Find Academic Supervisors

Cathy WuView profile

Professor

• Computational Biology
• Bioinformatics
• Data Science
• +8 more

Cathy Wu is a distinguished academic holding the Unidel Edward G. Jefferson Chair in Engineering and Computer Science at the University of Delaware. She serves as Director of the Center for Bioinformatics & Computational Biology (CBCB), Data Science Institute (DSI), and Protein Information Resource (PIR). Her roles include professorships in the Departments of Computer & Information Sciences and Biological Sciences. Education: BS in Plant Pathology (National Taiwan University, 1978), MS and PhD in Plant Pathology (Purdue University, 1982–1984), and a second MS in Computer Science (University of Texas at Tyler, 1989). She completed postdoctoral training in Molecular Biology at Michigan State University (1985–1986). Research interests focus on computational biology, bioinformatics, and data science with emphasis on protein informatics, biological text mining, ontology development, gene-disease-drug networks, and machine learning applications. She leads initiatives in integrating FAIR principles into biological databases like UniProt and InterPro. Her work bridges computational methods with biomedical challenges, including cancer genomics, epigenetic regulation, and proteomic analyses. She has spearheaded educational programs such as the Online Graduate Certificates in Applied Bioinformatics and Biomedical Informatics and Data Science. Her contributions include over 290 peer-reviewed publications (48,000+ citations, h-index 71) and authored/co-authored four books on bioinformatics. She directs multidisciplinary research teams and collaborates internationally on projects like the HALO study on ovarian cancer genetics. Awards and recognition are implied through her leadership roles and academic appointments, though specific prizes are not listed here. Her grants and funding support large-scale initiatives in bioinformatics infrastructure and translational research.

Elsayed IssaView profile

Assistant Professor

• Natural Language Processing
• Second Language Acquisition
• Arabic Linguistics
• +6 more

Elsayed Issa is an Assistant Professor in the School of Languages and Cultures at Purdue University. Specializing in Computational Linguistics and Arabic, his interdisciplinary research bridges Natural Language Processing (NLP) with Second Language Acquisition (SLA), focusing on conversational AI and speech technology for under-resourced languages. Ph.D. in Linguistics from the University of Arizona (2023) Research integrates NLP, conversational AI, and SLA methodologies Develops tools for computer-assisted pronunciation training (CAPT) Focuses on Arabic dialectology and large language models (LLMs) His work employs Transformer architectures and end-to-end machine learning to enhance language learning systems. Recent projects include ArabiBot development and dialect identification models. He specializes in speech-to-text systems , prosody modeling , and emotional speech analysis for Arabic language learning applications.

Janice McGregorView profile

Associate Professor

• Language Learning and Teaching Ideologies
• Intercultural Learning in Study Abroad
• Qualitative Research Methods in Applied Linguistics
• +3 more

Janice McGregor is an Associate Professor of German Studies at the University of Arizona, affiliated with the College of Humanities and the Interdisciplinary PhD program in Second Language Acquisition and Teaching (SLAT). She holds a PhD in German Applied Linguistics from Penn State and previously served as Assistant Professor of German at Kansas State University (2012–2018). Her research focuses on three core areas: ideologies in language learning/teaching, discourses around intercultural learning in study abroad, and reflexive qualitative research methods in applied linguistics. She emphasizes the importance of examining social interactions and authentic language use patterns across communities. Her work critiques traditional methodologies in study abroad research, advocating for more reflexive and decolonized approaches. Notable contributions include analyzing interactions in study abroad contexts, the role of authenticity in language learning, and the ethical dimensions of global mobility programs. Current courses include GER 244 (Real Talk: Why Language Matters) and GER 508 (Approaches to German Studies). Her research methodologies often integrate autoethnography and critical discourse analysis. McGregor’s articles consistently address themes of agency, authenticity, and methodological innovation. Recent work explores ungrading practices and the use of technology in L2 learning. She actively participates in academic discourse through her contributions to conferences like the Tucson Humanities Festival and her involvement in curricular decolonization initiatives.

