Find Academic Supervisors

Qiuming YaoView profile

Assistant Professor

• Bioinformatics
• Computational Biology
• Omics Data Integration
• +5 more

Qiuming Yao is an Assistant Professor in the Department of Computer Science at the School of Computing, University of Nebraska-Lincoln since 2020. His research develops computational methods for integrating multi-omics data to decode complex biological systems at the interface of computer science, biology, and medicine. PhD in Computer Science, University of Missouri, 2014 MA in Statistics, University of Missouri, 2014 Dr. Yao's work pioneers scalable algorithms for genomics, transcriptomics, proteomics and metabolomics integration. His lab investigates microbiome ecology (environmental/health impacts), genetic mutation functionality (gene therapy applications), molecular isoform quantification (medical/plant contexts), and interpretable machine learning. He bridges frequentist and Bayesian statistical frameworks to model biological uncertainty while developing tools for causal inference in high-dimensional omics data. His publication record (2012-2021) reveals consistent innovation in bioinformatics tool development, with flagship projects including Motif Raptor for transcription factor analysis, Storm/Omega2 for metagenomic pipelines, and P3DB/Musite for phosphorylation databases. These tools, published in Nature Genetics, Nature Communications, and Bioinformatics, demonstrate cross-domain applicability from human genetics to plant proteomics through rigorous algorithmic design. No scientific awards were documented in the source material. Dr. Yao actively mentors postdocs (offering salaries exceeding NIH standards), graduate RAs (with tuition waivers), undergraduates, and visiting scholars through his Integrated Digital Omics Lab. His lab culture emphasizes interdisciplinary collaboration, self-directed learning, and translating computational research into publishable outcomes for academic or industry careers. The Integrated Digital Omics Lab (IDOL) cultivates a collaborative environment where computer scientists, biologists, and statisticians develop omics integration frameworks. The lab welcomes researchers passionate about algorithm development for biological discovery, with current focus on microbiome modeling, mutation impact prediction, and interpretable machine learning for molecular systems.

• Construction Grammar
• Valency Theory
• Lexicography
• +7 more

Thomas Herbst serves as a Professor in the Department of English and American Studies within the Faculty of Humanities, Social Sciences, and Theology at Friedrich Alexander University Erlangen-Nuremberg (FAU). With a distinguished career spanning over four decades, his research has significantly contributed to linguistic theory and practice. His current work focuses on advancing construction grammar frameworks and their practical applications in language learning and lexicography. Professor Herbst's research interests center on Construction Grammar, Valency Theory, and Lexicography, with particular emphasis on the intersection between lexical and syntactic patterns. His scholarly work explores how constructions—recurring patterns of language—shape meaning, communication, and language acquisition. He has pioneered approaches to constructing constructicons (comprehensive inventories of constructions) and has made significant contributions to understanding how valency patterns function in English and other languages. His research bridges theoretical linguistics with practical applications in language teaching, dictionary compilation, and translation studies, particularly examining how multimodal elements like gesture and accent contribute to meaning in audiovisual contexts. Analysis of his recent publications reveals a consistent trajectory exploring constructional networks, argument structure, and the practical implementation of construction grammar in language learning. His work increasingly focuses on digital applications of linguistic theory, including constructicon development and computational implementations. Herbst's research demonstrates a strong commitment to making linguistic theory accessible and applicable to language learners, teachers, and lexicographers, with particular attention to how constructions manifest in second language acquisition and dictionary usage. Throughout his extensive career, Professor Herbst has maintained an active role in academic service, editing journals and special issues that have shaped discourse in construction grammar and lexicography. His editorial work for publications like Zeitschrift für Anglistik und Amerikanistik and contributions to major reference works have provided essential platforms for scholarly exchange in his fields of expertise.

