Find Academic Supervisors

• Political Economy
• Economic Growth
• Innovation Economics
• +3 more

Rainer Andergassen is an Associate Professor in the Department of Economic Sciences at the University of Bologna. His research focuses on political economy, economic growth, innovation dynamics, and tourism economics. He holds a formal affiliation with the University of Bologna's Department of Economic Sciences and maintains an ORCID profile. His work bridges theoretical economic modeling with applied policy analysis, particularly in areas of innovation diffusion, structural change, and tourism destination management. Education details are not explicitly provided in the text, but his academic trajectory aligns with typical senior faculty roles. Research interests include intergenerational mobility, technological convergence, and public policy design for tourism sectors. His recent publications (2012-2021) explore topics like innovation networks, disaster mitigation economics, and fraudulent behavior in competitive markets. Dr. Andergassen's academic contributions span 20+ years with articles addressing: (1) innovation's role in economic growth through structural transformation, (2) strategic tourism destination management frameworks, and (3) behavioral economic factors influencing managerial fraud. His work frequently integrates mathematical modeling with real-world policy implications. No formal awards or grants are listed, though his extensive publication record indicates sustained research activity. He is available for consultations at his office (Piazza Scaravilli 2, Bologna) on Wednesdays at 11:30am.

Stanka FitnevaView profile

Associate Professor

• Developmental Psychology
• Language Acquisition
• Social Cognition
• +3 more

Stanka Fitneva is an Associate Professor and Chair of the Developmental Psychology Program at Queen's University's Department of Psychology. She holds a B.A. from Smith College (1996) and a Ph.D. from Cornell University (2003). Her research focuses on language acquisition, social cognition, and the development of children's understanding of knowledge sources, including evidentiality, cultural influences, and memory. She explores questions like how children gather information, assess reliability of sources, and represent the social world. Her work integrates experimental methods to study topics such as cross-situational word learning, the role of context in communication, and the cognitive mechanisms underlying social information processing. Notable research includes investigations into children’s beliefs about knowledge distribution across cultures (e.g., Japanese vs. Canadian children) and the impact of epistemic framing on communication strategies. Recent articles highlight themes such as error correction mechanisms in word learning, psychosocial factors in neurodevelopmental disabilities, and the interplay between epistemic emotions and decision-making. Her findings contribute to theoretical frameworks in developmental psychology and cognitive science, emphasizing the social and linguistic foundations of cognitive development. No scientific awards are explicitly mentioned in the provided text. Her advising and grants activities are not detailed, though her lab site and CV suggest active research collaborations. She maintains a lab focused on developmental psychology, exploring topics like evidentiality and social cognition through experimental paradigms.

Bronwen PowellView profile

Assistant Professor

• Food Security
• Agroecology
• Forests and Nutrition
• +3 more

Bronwen Powell is an Assistant Professor of Geography, African Studies, and Anthropology at Pennsylvania State University, located in the College of Earth and Mineral Sciences. Her work focuses on the intersection of food systems, environmental sustainability, and cultural practices, particularly in Africa and Mediterranean regions. She explores how forests, wild foods, and traditional knowledge contribute to dietary diversity and food security in the context of climate change and agrarian transformation. Her research emphasizes interdisciplinary approaches to understand how landscapes shape nutrition outcomes. Key themes include agroecology, the role of biodiversity in food production, and the impacts of deforestation on rural communities. Powell’s studies often integrate ecological data with socioeconomic analyses, highlighting the importance of integrating wild food resources into climate adaptation strategies. Her recent work examines dietary transitions in tropical regions, the governance of forested landscapes, and the transmission of traditional ecological knowledge. Powell has contributed to international initiatives like the Forests, Trees, and Agroforestry (FTA) program, analyzing decade-long impacts on food security and nutrition policies. While specific grants or advising details are not highlighted in the provided texts, her publications consistently address policy-relevant solutions for sustainable food systems. Powell’s research frequently involves collaborative projects with international organizations and local communities, reflecting her commitment to applied anthropological and geographical methodologies.

