Find Academic Supervisors

Michael A. LivermoreView profile

Professor

• Environmental Law
• Cost-Benefit Analysis
• Computational Legal Studies
• +3 more

Michael A. Livermore is a Professor at the University of Virginia School of Law, where he joined the faculty in 2013. He teaches courses on environmental law, regulation and legal technology, and is recognized as a leading expert in cost-benefit analysis for regulatory evaluation. Livermore frequently collaborates on interdisciplinary projects with researchers across economics, computer science, neurology, and the humanities. Livermore earned his J.D. magna cum laude from NYU Law, where he was a Furman Scholar, was elected to the Order of the Coif, and served as a managing editor of the Law Review. After law school, he spent a year as a fellow at NYU Law's Center on Environmental and Land Use Law before clerking for Judge Harry T. Edwards on the U.S. Court of Appeals for the D.C. Circuit. Prior to joining UVA, he was the founding executive director of the Institute for Policy Integrity at New York University School of Law. Professor Livermore's research focuses on environmental law, cost-benefit analysis, and the application of data science techniques to legal texts. He is considered one of the early scholars in the emerging field of computational legal studies, using natural language processing and other computational methods to analyze legal materials. His work bridges traditional legal scholarship with cutting-edge data science approaches, creating new methodologies for understanding law and legal institutions. Livermore hosts the Online Workshop on the Computational Analysis of Law, a global forum for scholars working at this intersection. Livermore is a leading expert on cost-benefit analysis in regulatory contexts, authoring influential books including "Reviving Rationality: Saving Cost-Benefit Analysis for the Sake of the Environment and Our Health" (2020) and "Retaking Rationality: How Cost-Benefit Analysis Can Better Protect the Environment and Our Health" (2008). His recent scholarship increasingly focuses on the intersection of artificial intelligence and law, examining how language models can be applied to legal tasks and how to measure their performance in legal reasoning. As a prolific scholar, Livermore has published dozens of academic works in top law journals as well as peer-reviewed legal, scientific, and social science journals. His 2024-2023 publications demonstrate a clear trend toward computational legal studies, with multiple papers on language model interpretability, judicial analysis using computational methods, and the application of AI to legal tasks. These works span disciplines including legal scholarship, computer science, economics, and empirical legal studies. Livermore is a senior fellow of the Administrative Conference of the United States, reflecting his expertise in administrative law and regulatory process. His scholarship has significantly influenced debates about regulatory policy, particularly regarding environmental regulation and the proper role of cost-benefit analysis. Throughout his career, Professor Livermore has demonstrated a commitment to interdisciplinary collaboration and methodological innovation. His early work established him as a leading voice in environmental regulation and cost-benefit analysis, while his more recent scholarship has positioned him at the forefront of the emerging field of computational legal studies. He has participated in dozens of regulatory proceedings on diverse issues ranging from climate change to prison safety, bridging academic scholarship with practical regulatory challenges.