Dominik SchnausView profile

Academic

• Computer Vision
• Deep Learning
• 3D/4D Reconstruction
• +3 more

Dominik Schnaus is a PhD Student at the Computer Vision Group within the School of Computation, Information and Technology at the Technical University of Munich. His research focuses on computer vision and deep learning, particularly in vision-language correspondence and uncertainty estimation in neural networks. Research Interests: 3D/4D reconstruction, vision-language models, neural network uncertainty, robotics Contact: dominik.schnaus@tum.de

• Applied Linguistics
• Language Testing and Assessment
• Language Assessment Literacy
• +6 more

Professor Luke Harding is a faculty member at the Department of Linguistics and English Language , Lancaster University , within the School of Social Sciences . His work bridges applied linguistics, language assessment, and critical discourse studies, with a focus on the ethical and societal implications of testing. Research Interests : Language testing and assessment, World Englishes and English as a Lingua Franca (ELF), second language listening and pronunciation assessment, diagnostic approaches to language evaluation, and language assessment literacy. Recent projects integrate digital technology and corpus linguistics into testing frameworks. Publications : Published extensively in Language Testing , Applied Linguistics , and Language Assessment Quarterly . Co-edited the Routledge Handbook of Language Testing (Second Edition) (2022), a key reference work in the field. Teaching : Leads modules in Language Test Construction and Evaluation , Issues in Language Testing , and Statistical Analysis for Language Testing within the university's distance MA program. Leadership : Convened the Language Testing Research Group with colleagues Tineke Brunfaut and John Pill, advancing interdisciplinary approaches to assessment.

• Chinese Language Pedagogy
• Chinese Linguistics
• Chinese Cinema
• +5 more

Zhiqiang Yu serves as an Associate Professor in the Department of Modern Languages and Comparative Literature at Baruch College's Weissman School of Arts and Sciences, City University of New York. With over two decades of teaching experience, he has established himself as a dedicated educator specializing in Chinese language, cinema, and civilization courses. Education: Ph.D. in Chinese, University of Washington M.A. in Asian Civilization, University of Iowa B.A. in Chinese Literature, Fudan University (Shanghai) Professor Yu's research focuses on innovative approaches to Chinese language pedagogy, with particular interest in applying economic principles and artificial intelligence to language teaching. His work bridges traditional linguistic scholarship with modern educational technology, examining how efficiency, resource allocation, and technological advancements can enhance language learning outcomes. His research spans Chinese linguistics, dialectology, cinema studies, and cultural elements in language teaching. His publication record reveals a consistent trajectory toward optimizing language instruction through systematic analysis. Recent work increasingly focuses on AI applications in language education and the economic framework of pedagogical efficiency. His scholarship demonstrates a progression from traditional linguistic analysis toward innovative teaching methodologies that incorporate modern technological and theoretical frameworks. Scientific Awards: Award of Excellent Academic Research Reviewer from Journal of International Chinese Education (2016) Graduate Teaching Fellowship from University of Washington (1993) Graduate Teaching Fellowship from University of Iowa (1989) Graduate Research Fellowship from University of Iowa (1988) Student Excellency Award from Fudan University (1984) Professor Yu has served extensively on departmental committees including as Department Assessment Coordinator and Secretary of the Asian and Asian-American Studies Committee. He has organized numerous academic events featuring prominent Chinese cultural figures and has contributed to developing Chinese language curriculum resources including online placement tests. His professional service extends to editorial work for CUNY publications and Chinese language training for the New York Police Academy. He maintains active involvement with multiple professional organizations including the American Name Society, American Oriental Society, American Society of Geolinguistics, Association for Asian Studies, and Chinese Language Teachers Association, frequently presenting at international conferences on Chinese language pedagogy.

Minh Hue NguyenView profile

Senior Lecturer

• Second language teacher education
• TESOL pedagogy
• Language teacher cognition
• +6 more

Minh Hue Nguyen is a Senior Lecturer in EAL/TESOL Teacher Education at Monash University's School of Curriculum, Teaching and Inclusive Education within the Faculty of Education. She holds a PhD in Education (TESOL focused) from Monash University and has taught at Vietnam National University, Deakin University, and the University of Melbourne. Her educational background includes: PhD in Education (TESOL focused), Monash University (2015) MA in Applied Linguistics, Victoria University of Wellington (2008) BA in English Language Teaching, Vietnam National University (2003) Nguyen's research centers on teachers' professional learning, curriculum, and pedagogy in TESOL and EAL contexts, with specific focus on emotional experiences, identity development, mentoring, agency, and collaboration. She explores sociocultural contexts of teacher development through activity theory and sociocultural perspectives, examining how institutions support teachers' learning journeys from preservice to in-service stages. Recent work investigates professional learning for teacher educators and implementation of the Victorian EAL Curriculum. Her 15 most recent publications (2024-2025) reveal a strong thematic focus on language teacher agency, identity negotiation, and multilingual pedagogies. The research increasingly examines emotional dimensions of teaching, cross-cultural identity tensions, and collaborative models between EAL and content teachers, with significant contributions to understanding how teachers navigate complex educational contexts while developing professional identities. Her scientific recognition includes: Penny McKay Award Special Commendation Monash Education Research Community's Publication Award ATEA/Kay Martinez Award for Best Paper Monash Dean of Education’s ECR Project Award Advancing Women's Research Success Grant Vietnamese Government Merit-based Scholarships Nguyen actively supervises PhD research in TESOL teacher professional learning, teacher identity, and curriculum development, though is currently unavailable for new PhD students until 2027. She contributes to editorial boards for Teaching and Teacher Education, Second Language Teacher Education, and System journals, and serves on the Australian Teacher Education Association. Her work supports UN Sustainable Development Goal 4 (Quality Education) through inclusive pedagogical frameworks. She leads research projects including 'Elucidating practices to assist EAL learners to acquire specialised science vocabulary' and 'Establishing an online community-of-practice model for learner agency during work placements,' demonstrating commitment to practical educational innovations.