• African Linguistics
• Language Documentation
• Phonetics
• +6 more

Prof. Roland Kießling is a Professor of African Studies at the University of Hamburg's Faculty of Humanities, affiliated with the Asia-Africa Institute's Department of African and Ethiopian Studies. He has held visiting professorships at the Universities of Bayreuth and Cologne, and served as a DFG Heisenberg Fellow (2001–2006). His research focuses on African languages, particularly Southern Cushitic, Nilotic, Niger-Congo, and Khoisan languages, emphasizing documentation, phonetics, morphosemantics, and language change. Academic Career: Studied at University of Hamburg (African Studies, Phonetics), M.A. 1988, Ph.D. 1993, Habilitation 2000 1990–1993: Research Associate in the DFG 'Iraqw Texts' project 1993–1999: Research Assistant at Hamburg's Institute for African and Ethiopian Studies Recipient of the Kurt-Hartwig-Siemers Prize (1995) Since 2006: Full Professor at University of Hamburg Research Interests: Documentation of endangered African languages, phonetic transcription, morphosemantics, language contact, and historical linguistics. Specializes in Cushitic (Southern), Nilotic (Southern), Niger-Congo (South Bantoid), and Khoisan languages including !Xoon. Key Projects (selection): Cluster of Excellence 'Understanding Written Artefacts' (2019–2025) DFG SFB 950 'Manuscript Cultures' (2011–2020), leading subproject C07 on Arabo-Swahili manuscripts DoBeS-funded documentation projects for Bezen (2011–2015) and Datooga motion lexico-grammar (2018–2022) Publications: Over 59 publications including monographs on Isu (West Ring Bantu), edited volumes on African linguistics, and articles in Journal of African Languages and Linguistics , Afrika und Übersee , and others. Recent work explores numeral classifiers, hybrid youth discourse, and tonogenesis. Awards: Kurt-Hartwig-Siemers Prize (1995), Heisenberg Fellowship (2001–2006), and contributions to major linguistic reference works like The Oxford Handbook of African Languages .

• Digital Humanities
• Text Mining
• Artificial Intelligence in Education
• +3 more

Dr. Ahmed Taiye Mohammed holds a Postdoctoral research fellowship at Linnaeus University's Department of Cultural Sciences, Faculty of Arts and Humanities in Växjö, Sweden. He earned his Master's and PhD from Northern University of Malaysia (UUM) with a thesis on text anomaly detection. His research focuses on Digital Humanities (DH), AI applications in education, and computational thinking for non-engineers. He teaches courses like Digital Humanities Research Methods, Programming for DH, and AI in Healthcare. Key research projects include InKuiS (innovative cultural entrepreneurship) and AI for ISP (supporting academic writing via ChatGPT). He collaborates with Linnaeus University Centre for Data Intensive Sciences (DISA) on e-health initiatives. Recent publications explore AI in K-12 education, automated library classification, and text mining for archaeology. His work spans AI ethics, DH methodologies, and interdisciplinary applications of computational tools. Teaching responsibilities include over 10 courses at undergraduate/master's levels, emphasizing practical skills in DH technologies. Active in developing AI-based educational tools like CHAT4ISP-AI and exploring generative AI for academic writing support. Research also involves social media ecosystems, data mining practices, and satellite image classification using SVM techniques.

• Thoracic Imaging
• Radiology
• Pulmonary Diseases
• +3 more

Leah Traube is an Assistant Professor of Radiology and Biomedical Imaging at Yale School of Medicine. She is affiliated with the departments of Cardiothoracic Imaging and Clinical Radiology. Her research focuses on thoracic imaging, pulmonary diseases, and cardiovascular imaging, with a strong emphasis on CT scan analysis, lung lesions, and immune therapy complications. Her recent publications highlight studies on ophthalmic-thoracic disorders, ICU imaging protocols, and trends in ground-glass nodules. She collaborates frequently with clinicians like Anna Shlionsky Bader and Babina Gosangi. No scientific awards or grants are explicitly listed in the provided texts. No formal advisees or lab affiliations are mentioned. Her work bridges clinical radiology with emerging diagnostic techniques in thoracic and cardiovascular fields.