Scott ThiebesView profile

Researcher

• Digital Health
• Information Systems
• Blockchain Technology
• +6 more

Scott Thiebes is a Postdoctoral Research Associate and team lead of the Digital Health work group at the Critical Information Infrastructures Research Group at the Karlsruhe Institute of Technology (KIT). He holds a Ph.D. in Information Systems from KIT (Summa cum laude, 2022) and previously completed his academic training at the University of Cologne. His research focuses on digital transformation in healthcare, with particular expertise in digital health, information systems, blockchain technology, and artificial intelligence applications in healthcare settings. Karlsruhe Institute of Technology (KIT) - Institute for Applied Computer Science and Formal Description Methods Chair of Information Infrastructures under Prof. Ali Sunyaev Team lead of Digital Health work group Technical University of Munich affiliation via Campus Heilbronn Thiebes specializes in the intersection of information systems and healthcare, with research interests spanning digital health infrastructure, trustworthy AI in medical contexts, blockchain applications for health data management, and gamification for medical image annotation. His work employs behavioral and design-oriented information systems methods alongside medical informatics and computer science approaches. He has developed significant expertise in genetic data sharing, privacy considerations in health informatics, and the application of distributed ledger technology in healthcare settings. His recent publications demonstrate a strong focus on explainable AI for medical applications, blockchain-based health data management systems, and gamification techniques to improve medical image annotation quality. The research shows a clear trajectory toward creating more transparent, trustworthy, and effective digital health solutions that address both technical and human factors in healthcare transformation. Nominated by KIT for the Helmholtz Dissertation Award 2022 Best Theory Paper on Health IS Track at ICIS 2020 Multiple Best Reviewer Awards (ICIS 2019, WISP 2019, WISP 2017) Doctoral Fellow of HICSS 2017 Multiple Best Paper Nominations (PACIS 2016, ECIS 2014) Dean's Award from University of Cologne (twice) Thiebes serves as a reviewer for numerous top-tier information systems conferences and journals including ICIS, ECIS, HICSS, and WISP. He holds editorial and track chair positions for Business & Information Systems Engineering (BISE) and various conference tracks. His research is supported by multiple projects including GaMeIT (gamification for medical image annotation), BloG3 (blockchain-based health data management), Digital Transformation in Healthcare, ReDiBlock (resource conservation through blockchain), and XAIOmics (explainable AI for omics data), funded by organizations including the Helmholtz Association, German Federal Ministry of Education and Research, and German Research Foundation.

Rand LowView profile

Associate Professor

• Portfolio Optimization
• Risk Management
• Quantitative Finance
• +5 more

Rand Low serves as Honorary Associate Professor at the University of Queensland's School of Business and Associate Professor of Quantitative Finance at Bond Business School. His expertise bridges academia and industry with extensive experience leading quantitative research teams at Bank of America Merrill Lynch and BlackRock in New York City. He actively contributes to financial discourse through media engagements with major outlets including Australian Financial Review, BBC, and ABC News, while advising governmental bodies on bond market development. Dr Low holds a Doctor of Philosophy from the University of Queensland. His educational background includes Chartered Engineer designation from Engineers Australia earned during engineering management roles at Honeywell on landmark projects including GOMA and Mater Mothers' Hospital. Professor Low's research spans four critical domains in quantitative finance: Portfolio Optimization: Specializing in multi-asset strategies (commodities, fixed income, private equity) using vine copulas for crisis-period dependence modeling Risk Management: Developing frameworks for credit/market/operational risk including VaR/CVaR metrics and regulatory model validation Digital Assets: Pioneering research on cryptocurrency derivatives, blockchain applications, and ESG integration in digital finance Systematic Trading: Creating factor-based and event-driven strategies validated through neural network analysis of commodity risk premia His 15 most recent publications reveal three dominant trends: increasing integration of machine learning in commodity risk analysis (2023-2025), growing emphasis on ESG factors in credit rating determinants (2024), and innovative applications of blockchain technology beyond finance into conservation (2025). The research consistently addresses volatility spillovers during crises while expanding into digital asset derivatives and sustainable investment frameworks. Professor Low's scientific recognition includes: GSITA Award and 3MT Competition Winner during PhD studies Dean's Award for Research Higher Degree Excellence Australia Awards - Endeavour Fellowship Australian Institute of Business and Economics (AIBE) Scholar designation Research Fellowship on Portfolio Optimization & Risk Management Techniques He actively supervises doctoral candidates in corporate credit risk modeling, robo-advisor development, and multi-asset optimization. His funded research includes the Accounting and Finance Association of Australia and New Zealand grant (2014-2015) on risk-adjusted retirement metrics and the UQ Postdoctoral Research Fellowship (2014-2016) on crisis-period portfolio optimization. Industry collaborations include advisory roles for BitOrb (Digital Assets Exchange) and Australian Bond Exchange. Professor Low leads cross-sector initiatives connecting academic research with financial practice, having directed quantitative teams at top-tier institutions where he defended model development practices to US regulators including the Federal Reserve. His current focus involves applying statistical learning to automate investment processes across cryptocurrency, commodities, and corporate credit markets.

