جست‌وجوی استاد و پژوهشگر

John Bickfordمشاهده پروفایل

مدرس ارشد

• Personality and Social Psychology
• Gay and Lesbian Psychology
• Social Cognition
• +۶ مورد دیگر

John Bickford is a Senior Lecturer II in the Department of Psychological and Brain Sciences at the University of Massachusetts Amherst, within the College of Natural Science. He is actively involved in undergraduate education, teaching foundational and specialized psychology courses, and serves as the Coordinator of Online Instruction, mentoring graduate students in online teaching methodologies. Education: PhD, 2003 – University of Massachusetts Amherst MS, 1999 – University of Massachusetts Amherst BA, 1996 – Salem State College Dr. Bickford's research interests lie primarily in personality and social psychology, with a strong focus on gay and lesbian psychology, social cognition, identity formation, and social stigma. His earlier scholarly work developed a multidimensional model of sexual orientation distinct from sexual identity. However, he is no longer active in research and now dedicates his efforts entirely to teaching and pedagogical innovation, especially in online learning environments. His teaching philosophy is deeply rooted in social justice, self-acceptance, and advocacy for marginalized communities. Although no recent publications are listed, his academic contributions have been primarily educational, reflected in his extensive teaching portfolio and leadership in online instruction. His influence extends through curriculum development and mentorship in digital pedagogy. Scientific Awards and Recognitions: 2021 Winner – UMass College of Natural Science Teaching Award Multiple-time nominee for the UMass Distinguished Teaching Award (2022, 2018, 2017, 2007, 2000) Recipient of the UMass Residential First-Year Experience Student-Choice Award (2014, 2011, 2010, 2009) 2000 Award for Demonstrated Effectiveness in Teaching, Division of Continuing Education Nominee for McKeachie Early Career Teaching Award (2002, 2001) Dr. Bickford advises undergraduate students informally through teaching and mentoring, particularly graduate students teaching online courses. While he does not supervise formal thesis or dissertation research, his role as a mentor in pedagogy is significant. He has contributed to educational grants or programs through the Division of Continuing and Professional Education, though specific grant details are not listed. He is actively involved in shaping the online psychology curriculum and fostering inclusive classroom environments. He is part of the core instructional team in the Department of Psychological and Brain Sciences and plays a key role in the online teaching initiative, supporting both course delivery and instructor development. His work helps expand access to high-quality psychology education beyond the traditional classroom.

Kaiyi Jiمشاهده پروفایل

استادیار

• Large-scale optimization
• Machine learning
• Multi-task learning
• +۶ مورد دیگر

Kaiyi Ji is an Assistant Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY. He earned his PhD in Electrical and Computer Engineering from Ohio State University in 2021 and completed a postdoctoral fellowship at the University of Michigan. His research focuses on large-scale optimization, machine learning, and foundation models. PhD: Electrical and Computer Engineering, Ohio State University (2021) Postdoc: University of Michigan (2022) BSc: University of Science and Technology of China (2016) Research interests include bilevel optimization, multi-task learning, continual learning, and AI4Science, with applications in robotics and crystal property prediction. Recent work explores efficient algorithms for LLM training and optimization. His publications span top venues like ICLR, ICML, NeurIPS, and IEEE Transactions on Information Theory. He received the CSE Junior Faculty Research Award (2023) and NSF CAREER Award (2025). He advises PhD students and actively participates in departmental service as Associate Chair for Graduate Student Admissions and organizer of academic workshops.

Stavros Demetriadisمشاهده پروفایل

استاد

• Learning Technologies
• Educational Technology
• ICT in Education
• +۷ مورد دیگر