David PeetersView profile

Associate Professor

• Multimodal Communication
• Multilingualism
• Bilingualism
• +3 more

David Peeters is an Associate Professor at Tilburg University's Department of Communication and Cognition, part of the Tilburg School of Humanities and Digital Sciences. His research focuses on multimodal communication, multilingualism, and digital communication, leveraging immersive virtual reality (VR) technologies combined with EEG, eye-tracking, and fMRI. He explores neurobiological underpinnings of language, including neuropragmatics, non-verbal communication, and multilingualism. His work is supported by grants such as the NWO Veni and Tilburg University Fund. Peeters teaches courses on virtual reality, language psychology, and digital literature integration in education. He is a Research Fellow at the Donders Institute and President of the Tilburg Young Academy. Key research interests include the role of gesture and iconicity in second language acquisition, bilingual language switching in immersive environments, and the impact of dataism on academic publishing. He collaborates with libraries and schools to integrate digital literature into curricula and public collections. His scientific awards include the NWO Veni Grant and a Fellowship from the International Max Planck Research School for Language Sciences. His research bridges cognitive science, linguistics, and technology, emphasizing ecologically valid experimental paradigms.

Mahdi S. HosseiniView profile

Assistant Professor

• Deep Learning
• Computer Vision
• Computational Pathology
• +3 more

Mahdi S. Hosseini is an Assistant Professor in the Department of Computer Science and Software Engineering at Concordia University and a faculty member of the Applied AI Institute. He holds a PhD from the University of Toronto (2016) and completed a postdoctoral fellowship at UofT, supported by MITACS-Elevate and NSERC fellowships. His research focuses on advancing deep learning and computer vision for computational pathology and healthcare technologies, aiming to develop AI tools for clinical diagnosis. He currently supervises graduate students and has published over 30 papers and two patents. Education: PhD in Electrical and Computer Engineering from the University of Toronto (2016), postdoctoral training at UofT collaborating with Huron Digital Pathology Inc. (Waterloo, Ontario). Research interests include deep learning, computer vision, computational pathology, medical imaging, and AI ethics (P4AI project). His work emphasizes developing explainable AI systems for clinical pathology, biomarker discovery, and efficient learning algorithms. Professional service includes serving as Area Chair for NeurIPS 2023, CVPR 2023-2024, and ECCV 2024. He reviews grants for CIHR, NSERC, and serves on program committees for key conferences (ICCV, CVPR, NeurIPS). Teaching includes courses on applied AI, machine learning, and deep learning for computational pathology at both graduate and undergraduate levels. Awards: MITACS-Elevate Fellowship (postdoc), NSERC Research Funding (2016-2017). His work has led to patents in diagnostic systems and has collaborated with hospitals and pathologists to advance clinical applications. Labs/Teams: Active collaborations with the Applied AI Institute at Concordia, Huron Digital Pathology, and healthcare institutions. Research emphasizes interdisciplinary approaches between computer science and clinical medicine.

Ahmed FerhadiView profile

Clinical Professor

• Second Language Acquisition
• Sociolinguistics
• Language Testing
• +3 more

Ahmed Ferhadi is a Clinical Professor of Middle Eastern & Islamic Studies at New York University (NYU), specializing in linguistics with a focus on Second Language Acquisition, Sociolinguistics, and Language Testing. He holds a PhD in Linguistics from the University of Michigan (1990), an MA in Teaching Arabic as a Foreign Language (TAFL) from the same institution, and an M.S. in Applied Linguistics from the University of Edinburgh. His teaching career spans institutions like Princeton University, Columbia University, and Kurdish universities such as Salahuddin and Suleimaniyya Universities. He pioneered video-based language performance evaluation methods during his tenure at Middlebury College in 1991, which became a standard practice. Ferhadi has also served in high-level advisory roles, including President of the Association of American Teachers of Arabic (AATA) since 2017 and Distinguished Global Scholar of Kurdish Studies at American University (2010). Research interests include Kurdish language standardization, advanced Arabic pedagogy, and the sociopolitical dimensions of language. His projects include a Kurdish standardization initiative and curriculum development for advanced Arabic learners. Ferhadi has received numerous accolades, including the Golden Teaching Award (NYU 2000) and Top Language Award (U.S. Department of State 2006). His publications span linguistic theory, pedagogical techniques, and cultural studies, with recent works addressing Arabic dialect dynamics and Kurdish language policy. Ferhadi’s work bridges academic rigor with practical applications, emphasizing technology’s role in modern language education.