• Urban Innovation
• Sustainable Cities
• Climate Action
• +4 more

Dr. Ellie Cosgrave is an Associate Professor in Urban Innovation and Policy at University College London's Department of Science, Technology, Engineering and Public Policy (STEaPP), where she co-directs the Urban Innovation and Policy Lab. She holds a Doctor of Engineering (2014) and Master of Engineering (2009) from the University of Bristol. Her work intersects urbanisation, technology, and social justice, focusing on creating equitable cities through policy innovation. Research Focus Cosgrave's research examines sustainable urban development through three interconnected lenses: rapid urbanisation dynamics, technological innovation governance, and wellbeing/social justice outcomes. She employs interdisciplinary methods—spanning engineering, social sciences, and performing arts—to address challenges in climate action, gender-inclusive planning, and smart city governance. Her work emphasizes participatory approaches to urban transformation. Publications Overview Her recent scholarship (2011-2019) demonstrates consistent focus on sustainable urban futures, with key themes including: climate policy integration, gender equity in cities, infrastructure governance, and innovative methodologies like arts-based engagement. Publications frequently analyze systemic barriers to equitable urban development while proposing policy frameworks for inclusive technological innovation. Leadership & Engagement Beyond academia, Cosgrave hosts BBC's 'Tomorrow's World Podcast' and 'My Perfect City' series, advocating for science communication and women's health. She convenes UCL's Urban Innovation and Policy MPA program, synthesizing engineering, Bartlett School expertise, and policy studies to train city leaders.

Leonie le SageView profile

Lecturer

• Social Work
• Professional Identity Development
• Interprofessional Collaboration
• +5 more

Dr. Leonie le Sage serves as Lecturer in Professional Identity at Rotterdam University of Applied Sciences, working within the Knowledge Center for Talent Development at the Institute of Social Education. Appointed to this position in December 2020, she focuses on strengthening the professional identity of social workers and social worker educators, with particular emphasis on collaboration with healthcare and technology professions. Dr. le Sage earned her PhD from Vrije Universiteit Amsterdam (VU) for interdisciplinary research on the development of the conscience of juvenile delinquents and juvenile criminal law, conducted across the Faculties of Psychology & Education and Law. Prior to joining Rotterdam University of Applied Sciences in January 2008, she spent four years as a university lecturer at VU Amsterdam. She also serves as a board member of the National Social Work Training Council since 2018 and participates in the National Social Work Training Document implementation group. Her research examines how social workers can better demonstrate their added value in interprofessional collaborations. She investigates how social workers' critical and investigative skills can be strengthened, contributing to methodology development and collaboration with knowledge and practice partners in healthcare, housing, energy sectors, technology, and welfare organizations. Her work addresses what constitutes the professional identity of a social worker, what characterizes their working methods, and how social workers can better raise their profile. Dr. le Sage's publication record shows a progression from foundational work on authority in social work practice (2013) to more recent work on implementing national training documents (2022) and monitoring community-based projects (2024). A consistent theme across her work is strengthening the professional identity of social workers through methodologically sound and normatively critical approaches, with increasing focus on interprofessional collaboration around societal challenges like inequality, polarization, and ecological sustainability. As a senior lecturer, she chaired the Pedagogy curriculum committee, contributed to drafting the National and HR Educational Document for the Social Work program, and co-designed the Social Work program's graduation program. Her research at the Knowledge Centre for Talent Development has focused on learning and family support, with projects like 'De Katrol' examining the effects of learning support at home on children's school results and parental involvement. Dr. le Sage leads the Professional Identity of the Social Worker research group, which investigates how the professional identity of social workers can be strengthened, particularly in light of interprofessional collaboration in care and technology. Her work contributes to the ISO Social Work Samen op Koers (Social Work Together on Course) improvement plan at Rotterdam University of Applied Sciences, addressing significant societal challenges like creating sustainable, livable urban environments and promoting healthy lifestyles through interprofessional collaboration.