• Neuroscience
• Psychiatry
• Neuropharmacology
• +3 more

Jocelyne Rondeau is a Researcher in the Department of Psychiatry at Yale School of Medicine, Yale University. Her work focuses on neuropharmacology, mental health treatment, and clinical trials, with particular expertise in neurotransmitter dynamics and psychedelic drug mechanisms. She has contributed to studies analyzing c-Fos expression in brain imaging, norepinephrine's role in threat prediction, and the therapeutic potential of ketamine for Borderline Personality Disorder. Her research integrates neuroimaging techniques, computational models, and behavioral experiments to understand neural mechanisms underlying psychiatric conditions. Notable projects include classification systems for psychedelic drugs and pilot trials evaluating novel therapeutic approaches. No academic awards are explicitly mentioned in the provided texts. Her current role does not involve direct student advisement, though her research collaborations may involve postgraduate trainees. She is affiliated with Yale's Psychiatry department and contributes to interdisciplinary studies at the School of Medicine.

Javier OsorioView profile

Assistant Professor

• Political and Criminal Violence
• Comparative Politics
• Natural Language Processing
• +3 more

Javier Osorio is an Assistant Professor at the University of Arizona's School of Government and Public Policy. His research focuses on the micro-foundations and dynamics of political and criminal violence in Latin America, employing quantitative methods such as natural language processing, GIS, and big data analytics. He has received awards from the UNODC and MPSA, and his work appears in leading journals like the Journal of Peace Research . Dr. Osorio holds a Ph.D. in Political Science from the University of Notre Dame (2013) and previously taught at John Jay College of Criminal Justice. He leads the Academy for Security Analysis, funded by USAID, and collaborates with the NSF and DoD’s Minerva Initiative. His research projects include supervised event coding for conflict analysis and randomized controlled trials in Central America. His key contributions span conflict language models (e.g., ConfliBERT), criminal violence classification, and multilingual event coding frameworks. He has advised interventions in El Salvador and Nicaragua, emphasizing data-driven approaches to security challenges.

• Group Theory
• Algebra
• Coding Theory
• +3 more

Mima Stanojkovski is an Assistant Professor at the Department of Mathematics, University of Trento. Her research focuses on group theory, algebra, and their applications in coding theory and cryptography. She teaches courses such as Algebra B, Statistics for Data Science, and Teoria dei Gruppi, emphasizing foundational concepts in abstract algebra and their practical implications. Teaching Responsibilities: Algebra B (Department of Mathematics) Statistics for Data Science (Department of Sociology and Social Research) Teoria dei Gruppi (Department of Mathematics) Research Interests: Mima's work centers on geometric and combinatorial aspects of finite groups, modular group algebras, and cryptographic applications of algebraic structures. She explores topics such as independence complexes, rank-metric codes, and pro-p group constructions. Her recent publications address conjectures in coding theory and security analyses of homomorphic encryption schemes. Grants & Collaborations: No grants or collaborative projects explicitly listed in the provided text. Labs/Teams: No specific lab affiliations or research teams mentioned.

