTS OPEN's software for recommending personalized learning pathways, used by over 750 students and professionals.