Janet CarlsonView profile

Associate Professor

• Science Education
• Curriculum Development
• Teacher Professional Development
• +4 more

Janet Carlson is an Associate Professor (Research) of Education at Stanford University's Graduate School of Education, with her office located in Room 530 of the CERAS building. Her research focuses on science education, teacher professional development, and curriculum materials design. Dr. Carlson earned her BA in Environmental Biology from Carleton College, an MS in Curriculum and Instruction from Kansas State University, and a PhD in Instruction and Curriculum (science education) from the University of Colorado. With over 20 years of experience beginning as a middle and high school science teacher, she brings extensive practical knowledge to her academic work. Her research examines how educative curriculum materials and transformative professional development impact science teaching and learning, with recent expansion into mathematics education and equity issues. She investigates teacher noticing, pedagogical content knowledge, and responsive teaching practices through innovative methods like video annotation and teaching rehearsals. Dr. Carlson's publication record (2017-2023) reveals consistent contributions to science and mathematics teacher education, particularly in refining pedagogical content knowledge models and developing video-based professional development approaches. Her work demonstrates strong collaboration with researchers like Hilda Borko and spans practical applications in K-12 classrooms. No scientific awards are mentioned in the provided text. While no specific advisees are listed, Dr. Carlson leads multiple research projects that likely involve mentoring graduate students. Her grant-funded initiatives include the AP Success Project, Letovo School collaboration, Middle School Science Coaching, PLATO protocol development, and the TELOS project focused on equity in learning opportunities. She actively collaborates with Stanford's Center to Support Excellence in Teaching (CSET) and maintains research partnerships across institutions, contributing to national efforts in improving STEM teacher preparation and classroom practices through evidence-based approaches.

Selcen Erten JohanssonView profile

Researcher

• Corpus Linguistics
• Media Discourse Analysis
• Turkish Web Registers
• +3 more

Selcen Erten Johansson is a Doctoral Researcher in Digital Language Studies at the University of Turku, focusing on corpus linguistics and media discourse analysis. Her research examines Turkish web registers in the context of political events, such as Finland's NATO membership process in Turkish media. Supported by the Eino Jutikkala Fund (2024–2026), her work bridges computational methods with sociolinguistic inquiry. She holds a Master's in Linguistics from Mersin University (2019) and has been a Fulbright scholar in the U.S. Her teaching spans corpus linguistics, language technology, and Turkish as a foreign language at institutions including Turun Suomenkielinen Työväenopisto and Toros University. Education: PhD Candidate in Digital Linguistics, University of Turku (2021–present) Master's in Linguistics, Mersin University, Türkiye (2019) Fulbright Scholarship, Michigan State University (2015–2016) Research Interests: Selcen explores language variation in digital contexts, particularly Turkish web-based discourse. She combines corpus linguistics with computational tools to analyze political media narratives and multilingual web registers. Her work emphasizes the intersection of technology and sociolinguistics, including projects like TurCORE and collaborations with the TurkuNLP research team. She also investigates pedagogical approaches for teaching Turkish and Finnish as foreign languages. Grants & Support: Eino Jutikkala Fund Grant (2024–2026), Finnish Academy of Science and Letters Teaching & Outreach: She has taught courses on corpus linguistics, automatic text processing, and Turkish language instruction across multiple institutions. Her teaching philosophy integrates digital tools with traditional language pedagogy. Labs & Teams: Active member of the TurkuNLP research team, focusing on NLP applications in digital humanities and multilingual corpora analysis.

Sanka RasnayakaView profile

Lecturer

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +6 more

Sanka Rasnayaka is a Lecturer at the School of Computing, National University of Singapore , where he has worked since 2022. He previously served as a full-time Teaching Assistant and PhD candidate at the same institution. PhD in Computer Science (2021), National University of Singapore B.Sc. Engineering (Honours) in Computer Science and Engineering (2016), University of Moratuwa, Sri Lanka Research interests focus on Artificial Intelligence and Computer Vision , specifically in biometrics, privacy, and human perception. Current projects explore: Biometrics & Continuous Authentication (gait, keystroke dynamics) Large Language Models for Software Engineering Physics-Informed Generative AI for flood modeling Recent publications demonstrate expertise in: Biometric authentication systems Privacy-preserving AI Transformer architectures for behavioral analysis Generative AI in environmental modeling Teaching includes foundational courses like CS1101S Programming Methodology (co-teaching since 2022) and CS2040 Data Structures and Algorithms (AY2410). He also developed workshops on Generative AI, LLMs, and Computer Vision. Projects supervised: CRISP Platform for classroom management Live Annotation Tool for educators AI Pal for customized LLM assistants Scientific awards include multiple Teaching Excellence Awards (2024-2025) and scholarships from NUS (2017-2021).