Stavros Demetriadis is a Full Professor at the School of Informatics, Aristotle University of Thessaloniki, Greece. His research focuses on Learning Technologies, including Conversational Agents in Education, Learning Analytics, Computer-Supported Collaborative Learning (CSCL), Computational Thinking, and Massive Open Online Courses (MOOCs). He has led EU-funded projects like colMOOC and developed educational tools such as 'pytolearn' for Python instruction and 'Cubes Coding' (winner of Open Education Challenge 2014 and NUMA Competition 2014). He has supervised 5 completed PhD theses, 4 ongoing PhDs, and over 60 Master’s theses. Academic Appointments: Full Professor (2020–present), Associate Professor (2015–2020), Assistant Professor (2012–2015), Lecturer (2002–2008), Informatics Teacher (1989–2002) Education: PhD in Multimedia Technology in Education (2000), MSc in Electronic Physics (1986), BSc in Physics (1983) His work bridges AI and education, with over 161 publications and an h-index of 27. Recent research explores ChatGPT integration, ethics in Learning Analytics, and AI-driven assessment tools. He has delivered invited talks at institutions like the University of Valladolid (2024) and coordinates the 'Teachers' Fast-paced Distance Training on Tele-education' project. Awards include three international best paper awards and recognition for his 'Cubes Coding' project. Key Research Contributions: Developed frameworks for Conversational Agents in CSCL Innovated Computational Thinking pedagogy through robotics Explored ethics and culture in Learning Analytics adoption Created Python-based MOOCs for non-programmers He has taught courses like Human-Computer Interaction and Learning Analytics, and led short programs on Conversational AI. His collaborations span institutions in Spain, Denmark, and Greece. ORCID: 0000-0002-1561-6372; Google Scholar, Semantic Scholar, and Scopus profiles list his extensive output.

• Microfinance
• Informal Savings Groups
• Sustainable Finance
• +۳ مورد دیگر

Bert D'Espallier is a Professor at KU Leuven's Faculty of Economics and Business (FEB), based in the Finance Research Group at the Brussels campus. He serves on the FEB Council and Campus Council FEB Brussels, contributing to institutional governance. His research centers on microfinance and informal savings groups , examining financial/social performance, ethical dilemmas in hybrid organizations, and gender dynamics. Key areas include sustainable finance, donor impacts on social enterprises, and development finance, with emphasis on financial inclusion and poverty alleviation through community-based finance mechanisms. Recent publications (2024-2025) reveal a cohesive research program using advanced methodologies (survival analysis, machine learning, longitudinal studies) to analyze savings groups globally. Dominant themes include autonomy-performance relationships, sustainability determinants, and social potential of informal finance, bridging finance, development economics, and social impact assessment. No scientific awards were documented in the provided sources. D'Espallier supervises 5 PhD students (2 at KU Leuven, 3 at University of Agder) and leads multiple funded projects including 'Contextual performance of informal financial associations' (2020-2025) and 'Sabbatical for informal savings groups research' (SAB/22/036), supported by FWO grants and development industry partnerships. He collaborates with the CERCEM research group at UiA (Norway) and leverages the SAVIX-VSLA database for large-scale analysis of savings groups, actively engaging with development organizations to translate research into policy.

• Software Engineering
• Model-Based Software Engineering
• Automated Reasoning
• +۵ مورد دیگر

Sebastián Uchitel is a Professor at the Department of Computing, Imperial College London, UK. His research focuses on foundational aspects of Software Engineering, particularly in modeling and analysis for automated reasoning, verification of probabilistic systems, controller synthesis, and adaptive systems. He has led major research projects, including the ERC-funded IDEAS StG project on Partial Behaviour Modelling and the European FP6 SENSORIA project. Research Interests: Model-Based Software Engineering, Controller Synthesis, Probabilistic Systems, Adaptive Systems, Requirements Engineering External Roles: General Chair, International Conference on Software Engineering (2017); Associate Editor, Elsevier Science of Computer Programming; Steering Committee, International Conference on Software Engineering His recent work explores intersections between Software Engineering and AI, including assured adaptive systems and logic-based learning. A Senior Member of IEEE and Distinguished Scientist of ACM , he has received awards like the Houssay Prize (2015) and Philip Leverhulme Prize (2005). Collaborators include institutions in Argentina, Canada, and the UK. Selected Publications: 150+ peer-reviewed works spanning controller synthesis, requirements engineering, and formal methods Students: Supervised 12 PhD students since 2003 Grants: Principal Investigator for 3 major grants (2005-2016) totaling over $3.7M USD, including: 2013-2016: Technology Platform in Software Engineering (ANPCYT, $1.6M) 2009-2014: ERC IDEAS StG on Partial Behaviour Modelling (€1.4M) 2005-2008: FP6 SENSORIA Project (€0.7M)