Zhaozheng ChenView profile

Researcher

• Computer Vision
• Machine Learning
• Deep Learning
• +3 more

Zhaozheng Chen is a Research Scientist at Singapore Management University (SMU), affiliated with the School of Computing and Information Systems (SCIS) and the Department of Computer Science. He holds a Ph.D. in Computer Science from SMU (2020–2023) and a B.Sc. in Computer Science and Technology from Shandong University (2015–2019). His research focuses on computer vision and machine learning, with particular emphasis on weakly-supervised learning, semantic segmentation, and deep learning applications in multi-task frameworks. **Education**: Ph.D. in Computer Science, Singapore Management University (Jan 2020 – Dec 2023; Advisor: Prof. Qianru Sun) B.Sc. in Computer Science and Technology, Shandong University (Sep 2015 – Jun 2019; Advisor: Prof. Liqiang Nie) **Research Interests**: Zhaozheng’s work spans computer vision, machine learning, and deep learning, with recent contributions to weakly-supervised semantic segmentation, class activation maps, and multi-task learning for urban perception. He also explores applications in virtual try-on systems and text classification. **Awards**: He has been awarded the SMU Presidential Doctoral Fellowship (2022/2023 and 2023/2024), the SCIS Dean’s List (2023), and national scholarships for academic excellence. Notably, he secured a Bronze Medal in the ACM-ICPC Asia Regional Contest and a Meritorious Winner title in the Mathematical Contest in Modeling. **Teaching & Work Experience**: He served as a Teaching Assistant for CS 701 (Deep Learning and Vision) at SMU (2021–2022). Prior to his Ph.D., he interned at YouTu Lab, Tencent (Oct 2018 – Jan 2019), working under Dr. Xiaoyong Shen. Currently, he advises under Prof. Qianru Sun’s research group and contributes to open-source projects like ReCAM and LPCAM on GitHub. **Professional Services**: He actively reviews for top conferences including BMVC, ICCV, ECCV, IJCAI, CVPR, and journals such as IJCV, IEEE TPAMI, and ACM TOMM.

Fred PopowichView profile

Professor

• Natural Language Processing
• Artificial Intelligence
• Big Data
• +4 more

Fred Popowich is a Professor in the School of Computing Science at Simon Fraser University (SFU), Canada. He holds adjunct positions at Dalhousie University's Faculty of Graduate Studies and is an Associate Member of SFU's Department of Linguistics and Cognitive Science Program. His academic career began post-PhD (Cognitive Science/Artificial Intelligence, University of Edinburgh, 1989) and has spanned over three decades at SFU. Education: PhD in Cognitive Science/Artificial Intelligence (University of Edinburgh, 1989); M.Sc. and B.Sc. in Computing Science (Simon Fraser University and University of Alberta, 1985/1982). Research focuses on natural language processing (NLP), machine translation, intelligent systems, and big data applications. He directs SFU’s Big Data Initiative and leads the Natural Language Laboratory, supervising MSc/PhD students in computing science. His work includes developing systems for smart homes, toxic language detection in social media, and energy grid analysis. Industry roles include co-founding Axonwave Software (as CTO/President) and contributing to technology commercialization. Current projects address EV charging impacts, personalized learning systems, and real-time load monitoring. Publications span machine translation, sentiment analysis, and NLP applications in education and energy systems. His work bridges theoretical computer science with practical applications in healthcare, smart cities, and education.

Arash Habibi LashkariView profile

Associate Professor

• Cybersecurity
• Network Security
• Threat Hunting
• +7 more

Dr. Arash Habibi Lashkari is an Associate Professor and Canada Research Chair in Cybersecurity at York University's School of Information Technology. He holds a PhD from the University of Technology Malaysia and completed a Post-Doc at the University of New Brunswick. With over 25 years of teaching experience, he specializes in cybersecurity risk management, malware analysis, and threat hunting. He pioneered Canada’s first cybersecurity Capture the Flag (CTF) competition for post-secondary students and has authored 10 books and over 110 academic articles. Research Interests: Cybersecurity, Network Security, Threat Hunting, Malware Analysis, Cybersecurity Risk Management, and Blockchain Security. He leads the Behaciour-Centric Cybersecurity Center (BCCC), focusing on vulnerability detection technologies and cybersecurity dataset generation. Awards: Mitacs 150 Top Researchers (2017), University of New Brunswick Teaching Innovation Award (2020), Gold Medal at 2020 Canadian Online Publishing Awards, and multiple international security competition awards. His work has been featured in CBC, CIC, and global cybersecurity conferences. Key Projects: Development of intrusion detection datasets (e.g., CIRA-CIC-DoHBrw-2020), malware analysis frameworks, and AI-driven cybersecurity tools. He actively collaborates with organizations like Aviva and NICT on cybersecurity resilience strategies. Teaching: Offers courses in Digital Forensics, Network Security, and Cybersecurity Management. His 'Think-Que-Cussion' teaching methodology emphasizes interactive learning.