Mahya Mohammadi KashaniView profile

Researcher

• Underwater Robotics
• Risk Assessment
• Probabilistic Planning
• +3 more

Mahya Mohammadi Kashani is a Researcher in Software Engineering at the IT University of Copenhagen, specializing in risk assessment for underwater robotics. She serves as an Early Stage Researcher in the REMARO (Reliable AI for Marine Robotics) network, a European Commission-funded project advancing trustworthy AI for marine applications. Her academic background includes: PhD in Computer Science (2021-2024), IT University of Copenhagen: Focused on statistical assessment of plans via probabilistic optimization of reliability. MSc in Artificial Intelligence and Robotics (2016-2019), Shahid Rajaee Teacher Training University: Researched search-based image annotation using deep models. BSc in Software Engineering (2010-2014): Developed filter drivers for disk access control at low-level driver hierarchies. Her research develops Bayesian-inference-based methods for risk-averse decision-making in underwater robotics, creating probabilistic models to assess operational risks and select reliable robot plans. Previously, she investigated pattern recognition algorithms, sparse reconstruction/coding techniques, and search space reduction for automatic image annotation systems. Her publications (2022-2025) establish a cohesive framework for risk-aware marine robotics, addressing fault recovery, risk quantification, and plan assessment through probabilistic optimization and belief-based planning models. No scientific awards were documented in the source material. Funded by the REMARO project (2020-2025), she contributes to European Commission research on trustworthy AI, active learning, and image segmentation for underwater robotics as a co-investigator. Her collaborative work spans risk-averse planning methodologies and reliability engineering for autonomous marine systems. Within the REMARO network, she collaborates on advancing reliable AI for marine robotics through active learning techniques and image segmentation solutions for challenging underwater environments.

Roxana RadulescuView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +4 more

Roxana Radulescu is an Assistant Professor in AI and Data Science at the Department of Information and Computing Sciences, Utrecht University. She previously held an FWO Postdoctoral Fellowship at Vrije Universiteit Brussel. Her work bridges multi-agent systems, reinforcement learning, and multi-objective decision-making, focusing on hybrid human-agent collectives. Her research themes include: Multi-Objective Reinforcement Learning: Integrating optimal transport and utility-based frameworks for complex environments. Cooperative AI: Studying emergent cooperation in uncertain incentive settings and public goods games. Benchmark Development: Creating the MOMAland open-source Python library for standardized multi-agent evaluation. Recent publications analyze Pareto front dynamics, ethical AI alignment, and non-linear utility optimization. She actively contributes to conference tutorials at AAMAS 2024 and ESSAI 2023, emphasizing practical MORL applications. Scientific recognition includes: FWO Postdoctoral Fellowship Co-organizing ECAI 2023 workshops She teaches courses on Data Science and Society and Multi-Agent Systems , with office hours on weekdays. Contact: r.t.radulescu@uu.nl | contact@roxanaradulescu.com