• Genomics
• Transcriptomics
• Network Biology
• +7 more

Pasquale Luca Curci is a Researcher at the Institute of Biosciences and BioResources (IBBR), part of the National Research Council of Italy (CNR) in Bari. His work focuses on integrating large-scale genomic and transcriptomic datasets to uncover biological mechanisms in plants, particularly in crops like durum wheat and artichoke. His research interests span genomics, transcriptomics, and network biology, with a strong emphasis on nitrogen use efficiency, gene regulatory networks, and plant stress responses. He employs systems biology approaches to identify key genes and regulatory elements involved in plant development and adaptation. The analysis of his recent publications reveals a consistent focus on plant genomics, particularly in durum wheat and Cynara species. His work integrates omics data to understand gene function, stress responses, and evolutionary relationships. Key themes include nitrogen metabolism, microRNA regulation, chloroplast genomics, and cross-species network analysis. He has led and coordinated multiple national and international research collaborations with institutions in Belgium, Sweden, Spain, France, and Italy, focusing on gene function discovery, nitrogen efficiency, and germplasm characterization. Integrative network analysis for gene function discovery in wheat (with BASF Agricultural Solutions, Belgium) Cross-species network biology in plants (with SweTree Technologies, Sweden) Transcriptomics and regulatory networks in durum wheat (with Sequentia Biotech SL, Spain) Phenotypization and genomic analysis of durum wheat (with Alma Mater Studiorum, Bologna) Asparagine synthetase genes in durum wheat (with INRA-CNRGV, France) He has contributed to the development of genomic resources for Cynara and has published extensively on chloroplast genomics, transcriptomics under nitrogen stress, and genetic diversity in vegetable crops. His work supports crop improvement and sustainable agriculture through advanced molecular tools.

Sarah HuView profile

Assistant Professor

• Microbial Ecology
• Biological Oceanography
• Marine Microbial Food Webs
• +3 more

Sarah Hu is an Assistant Professor in the Department of Oceanography at Texas A&M University. Her research focuses on microbial ecology, biological oceanography, and data science, particularly exploring the ecological roles of protists in marine environments. She leads the Hu Lab, which examines protistan communities in deep-sea hydrothermal vents, coastal ecosystems, and transitional ocean zones. Her work integrates molecular approaches, computational biology, and microscopy to understand protist-driven biogeochemical processes. Dr. Hu holds a B.S. in Aquatic & Fishery Sciences from the University of Washington (2011), a Ph.D. in Marine Environmental Biology from the University of Southern California (2018), and completed a postdoctoral fellowship in Marine Chemistry & Geochemistry at Woods Hole Oceanographic Institution (2018–2022). Her awards include the Center for Dark Energy Biosphere Investigations Postdoctoral Fellowship (2018–2020) and the Katrina J. Edwards Memorial Dissertation Award (2018). Her research investigates protistan trophic strategies (phototrophy, heterotrophy, mixotrophy), their roles in marine food webs, and their responses to environmental changes. Key projects include studying protist diversity at hydrothermal vents, analyzing protistan community dynamics in the North Pacific Subtropical Gyre, and developing bioinformatic tools like EUKulele for taxonomic annotation. Her lab’s research spans meta’omics, field experiments, and computational modeling, addressing questions about protist distribution, activity, and ecological impacts. Collaborative efforts focus on microbial interactions in extreme environments and improving methodologies for studying microbial eukaryotes.