• AI Hardware
• Digital Chip Design
• Efficient AI Algorithms
• +۶ مورد دیگر

Deliang Fan is an Associate Professor at the School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ. His research focuses on AI hardware, in-memory computing, and neuromorphic systems. He received his MS and PhD from Purdue University under Prof. Kaushik Roy. Education: PhD, Purdue University (2015) Research Interests: AI Hardware, In-Memory Computing, Adversarial AI, Neuromorphic Computing His work spans cross-layer co-design for AI applications, including deep learning, bioinformatics, and graph processing. He has authored 170+ peer-reviewed papers and developed hardware solutions for spintronic and memristor-based systems. Recent publications emphasize efficient architectures for transformers, federated learning, and robust neural networks. Awards include the NSF Career Award and multiple best paper recognitions. He serves in editorial and organizational roles for leading conferences like DAC, ISQED, and GLSVLSI.

• Data Science and Data Analytics
• Machine Learning
• Recommender Systems
• +۷ مورد دیگر

Guandong Xu is a Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he has been employed since 2012. He also serves as the Director of the UTS-Providence Smart Future Research Centre, which focuses on disruptive technology for sustainability, and leads the Data Science and Machine Intelligence Lab dedicated to research excellence and industry innovation in data science and artificial intelligence. Dr. Xu holds a PhD in Computer Science from Victoria University, Australia, along with MSc and BSc degrees in Computer Science and Engineering. After holding various research positions at European and Australian universities, he joined UTS in 2012 and was promoted to Associate Professor in January 2017, then to Professor in January 2019. His research spans data mining, machine learning, social computing, recommender systems, text mining, predictive analytics, and user behavior modeling. He has published over 240 papers in these areas with increasing citations from academia. His recent work demonstrates a strong focus on integrating large language models with recommendation systems, causal inference in recommendation, multimodal learning, and fairness in AI systems. His publications reveal sophisticated graph-based approaches and addressing challenges in dynamic recommendation scenarios, particularly through temporal modeling and hypergraph structures. Dr. Xu has received numerous prestigious awards including the Digital Disruptors Winner for ICT Research Project of the Year (2021), eBay's Leaders' Choice Award (2021), and was elected Fellow of Institution of Engineering and Technology (IET), UK (2021) and Fellow of Australian Computer Society (ACS) (2022). He has shown strong academic leadership as founding Editor-in-Chief of Human-centric Intelligent Systems Journal, Assistant Editor-in-Chief of World Wide Web Journal, and founding Steering Committee Chair of the International Conference of Behavioural and Social Computing Conference. He has supervised over 25 high degree research students and secured over $8 million in research funding from ARC, government, and industry sources, including projects like 'Smart Personalized Privacy Preserved Information Sharing in Social Networks' and 'A Secured Smart Sensing and Industry Analytics Facility for Industry 4.0.' Dr. Xu directs the Data Science and Machine Intelligence Lab at UTS, which aligns with UTS research priority areas in data science and artificial intelligence. The lab focuses on research excellence and industry innovation across academia and industry, with particular emphasis on developing advanced techniques for recommendation systems, knowledge graphs, and multimodal learning applications.

• Image Analysis
• Artificial Intelligence
• Deep Learning
• +۵ مورد دیگر

Joakim Lindblad is a Professor at the Department of Information Technology, Uppsala University , and holds affiliated roles as Senior Research Associate at the Mathematical Institute of the Serbian Academy of Sciences and Arts, and Head of Research at Topgolf Sweden AB. With over two decades of expertise in image analysis and machine learning , his work bridges computational methods with biomedical applications. Key affiliations: Uppsala University, Serbian Academy of Sciences, Topgolf Sweden Specializations: Deep Learning, Multimodal Image Registration, Quantitative Microscopy His research focuses on reliable image processing frameworks that integrate intensity and spatial information , particularly for biomedical applications . Recent publications highlight innovations in autofluorescence-based cancer detection , self-supervised one-class learning for sparse instance identification, and rotation-equivariant CNNs for robust analysis of cytology images. Recent article trends demonstrate expertise in multimodal image analysis (2024: 3 papers), oral cancer detection (2025: 2 papers), and multiscale biomedical imaging . His 2025 work on the Uppsala Storytelling Dataset introduces novel frameworks for multimodal dataset creation in AI research. While no scientific awards are explicitly mentioned, his extensive publication record (2000-2025) across top venues like Pattern Recognition , PLOS ONE , and IEEE Transactions indicates significant academic impact. His methodological contributions span stochastic distance transforms , fuzzy set defuzzification , and multimodal image registration techniques. Collaborative work with researchers like Nataša Sladoje and interdisciplinary teams has produced innovations in automated cytology analysis , TEM image enhancement , and AI-driven medical diagnostics . His 2021-2022 projects introduced contrastive learning approaches for multimodal image registration and explainable AI frameworks for infant engagement analysis.