Ricardo A. CalixView profile

Professor

• Machine Learning
• Natural Language Processing
• Deep Learning
• +4 more

Ricardo A. Calix is a Professor of Computer Information Technology at Purdue University Northwest. His research focuses on Machine Learning, Natural Language Processing, AI applications in Cyber Security and Healthcare, and Deep Learning methodologies. He holds a Ph.D. in Engineering Science from Louisiana State University. Key research areas include ethical AI model analysis, reinforcement learning for aerospace control systems, and industrial automation through machine learning. His work spans cybersecurity tools (e.g., CyberSecTK) and healthcare data mining from social media. Calix has secured grants as PI/Co-PI for projects like 'Detection of Potential Drug Effects from Twitter Data' (NIH) and 'A Smart and Fast IDS' (Northrop Grumman). He authored Getting Started with Deep Learning: Programming and Methodologies Using Python (2017). Recent publications (2023-2024) address biases in AI models, blast furnace automation, and autonomous aircraft control via reinforcement learning. His work bridges theoretical AI with practical applications in industry and security.

Eelke BosView profile

Researcher

• Neurosurgery
• Neuro-oncology
• Meningioma
• +7 more

Eelke Bos is a researcher in the Department of Neurosurgery at Erasmus MC, actively contributing to clinical and translational neuro-oncology research. His work focuses on improving outcomes in meningioma and glioblastoma patients through surgical innovation, molecular classification, and functional assessment. Research Interests: His primary fields include neurosurgery, neuro-oncology, meningioma, glioblastoma, molecular tumor classification, and functional neurosurgery. He investigates how surgical techniques and adjuvant therapies impact patient outcomes, particularly in eloquent brain areas. The recent publications reveal a strong trend in using multicenter data and molecular markers to guide treatment decisions in brain tumors. His research emphasizes evidence-based surgical practices, functional preservation, and precision oncology in neurosurgical care. No scientific awards mentioned in the text. Advising and Grants: While specific grants are not detailed, his involvement in large consortia such as the International Consortium on Meningiomas (ICOM) and the Dutch Brain Tumour Registry suggests collaborative funding and national/international research support. He has supervised at least one junior researcher, indicating an emerging mentoring role. Labs and Teams: Eelke Bos is embedded in a multidisciplinary neurosurgical and neuro-oncology team at Erasmus MC, collaborating with experts in neuroimaging, radiation oncology, and molecular pathology. He contributes to both national registries and global research networks focused on brain tumor outcomes.

Alexander Miserlis HoyleView profile

Researcher

• Computational Social Science
• Natural Language Processing
• Machine Learning
• +6 more

Alexander Hoyle is a Researcher at the ETH Zürich AI Center, concurrently contributing to natural language processing/machine learning and social science groups. He holds a PhD in Computer Science from the University of Maryland (advised by Philip Resnik) and a Master's in Computational Statistics from University College London (advised by Sebastian Riedel and Jeff Mitchell). His research focuses on computational social science, emphasizing methods for latent construct identification (e.g., topic models, ideal point models) and evaluation frameworks grounded in validity. Key areas include bias/fairness in AI, political science applications, and mental health constructs like suicidality. He pioneered frameworks like PairScale (attitude measurement via pairwise comparisons) and TopicGPT (prompt-based topic modeling). Education: PhD in Computer Science, University of Maryland (2020-2023) MS in Computational Statistics & Machine Learning, University College London (2018) Bachelor's degree (pre-PhD details omitted) Research Interests: Combining NLP with social science needs, particularly in evaluation rigor and interpretability. Active in interdisciplinary work between NLP and computational social science (e.g., measuring attitude evolution on Reddit, improving topic model validity). Advocates for human-in-the-loop approaches to address LLM limitations in tasks like document clustering and sentiment analysis. Grants & Projects: Contributed to a landmark $2.2B DOJ settlement on NYC public housing via econometric modeling at The Brattle Group. Active in graduate labor advocacy (Maryland state legislature testimony) and mentorship (Científico Latino's mentorship program). Labs & Teams: Leads initiatives at the ETH Zürich AI Center, collaborating with groups like Microsoft Research (FATE) and AI2's AllenNLP. Involved in multi-university projects (e.g., University of Maryland's Computational Linguistics lab).