• Computer Vision
• Robotics
• 3D Reconstruction
• +5 more

Thomas Läbe is a Researcher in the Department of Photogrammetry at the University of Bonn's Institute of Geodesy and Geoinformation. His roles include technical associate and software developer, with a focus on advancing robotics, computer vision, and agricultural automation. He holds a diploma in computer science (Dipl.-Inform. (FH)) from Cologne University of Applied Sciences (1994). His research spans image processing, bundle adjustment, visual odometry, and camera calibration, with notable contributions to SLAM (Simultaneous Localization and Mapping) for autonomous systems. Education: 1994: Dipl.-Inform. (FH) in Computer Science, Cologne University of Applied Sciences Research Interests: Focuses on integrating vision-based technologies into robotics for precision agriculture, 3D reconstruction, and robust localization in dynamic environments. His work addresses challenges in sensor calibration, panoptic segmentation, and semantic mapping for autonomous systems operating in agricultural and urban settings. Publications Trends: Recent work emphasizes agricultural robotics, including fruit completion, plant phenotyping, and robust localization under changing conditions. Key themes include LiDAR-based localization, semantic occupancy prediction, and end-to-end learning for 3D representations. Awards: 2001 Hansa Luftbild Price (Best PFG paper award, shared) Technical Contributions: Developed software frameworks for bundle adjustment, multi-camera systems, and obstacle detection. Collaborated on projects like the Phenoliner field phenotyping platform and UAV-based environmental monitoring systems. Labs/Teams: Active in the Photogrammetry professorship group, contributing to the PRBonn (Perception, Robotics & Bonn) robotics initiatives, with open-source tools like OverlapNet and PAg-NeRF for 3D perception.

Mariano RicoView profile

Associate Professor

• Linked Open Data
• Natural Language Processing
• Semantic Web Technologies
• +3 more

Mariano Rico is an Associate Professor at the Polytechnic University of Madrid (UPM), affiliated with the OEG research group in the Artificial Intelligence Department. Previously, he served as a Senior Researcher at OEG (2016-2020) and held teaching roles at the Autonomous University of Madrid (UAM). His primary affiliations include the UPM's Faculty of Computer Science and the UAM's Computer Engineering Department. Education: PhD in Computer Science (UAM, 2009), MSc in Physics (UAM, 1992), and postgraduate studies in Telecommunications Engineering. He conducted research stays at DERI (Ireland) and Freie Universität Berlin, focusing on Semantic Web and Linked Data. Research interests center on Linked Open Data, Natural Language Processing (NLP), and Semantic Web technologies, with contributions to DBpedia's Spanish branch and projects like Wf4Ever and LIDER. He actively collaborates with institutions in Leipzig, Bielefeld, and Berlin on Linked Data and linguistic applications. Teaching: Coordinates courses in NLP, Linguistic Engineering, and Big Data Visualization at UPM and online programs. Has instructed over 300 UAM faculty through teacher training programs on LaTeX, bibliographic management, and digital scholarly practices. Projects: Lead roles in European and national initiatives including SlideWiki, UpGrid, and Neptune. Current work focuses on NLP applications like text summarization (esT5s) and terminology tools (TermInteract). Labs/Teams: Core member of the OEG group, contributing to semantic web infrastructure and NLP tool development. Maintains international collaborations through AKSW and CITEC groups.

Debora NozzaView profile

Assistant Professor

• Natural Language Processing
• Hate Speech Detection
• Ethics in NLP
• +4 more

Debora Nozza is an Assistant Professor in Computing Sciences at Bocconi University , where she leads research on ethics in Natural Language Processing with a focus on hate speech detection and algorithmic bias in multilingual contexts. She was awarded a €1.5 million ERC Starting Grant (2023) for her project PERSONAE , exploring personalized and subjective approaches to NLP. Previously, she secured a €120,000 Fondazione Cariplo Grant (2019) for the MONICA project analyzing Italian responses to the pandemic. Education: PhD in Computer Science (2018), University of Milano Bicocca Her research spans hate speech detection , gender bias in language models , and computational social science . She organizes key workshops like the Workshop on Online Abuse and Harms (WOAH) and Gender Bias in NLP (GeBNLP) at ACL conferences, and co-led shared tasks including HODI (Homotransphobia Detection in Italian) and HatEval (hate speech against immigrants). Recent publications address actionable bias metrics , gender pronoun handling in translation , and large-scale stereotype amplification via text-to-image generation . Her work combines model interpretability , cross-lingual frameworks , and social impact analysis to tackle systemic biases. Scientific Awards: ERC Starting Grant (2023) Fondazione Cariplo Grant (2019) She actively participates in international conferences, including keynotes at ECCV 2024 and WASSA 2024 , and collaborates with groups like MilaNLP and ACL workshops .