• Educational psychology
• Developmental Disorders
• Anger Management
• +۴ مورد دیگر

Professor Keiko Honda is a distinguished faculty member at Waseda University's Faculty of Education and Integrated Arts and Sciences, School of Education. With a Doctorate in Education from Teachers College, Columbia University, she has established herself as a leading expert in educational psychology, particularly focusing on developmental disorders, anger management, crisis intervention, and school counseling. Her educational background includes: Graduate School, Division of Psychology, Counseling Psychology at Teachers College, Columbia University (1994) Faculty of Liberal Arts, Social Study at International Christian University Professor Honda's research focuses on understanding and addressing the challenges faced by children with developmental disorders, particularly in emotional regulation and social interaction. Her work has led to the development of specialized intervention programs including anger management techniques for children with borderline intelligence and social skills training for children with special needs. She has pioneered approaches that combine clinical psychology with educational practices to create effective support systems in school environments. Her research has identified key developmental stages in children's needs and self-control, resulting in categorized intervention strategies. Her work has been particularly influential in developing practical tools for educators and counselors working with children who have difficulties in social interaction and emotional regulation, including VRICS (Violence Risk Check Sheet) and specialized anger management programs implemented in schools and correctional facilities. Professor Honda is actively involved in professional organizations including: Japan Psychological Association Japan School Psychologist Association Japanese Association of Criminal Psychology Japanese Association of Correction Education Japanese Association of Educational Psychology Japanese Association of Learning Disorder She supervises graduate students across multiple departments including the Graduate School of Education and the Graduate School of Letters, Arts and Sciences, teaching diverse courses related to school psychology, educational psychology, and brain-based learning in inclusive classrooms. Her current research projects focus on developing comprehensive systems for inclusive education and prosocial problem-solving strategies for children with developmental disabilities.

• Artificial Intelligence
• Robotics
• Data Science
• +۴ مورد دیگر

Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).

Atle Ødegårdمشاهده پروفایل

استاد

• Interprofessional Collaboration
• Social Innovation
• Service Design
• +۷ مورد دیگر

Atle Ødegård is a Professor at Molde University College, Faculty of Health Sciences and Social Care. He is actively engaged in research and academic leadership with a strong focus on interprofessional collaboration and social innovation in health and welfare services. Position: Professor Institution: Molde University College Faculty: Faculty of Health Sciences and Social Care Email: atle.odegard@himolde.no Office: B333, Molde His research interests center on interprofessional collaboration, service design, social innovation, and the integration of health and social care services. He explores how professionals from different disciplines can work together effectively, particularly in contexts involving vulnerable populations such as individuals with developmental disabilities, those in the criminal justice system, and elderly care residents. His work also emphasizes co-creation and user participation in public service development. The recent publications of Atle Ødegård reflect a consistent focus on interprofessional education and collaboration across health, social care, and criminal justice. His work spans qualitative studies, systematic reviews, and conceptual frameworks, often contributing to policy and practice. He frequently collaborates with researchers like Anna Elisabeth Willumsen, Bjørn Kjetil Larsen, and Ingrid Krohn Aasgård, and has co-edited key books in his field. Atle Ødegård has not received any explicitly mentioned scientific awards in the provided text. He is involved in advising and research leadership, contributing to training programs and editorial work. He has co-edited multiple books and special issues, and his work often bridges academic research with public policy through opinion pieces and blog contributions. There is no explicit mention of external grants, but his extensive publication record suggests active research funding. He is part of research groups focused on interprofessional collaboration in practice and education and contributes to initiatives such as the Regional Knowledge Center for Rehabilitation (RHAB) and the FOGTPS blog, promoting knowledge development and co-creation in practice settings.