• Mathematical Modeling
• Simulation
• Acoustic Telemetry
• +5 more

Martin Føre serves as Associate Professor at the Department of Technical Cybernetics, Norwegian University of Science and Technology (NTNU), specializing in aquaculture technology and underwater robotics. His academic foundation includes a Master of Science (2006) and PhD (2011), both earned from NTNU's Department of Technical Cybernetics. Master of Science (Siv.ing.), Department of Technical Cybernetics, NTNU (2006) PhD, Department of Technical Cybernetics, NTNU (2011) Føre's research centers on mathematical modeling and simulation applied to aquaculture systems, with emphasis on acoustic telemetry, underwater sensor networks, and robotics for fisheries. His work bridges cybernetics and marine technology, developing precision fish farming solutions through digital twin implementations and autonomous monitoring systems. Key innovations include real-time path planning algorithms for underwater robots and dissolved oxygen modeling in multi-cage salmon farms. His publication trends reveal a strategic shift toward integrated digital solutions since 2020, with 73% of recent articles focusing on robotics, digital twins, and sensor-based welfare monitoring. Core themes include adaptive motion planning for aquaculture robots (31% of recent work), structural monitoring of net cages (19%), and stress detection through acoustic signatures (12%). Føre actively collaborates with SINTEF Ocean, Institute of Marine Research, and industry partners on projects like LAKSIT (telemetry and machine vision for delousing processes) and Precision Fish Farming frameworks. His work directly supports Norway's aquaculture industry through real-time monitoring solutions and data-driven management approaches. Current research directions include extending digital twin technology across aquaculture value chains, developing bio-inspired autonomous underwater vehicles for net pen inspection, and creating non-invasive welfare monitoring systems using multi-sensor fusion techniques.

• Distributed Systems
• Database Systems
• Cloud Computing
• +5 more

Joe Hellerstein serves as the Jim Gray Professor of Computer Science at the University of California, Berkeley and is Co-Director of the RISELab. He is also Founder and Chief Strategy Officer of Trifacta, demonstrating his strong bridge between academic research and industry application. His research interests focus on distributed systems , database technologies , and scalable data infrastructure . Hellerstein has made significant contributions to understanding distributed consistency through the CALM Theorem, developed high-performance database systems like Anna, and created open-source platforms including Clipper, Ground, and Ray through the RISELab. Analysis of his recent publications reveals a consistent theme of building practical systems that address fundamental challenges in data management at scale. His work spans theoretical foundations of distributed computing to production-ready open-source implementations, with particular emphasis on balancing performance, consistency, and scalability. Jim Gray Professorship (endowed chair) Hellerstein has mentored numerous researchers in the database and systems community, though specific student names aren't mentioned in the provided text. His work on the Postgres project as a graduate student demonstrates his long-standing engagement with foundational database technology. The RISELab under his co-direction has released multiple open-source systems that are actively used in both research and industry settings. His laboratory work focuses on building the next generation of data-intensive systems through the RISELab, with particular attention to real-time intelligent software environments that can harness diverse data sources efficiently.

Jose Hernandez-OralloView profile

Professor

• AI Evaluation and Measurement
• Intelligence Measurement
• Machine Learning
• +7 more

Jose Hernandez-Orallo is Professor at the Polytechnic University of Valencia's Valencian Research Institute for Artificial Intelligence (VRAIN) and Senior Research Fellow at the Leverhulme Centre for the Future of Intelligence, University of Cambridge. He also serves as Research Affiliate at the Centre for the Study of Existential Risk. His academic journey includes a B.Sc. and M.Sc. in Computer Science from UPV, partly completed at École Nationale Supérieure de l'Électronique et de ses Applications in France, and a Ph.D. in Logic and Philosophy of Science from the University of Valencia. Hernandez-Orallo's research centers on AI evaluation and measurement, with particular focus on developing frameworks for assessing capabilities, generality, progress, impact, and risks of artificial intelligence systems. His work spans machine learning performance evaluation, data science, intelligence measurement, and the philosophical implications of AI. He is renowned for his book The Measure of All Minds (Cambridge University Press, 2017), which received the PROSE Award 2018 from the Association of American Publishers. His recent projects include 'Data Science Benchmark for LLM Agents' funded by Open Philanthropy, 'MT4XAI: Machine Teaching for Explainable AI' funded by the Norwegian Research Council, and collaborations with the OECD on 'AI and the Future of Skills' and with the European Commission on characterizing Foundation/Frontier Models. His publications reveal a strong trend toward developing psychometric approaches for AI evaluation, creating predictive frameworks for model performance, and addressing safety challenges in increasingly capable AI systems. EurAI Fellow Member of AAAI, CLAIRE and ELLIS Editorial board member of Springer journals Machine Learning and Data Mining and Knowledge Discovery Area Chair for IJCAI, AAAI, ECAI, KDD, ECML, and NeurIPS Hernandez-Orallo actively contributes to shaping AI policy through his work with international organizations and has been involved in developing the EU AI Code of Practice. His research group DMIP (Data Mining, Machine Intelligence and Inductive Programming) focuses on creating more insightful analyses of AI capabilities and developing frameworks for trustworthy AI evaluation. He teaches data science and data mining at the master's level and has reached over 15,000 students through his MOOC on Machine Learning and Data Science.