M. Tamer ÖzsuView profile

Professor

• Data Science
• Database Systems
• Distributed Data Management
• +3 more

M. Tamer Özsu is a University Professor of Computer Science at the David R. Cheriton School of Computer Science, University of Waterloo, where he holds a Cheriton Faculty Fellowship. He also serves as a Distinguished Visiting Professor at Tsinghua University and is the Founding Director of Waterloo-Huawei Joint Innovation Laboratory since 2018. His extensive contributions to computing have earned him numerous prestigious awards including the 2024 ACM Presidential Award for long-standing and significant contributions to the computing field. Professor Özsu's research focuses on data engineering aspects of data science, particularly addressing data management issues with two main foci: management of non-traditional data and large-scale distributed data management. He is renowned for his seminal book "Principles of Distributed Database Systems" (co-authored with Patrick Valduriez), now in its fourth edition, and the "Encyclopedia of Database Systems" (co-edited with Ling Liu), in its second edition. His work bridges theoretical foundations with practical system implementations, targeting grand societal challenges through computational approaches. His recent publications reveal a strong trend toward graph analytics, streaming data processing, and the integration of large language models with vector data management. The research shows increasing focus on GPU-accelerated graph processing, RDF query optimization, and multimodal data analysis, reflecting the evolution of data management challenges in the era of big data and AI. His work continues to address fundamental challenges in distributed data systems while adapting to emerging technologies and application domains. Scientific Awards and Fellowships ACM Presidential Award (2024) IEEE TCDE Education Award (2024) IEEE Innovation in Societal Infrastructure Award (2022) CS Can | Info Can Lifetime Achievement Award (2018/2019) ACM SIGMOD Test-of-Time Award (2015) ACM SIGMOD Contributions Award (2006) The Ohio State University College of Engineering Distinguished Alumnus Award (2008) Fellow of the Royal Society of Canada Fellow of the American Association for the Advancement of Science (AAAS) Life Fellow of the Association for Computing Machinery (ACM) Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) Elected member of the Science Academy, Türkiye Professor Özsu has been deeply involved in academic leadership and community building. As Founding Editor-in-Chief of ACM Books (2013-2019), he launched a series that by 2019 had published 28 major books with another 30 under contract. His service to ACM, particularly through SIGMOD, has been exemplary and widely recognized. He directs the Waterloo-Huawei Joint Innovation Laboratory, which focuses on cutting-edge research in data management and distributed systems, fostering strong industry-academia collaboration.

Martha Sidury ChristiansenView profile

Professor

• Sociolinguistics
• Digital Literacies
• Language Ideologies
• +6 more

Dr. Martha Sidury Christiansen is a Professor of Applied Linguistics/TESOL at the University of Texas at San Antonio , where she serves in the College of Education and Human Development . She is the Principal Investigator of Project RESPETO , a NSF-funded initiative exploring racial equity in engineering education. Her work spans sociolinguistics, digital literacies, and raciolinguistic analysis, with a focus on transnational multilingual communities. Born in Veracruz, Mexico Ph.D. in Foreign/Second Language Education (Ohio State University, 2013) M.A. in English Composition (Indiana University, 2007) B.A. in English Language Teaching (Universidad Veracruzana, 2002) Her research examines how transnational youth navigate digital spaces through multiliteracies , challenges Western academic writing norms via Mexican decolonial methodologies , and investigates raciolinguistic intersections in identity formation. The 15 most recent publications reveal a strong focus on digital communication , transnationalism , and critical pedagogy across journals like TESOL Quarterly and Language@Internet . 2023-2025: Expanding raciolinguistic frameworks in digital contexts 2021-2022: Analyzing multimodal identity construction 2019-2020: Exploring Mexican bilinguals' online language use She has received multiple honors including ACUE Fellow (2023), Fulbright Scholar (2017), and Faculty Leadership Fellow (2021-2022). Her presentations at conferences like ICOLLITE and DDVM Lab highlight her expertise in critical sociolinguistic awareness and digital discourse analysis . Dr. Christiansen actively consults for nonprofits on linguistic equity and multilingual education .