• Sports Science
• Exercise Physiology
• Nutritional Science in Athletics
• +۱۴ مورد دیگر

Dr. Ciarán Ó Catháin is a Lecturer in the Department of Sport and Health Science within the Faculty of Science and Health. He is actively engaged in research at the intersection of sports science, exercise physiology, and nutritional health, with a strong emphasis on athlete performance and well-being. His research interests include: Sports Science and Exercise Physiology Nutritional Science in Athletics Female Athlete Health, particularly menstrual cycle and hormonal contraceptive tracking Dietary intake and culinary nutrition among athletes Resisted sprint training and performance monitoring Systematic reviews and meta-analyses in sports interventions Application of machine learning and wearable technology in sports Dr. Ó Catháin’s recent publications demonstrate a trend toward evidence synthesis (systematic reviews and meta-analyses), interdisciplinary methodologies, and a growing focus on gender-specific considerations in sports performance. His work integrates engineering concepts such as gait analysis and phase velocity with health sciences, reflecting a cross-disciplinary approach. He also explores emerging technologies like augmented reality and synthetic data generation for performance prediction. While no formal scientific awards are listed, his research has contributed to high-impact journals including Sports Medicine , Frontiers in Sports and Active Living , and Nutrition Bulletin . His h-index of 10 and 254 citations reflect a solid and growing academic influence. There is no available information regarding student supervision, grant funding, laboratory affiliations, or collaborative teams. However, his frequent co-authorship suggests active research collaboration, particularly with researchers in sports physiology and nutrition.

• Comparative Psychology
• Animal Cognition
• Developmental Psychology
• +۳ مورد دیگر

Dr. Emma Collier-Baker serves as an Honorary Research Fellow at The University of Queensland's School of Psychology, where her work bridges comparative psychology, animal cognition, and developmental science. Her research program investigates cognitive mechanisms across species, with particular emphasis on experimental comparisons between non-human primates (especially chimpanzees) and human children. Her core research interests include: Comparative analysis of inferential reasoning and metacognition Evolution of social learning and cultural transmission Development of self-recognition and theory of mind Moral cognition and its evolutionary foundations Cross-cultural variations in cognitive processes Experimental methodologies for studying animal cognition Analysis of her publication record reveals consistent focus on experimental paradigms examining exclusion reasoning, invisible displacement understanding, and social learning biases. Her recent work demonstrates significant expansion into cross-cultural moral psychology, evidenced by large-scale international collaborations involving 28 cultural groups. The methodological diversity across her career—from primate cognition studies to cross-national surveys—highlights her interdisciplinary approach to understanding cognitive evolution. No scientific awards were documented in the source material. While her collaborative publications indicate extensive research partnerships, specific details regarding student supervision, grant funding, or laboratory facilities were not provided. Her honorary fellowship status suggests research-focused engagement without primary teaching responsibilities.

Nele Mentensمشاهده پروفایل

استاد

• Applied Cryptography
• Hardware Security
• Secure Coprocessor Design
• +۱۲ مورد دیگر

Nele Mentens is a full professor at both KU Leuven and Leiden University, where she leads cutting-edge research in applied cryptography, hardware security, and secure embedded systems. At KU Leuven, she is affiliated with the Faculty of Engineering Technology and the Electrical Engineering Department (ESAT), leading the Emerging Technologies, Systems & Security (ES&S) research group at the Diepenbeek campus. Simultaneously, she holds a full professorship at Leiden University’s Leiden Institute of Advanced Computer Science (LIACS), focusing on applied cryptography and security. She has been instrumental in numerous national and international research initiatives, including Horizon Europe and NWO-funded projects. Full Professor, KU Leuven (since 2023) Full Professor, Leiden University (since 2020) Associate Professor, KU Leuven (2014–2023) Post-doctoral Researcher & Lecturer, KHLim / KU Leuven (2007–2014) Ph.D. in Engineering Science, KU Leuven (2007) M.Sc. in Electrical Engineering, KU Leuven (2003) Her research focuses on secure and efficient hardware design, particularly for cryptographic applications on FPGAs, reconfigurable architectures, IoT security, and neuromorphic computing. She explores physical attack resistance, side-channel analysis protection, and trusted computing architectures, with applications in healthcare, industrial monitoring, and endpoint AI. Her work bridges theoretical cryptography with practical hardware implementations, emphasizing energy efficiency and real-time performance. The 15 most recent publications reflect a strong trend toward secure, energy-efficient, and intelligent embedded systems. Topics include neuromorphic AI accelerators, trusted IoT architectures, dynamic reconfiguration for side-channel protection, and secure medical data processing. These works span disciplines such as computer architecture, cybersecurity, digital design, and embedded systems, with a focus on hardware-software co-design and real-world deployment. Nele Mentens has received recognition for her contributions, including: Best Paper Award, DATE'16 Best Paper Nomination, AsianHOST'17 Best Paper Award, CHES'19 She has supervised over 15 Ph.D. students and post-docs, both current and former, and has served as principal investigator in approximately 25 funded research projects. Her work has attracted significant grants from Horizon Europe, NWO, FWO, and national innovation programs. She actively contributes to the academic community through editorial roles in top journals and leadership in major conferences. Nele Mentens leads the ES&S research group at KU Leuven and collaborates closely with LIACS at Leiden University. Her team includes Ph.D. students, post-docs, and research experts working on projects like NimbleAI, NeuroSoC, and TrustedIoT. She has also established secure electronics labs through infrastructure grants and maintains strong international ties with institutions such as EPFL, Ruhr University Bochum, and ETH Zurich.