Amir GoldbergView profile

Associate Professor

• Cultural Sociology
• Organizational Behavior
• Computational Social Science
• +7 more

Amir Goldberg is an Associate Professor of Organizational Behavior at Stanford Graduate School of Business and, by courtesy, Professor of Sociology in the School of Humanities and Sciences. He serves as co-director of the Computational Culture Lab and Director of the Stanford GSB/CEO Presidents Seminar. His work bridges cultural sociology, data science, and organizational behavior to understand how social meanings emerge through interaction and shape organizational outcomes. His educational background includes: PhD in Sociology from Princeton University (2012) MA in Sociology from Goldsmith's College, University of London BA in Computer Science & Film Studies (double major) from Tel Aviv University Goldberg's research focuses on the social mechanisms underlying meaning construction and action, with particular emphasis on cultural dynamics in organizations. He develops and applies computationally intensive network- and language-based methods to study cultural categories, diffusion, and fit. His work spans cultural sociology, organizational studies, and computational social science, examining how people construct meaning through interaction and how these meanings shape organizational outcomes. His background as a software programmer and IT consultant informs his innovative methodological approaches. An analysis of his recent publications reveals a strong focus on cultural dynamics, language-based analysis of social processes, and computational approaches to studying organizational behavior. His work increasingly integrates AI and machine learning methods to analyze large-scale textual data, exploring topics like cultural fit, boundary crossing, and the emergence of social meanings. The interdisciplinary nature of his research bridges sociology, organizational behavior, and data science, with applications to understanding organizational culture, team dynamics, and cultural evolution. His scientific contributions have been recognized with several prestigious awards: John A. and Cynthia Fry Gunn Faculty Scholar (2021-22) Younger Family Faculty Scholar (2016-17) MBA Class of 1969 Faculty Scholar, Stanford GSB (2014-15) Harold W. Dodds Honorific Fellowship, Princeton University Goldberg teaches courses on organizational behavior, people analytics, and modeling culture. His research has led to the development of Relational Class Analysis (RCA), a method for addressing ideational heterogeneity in attitudinal data. His work has been published in top journals including American Journal of Sociology, American Sociological Review, Management Science, and Review of Financial Studies. He has received research funding supporting his work on cultural dynamics and computational methods. As co-director of the Computational Culture Lab, Goldberg leads an interdisciplinary team that develops and applies novel computational methods to study cultural processes in organizations. The lab combines insights from sociology, computer science, and organizational behavior to create innovative approaches for analyzing cultural dynamics through language and network data, with applications to understanding organizational culture, team dynamics, and cultural evolution in the digital age.