Andrew LanView profile

Associate Professor

• Artificial Intelligence in Education
• Educational Data Mining
• Personalized Learning
• +5 more

Andrew Lan is an Associate Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst, where he also serves as the CS Undergraduate Program Director. He was granted tenure by the UMass Board of Trustees in June 2025 and is currently on leave through Spring 2026. His research focuses on developing human-in-the-loop machine learning methods to enable scalable, effective, and personalized learning experiences in education. Dr. Lan received his BS in Physics and Mathematics from the Hong Kong University of Science and Technology, followed by his MS (2014) and PhD (2016) in Electrical and Computer Engineering from Rice University. He completed postdoctoral research at Rice University (2016) and Princeton University's EDGE Lab (2017-2018). His research spans artificial intelligence for education, with particular expertise in educational data mining, knowledge tracing, personalized learning systems, and human-AI collaboration in educational contexts. Dr. Lan's work leverages massive and multimodal learner and content data collected from both traditional classrooms and online learning platforms to develop systems that deliver high-quality, affordable, and personalized learning experiences. He has made significant contributions to areas including computerized adaptive testing, math word problem generation, student affect detection, and automated grading systems. His recent work increasingly focuses on leveraging large language models for educational applications while maintaining rigorous scientific validation of these approaches. Best Student Paper Award at the 2024 AIED Conference (with Alexander Scarlatos) Best Paper Nominee at LAK 2021 Best Student Paper Award at IEEE Big Data 2020 NAEP Math Automated Scoring Challenge Grand Prize Winner Dr. Lan actively mentors graduate students and postdoctoral researchers, with several of his advisees receiving recognition for their work. He has secured substantial funding from the National Science Foundation, including a $90M grant for the SafeInsights project, a secure cyberinfrastructure for educational research. His research group collaborates with institutions including Worcester Polytechnic Institute, University of Pennsylvania, and Rice University. He teaches undergraduate and graduate courses including COMPSCI 240 (Reasoning under Uncertainty) and COMPSCI 590OP (Applied Numerical Optimization), with a focus on the practical application of theoretical concepts in machine learning and artificial intelligence. His educational philosophy emphasizes bridging the gap between theoretical foundations and real-world implementation in educational technology.

Verónica Loureiro-RodríguezView profile

Associate Professor

• Sociolinguistics
• Language and Identity
• Language Attitudes
• +5 more

Verónica Loureiro-Rodríguez is an Associate Professor in the Department of Linguistics at the University of Manitoba's Faculty of Arts. Her research focuses on sociolinguistics, language identity, and code-switching, with special attention to global hip hop and multilingual communities. She holds a PhD from the University of California, Davis, an MA from the University of Colorado at Boulder, and a BA from the Universidade de Santiago de Compostela. Dr. Loureiro-Rodríguez's work examines language attitudes across diverse contexts, including French-English dynamics in Manitoba, Spanish-Valencian bilingual processing, and code-switching in music. She has also explored language use in robotics and cultural hybridity among Puerto Rican and Mexican communities. Her teaching excellence was recognized with the 2021 Faculty of Arts Teaching Excellence Award. Education: PhD (UC Davis), MA (CU Boulder), BA (USC) Awards: 2021 Teaching Excellence Award (Established Faculty) Research Focus: Language policy, digital sociolinguistics, and cultural identity She currently supervises graduate students in Master's and PhD programs, focusing on sociolinguistic methodologies like the matched-guise technique. Her research often intersects with music studies, robotics, and diaspora linguistics.

Hong HuaqingView profile

Professor

• Corpus Linguistics
• Computer-Assisted Instruction
• Machine Translation
• +3 more

Hong Huaqing is a Professor and doctoral supervisor at the Corpus Research Institute of Shanghai International Studies University. He holds roles as honorary director of the Chinese Corpus Linguistics Research Association and international expert at Peking University's Education Development Center. Formerly, he worked at Nanyang Technological University (Singapore) in roles such as researcher at the Learning Research and Development Center and director of the e-Learning Center of the Lee Kong Chian School of Medicine. His research spans machine translation, natural language processing, corpus linguistics, and educational technology. He supervises master's and doctoral students, co-supervises postdoctoral researchers, and focuses on smart education driven by big data analysis and innovative learning ecosystems. Research emphasizes corpus-based methods applied to language education, including computational frameworks for student engagement, wearable sensors in learning analytics, and cross-linguistic rhetoric studies. His work bridges technological innovation (e.g., AI-driven tutorial systems) with pedagogical practice, addressing challenges in non-English language education and teacher training.