• Sustainable Eco-tourism Development
• Indigenous Infrastructure and Housing
• Participatory Design Methods
• +۷ مورد دیگر

Campbell Drake is a Senior Lecturer in Interior Architecture at the University of Technology Sydney's School of Architecture within the Faculty of Design, Architecture and Building. Registered as an architect in New South Wales and Victoria with over 15 years of professional experience, he specializes in sustainable eco-tourism development in environmentally sensitive locations. His work bridges academic research and practical application through partnerships with government and non-government agencies focused on Indigenous infrastructure and housing. Education: PhD from RMIT University (2012-2018) Masters of Research Architecture from Goldsmiths College, University of London (2009-2010) Bachelor of Architecture from RMIT University (1999-2005) Dr. Drake's research centers on the interaction between urban infrastructure and social formation within remote communities, particularly investigating socio-architectural relations in Indigenous contexts. His work explores how infrastructure can enhance wellbeing, cultural practices, and environmental sustainability. He specializes in participatory design methods that empower communities through culturally responsive approaches that integrate Indigenous knowledge systems. His research spans sustainable tourism development in Indonesia, Indigenous housing policy in Australia, cultural burning practices, and the spatial politics of tourism infrastructure, demonstrating a commitment to decolonizing design practices and creating architecture that serves community needs. His recent publications reveal a clear trajectory toward evaluating specific programs (like the Roads to Home Program and Wreck Bay housing strategy) while simultaneously developing theoretical frameworks for culturally responsive architecture. There's a consistent focus on Indigenous infrastructure, housing, and participatory design methodologies, with increasing attention to the intersection of traditional knowledge systems with contemporary design practices in remote Australian communities. His work bridges practical implementation with critical theoretical analysis of power dynamics in architectural practice. Scientific Awards: 2018 UTS Teaching and Learning Awards: Indigenous Professional Capabilities High Commendation Interior Design/Interior Architecture Educators Association Teaching Award (2018 Third place finalist) 2018 AILA Research, Policy & Communication Landscape Architecture Award International Interior Design Association 2014 Global Excellence Awards Dr. Drake supervises Masters and PhD students with a focus on Indigenous architecture and sustainable design. His funded research includes culturally responsive design principles for Aboriginal housing, evaluations of the Wreck Bay Village housing program, Roads to Home evaluations for Gulargambone & Bowraville Reserves, and solar lighting projects for Namoi and Gingie Reserves. His grants come from diverse sources including the NSW Aboriginal Land Council, National Indigenous Australians Agency, and Department of Planning Industry and Environment, reflecting the practical impact of his work. As a founding member of UTS TIISHA (The Indigenous Infrastructure and Sustainable Housing Alliance), Dr. Drake leads collaborative research projects focused on 'health enabling infrastructure' to address structural factors of Indigenous disadvantage. TIISHA works with multiple Aboriginal Land Councils and government agencies to evaluate and implement housing and infrastructure programs that respect cultural values and community needs, demonstrating his commitment to creating tangible benefits for Indigenous communities through architectural practice.