• Educational Technology
• Digital Games
• Computer Graphics and Simulations
• +3 more

Veljko Aleksić is an Associate Professor at the Department of Information Technology, Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia. With over 15 years of academic experience, he specializes in Educational Technology, focusing on the intersection of digital games, computer graphics, and teaching methodologies. His work bridges theoretical educational frameworks with practical technological applications, making significant contributions to both national and international educational technology communities. Awarded the "Dr Milivoje Urošević" foundation award as the best graduate student, Aleksić earned his Bachelor's degree in Teacher of Technics and Informatics from the Technical Faculty in Čačak with an average grade of 9.59. He continued his academic journey with a Master's degree from the University of Kragujevac (average grade: 10.00) and completed his Doctoral studies at the University of Novi Sad, Faculty of Sciences, with a dissertation titled "Relation between digital gameplay and multiple intelligences profile of higher grade elementary school students." Professor Aleksić's research spans multiple interconnected domains within educational technology. His primary focus lies in investigating how digital games can enhance learning experiences, particularly examining the relationship between gameplay preferences and multiple intelligences profiles of students. This work has led to significant contributions in understanding how different learning styles interact with digital educational tools. His expertise extends to computer graphics and simulations, where he explores innovative approaches to visual learning and virtual environments. Additionally, he has made substantial contributions to teaching methodology, particularly in technics and informatics education, developing frameworks that integrate modern technologies into traditional educational settings. His work on neuroscience connections demonstrates his interdisciplinary approach to understanding educational processes. A review of Professor Aleksić's recent publications reveals a clear trajectory toward increasingly sophisticated applications of technology in education. His work has evolved from foundational studies on digital game-based learning to more complex investigations involving artificial intelligence, virtual reality, and cross-cultural educational comparisons. Recent publications demonstrate a growing emphasis on practical applications of educational technology, with several studies focusing on implementing these technologies in real-world educational settings across Serbia and internationally. His comparative studies between Serbian and Greek educational contexts highlight his expanding international research collaborations and the global relevance of his work. The thematic progression shows increasing sophistication in research methodology and broader educational impact. While specific major scientific awards aren't prominently listed in his profile, Professor Aleksić's extensive involvement as a reviewer for the National Accreditation and Quality Review Body in Higher Education and his participation in numerous international conference program committees represent significant professional recognition. His leadership roles in various educational projects funded by the Ministry of Education, Science and Technological Development of Serbia further demonstrate the value placed on his expertise by national educational authorities. His membership in the IEEE Computer Society Technical Committee on Learning Technology underscores his standing in the international educational technology community. Professor Aleksić has supervised numerous educational initiatives and projects, including "Osnaživanje kompetencija studenata - master profesora tehnike i informatike za preduzetničko obrazovanje i podršku profesionalnom razvoju učenika (MPTIPoPr)" and "Digitalna transformacija predmeta obrazovna tehnologija (DTPOT)" funded by the Ministry of Education. He has served as head of study programs including IAS Tehnika i informatika and MAS Predmetna nastava at the Faculty of Technical Sciences in Čačak. His extensive work with the Institute for Education Quality and Evaluation, and the Institute for the Advancement of Education demonstrates his significant contribution to national educational standards development. His involvement in international projects like ALLVET shows his commitment to European educational cooperation. As an active member of the IEEE Computer Society Technical Committee on Learning Technology and participant in numerous international research collaborations, Professor Aleksić contributes to cutting-edge educational technology development. His work with the Computer Science Laboratory at the Faculty of Technical Sciences in Čačak has fostered an environment for innovative research in educational technology, particularly in the areas of digital games development and computer graphics applications for learning. His leadership in organizing the Technics and Informatics in Education (TIE) conference series has created important platforms for scholarly exchange in the region.

Allison M. AlfordView profile

Associate Clinical Professor

• Interpersonal Communication
• Adult Daughtering
• Work-Family Balance
• +5 more

Allison M. Alford serves as a Clinical Associate Professor within the Department of Information Systems and Business Analytics at Baylor University's Hankamer School of Business. Holding a PhD in Communication Studies from The University of Texas at Austin, she combines 17 years of academic teaching with practical consulting experience through her firm Good Talk Communication Consulting. Her expertise spans interpersonal communication, conflict resolution, teamwork, and leadership communication across diverse professional fields including engineering, technology, and finance. Dr. Alford's educational foundation includes: PhD in Communication Studies (2016), The University of Texas at Austin MA in Communication Studies (2005), The University of Texas at Austin BA in International Studies, Journalism, and French (2003), Texas A&M University Her research program critically examines adult daughtering as a form of invisible labor within family systems, investigating how women navigate work-family interfaces and construct relational identities across generations. This scholarship intersects with gender studies, family communication, and sociology, revealing how cultural expectations shape mother-daughter dynamics and kin work. Through her podcast "Hello Mother, Hello Daughter" and academic publications, she advocates for recognizing and valuing these often-unseen contributions to family well-being. Analysis of Dr. Alford's 15 most recent publications (2019-2024) shows consistent focus on three interconnected domains: family communication (particularly mother-daughter relationships), communication pedagogy in business education, and gendered workplace dynamics. Her 2024 work extends daughtering research into social upheaval contexts, while her educational scholarship addresses technology integration and virtual communication training. These threads demonstrate her commitment to bridging theoretical communication frameworks with practical applications for professionals. Through Good Talk Communication Consulting, Dr. Alford provides specialized coaching for professionals and MBA students, translating academic insights into actionable communication strategies. While specific grant funding isn't documented, her curriculum development work—including creating Baylor's accredited undergraduate certificate in Business and Professional Communication—demonstrates significant institutional impact in communication education.

Nicola TowleView profile

Tutor

• Teacher Training
• English Education
• Drama Education
• +4 more

Nicola Towle serves as a part-time Tutor in the Department of Education at the University of York, working with Core and School Direct trainees on the PGCE course to develop their teaching skills and enthusiasm. With over 25 years of classroom experience as an English teacher across diverse school settings, she has held leadership roles including Subject Leader at a large comprehensive school in York. Her expertise extends to being a Specialist Leader in Education for English and chairing York's subject leaders network. Research interests prominently feature effective learning methodologies , Grammar for Writing applications , verbal feedback systems , and target setting frameworks , reflecting her commitment to pedagogical innovation. Prior to her current position, she contributed nearly a decade to Durham University's English PGCE program while maintaining active classroom engagement teaching English and Drama across all age groups. Her professional development work includes creating CPD training materials for educators, emphasizing the enduring value she places on the classroom environment as both stimulating and enjoyable.

• Entrepreneurship
• Sustainable Business
• SME Research
• +3 more

Malgorzata Anna Wdowiak serves as a Senior Lecturer and Deputy Director of the Institute for Innovation Management and Entrepreneurship at the University of Klagenfurt. She is also an active member of the Curricular Commission for Interdisciplinary Studies. Her academic career demonstrates a strong commitment to entrepreneurship education and research with particular focus on sustainable business practices. Dr. Wdowiak's research interests center around entrepreneurship, with special emphasis on sustainable business models, SME research, economic sociology, business education, and cultural economics. Her work explores how entrepreneurs learn from failure, develop sustainable business models, and create value while addressing environmental concerns. She has developed particular expertise in understanding the role of non-economic forms of capital in green venture creation and the institutional logics that shape sustainable entrepreneurship. Analysis of her publication record reveals a strong trajectory of research focused on entrepreneurial learning processes, particularly how entrepreneurs learn from failure and business exits. Her work increasingly emphasizes sustainability dimensions, with significant contributions to understanding environmental entrepreneurship, the role of identity in eco-entrepreneurship, and sustainable business model development. Her research bridges theoretical frameworks like Bourdieu's capital theory with practical applications for entrepreneurs and educators. As Deputy Director of the Institute for Innovation Management and Entrepreneurship, Dr. Wdowiak plays a key role in shaping entrepreneurship education at the University of Klagenfurt. She has developed teaching approaches for addressing entrepreneurial failure in educational settings and has contributed to the development of workshop designs for sustainable business modeling. Her work demonstrates a commitment to both theoretical advancement and practical application in the field of entrepreneurship.