Szymon PłotkaView profile

Researcher

• Medical Imaging
• Deep Learning
• Computer Vision
• +3 more

Szymon Płotka is a Researcher in the Medical Imaging and Robotics department at the University of Amsterdam's Informatics Institute. His work focuses on advancing prenatal care through deep learning, particularly in fetal ultrasound analysis and AI-driven medical solutions. He holds a PhD in Computer Science from the University of Amsterdam (2024), with a thesis on enhancing prenatal care via machine learning. Research Interests : Integration of deep learning techniques for medical image analysis Development of AI tools for diagnostic accuracy and clinical workflow optimization Multimodal data fusion in healthcare Real-time surgical imaging applications Recent work emphasizes fetal biometry measurements, endoscopic synthetic datasets, and real-time placental vessel segmentation. His research bridges cutting-edge AI with clinical practice, aiming to improve accessibility and efficiency in medical imaging. Key Contributions : Advances in fetal ultrasound video analysis matching human expert accuracy Pioneering synthetic endoscopic dataset generation with diffusion models Development of BabyNet++ for birth weight prediction No formal students listed, but his projects likely involve collaborations with academic teams. Active in organizing and participating in medical imaging challenges (e.g., FeTA, FetReg).

• Old Polish Literature
• Legal History in Literature
• Forensic Linguistics
• +3 more

Dr hab. Anna Kochan, prof. UWr, serves as Deputy Director for Scientific Affairs at the University of Wrocław's Faculty of Philology. Specializing in Old Polish literature, legal history, and forensic linguistics, she holds a prominent academic rank. Her research focuses on analyzing historical texts, legal narratives, and cultural practices in early modern Poland, with a particular emphasis on authors like Mikołaj Rej and Andrzej Zbylitowski. Kochan has edited and published numerous critical editions of early texts, contributing significantly to philological scholarship. Her work bridges traditional philology with modern interdisciplinary approaches, emphasizing the intersection of law, culture, and literature in historical contexts. Key research areas include the analysis of genre hybridity in early legal texts, forensic linguistics in judicial contexts, and the reinterpretation of marginalia in historical manuscripts. She has authored over 50 publications, including monographs, edited volumes, and articles in peer-reviewed journals like Pamiętnik Literacki and Studia Filmoznawcze . Her recent work addresses themes such as the cultural legacy of Rej’s writings, the role of myth in early modern poetry, and the recovery of lost literary works.

• Computer Vision
• Artificial Intelligence
• Multimodal Learning
• +4 more

Ke Yan is an Associate Professor in the Department of Computer Science at the National University of Singapore's College of Design and Engineering. With extensive research output from 2021-2026, their work spans computer vision, artificial intelligence, and multimodal learning systems. National University of Singapore (Primary Affiliation) Collaborations with University of Electronic Science and Technology of China Research ties with Tencent Youtu Lab in Shanghai Research focuses on advancing computer vision techniques, particularly in medical image analysis, vision-language integration, and fault diagnosis systems. Their work bridges theoretical AI development with practical applications in healthcare, industrial systems, and environmental monitoring. Notable contributions include novel approaches to multimodal learning, medical image segmentation with sparse annotations, and improving reliability of large vision-language models. Recent publication trends (2024-2026) demonstrate increasing focus on multimodal systems, with significant contributions to vision-language model reliability, medical AI applications, and efficient transfer learning techniques. Their work frequently addresses critical challenges like hallucination mitigation in large models and sparse data scenarios in medical imaging. As an advisor, they mentor multiple researchers including Junlong Du, Shouhong Ding, and Zhiwen Lin, with whom they frequently collaborate on cutting-edge computer vision projects. Their research group maintains strong industry connections, particularly with Tencent's AI research division. The research is conducted within NUS's computer vision and AI research ecosystem, collaborating with multiple laboratories focused on multimodal intelligence and practical AI deployment in real-world systems.

Bruna Goveia da RochaView profile

Assistant Professor

• Textile Innovation
• Digital Craftsmanship
• Research-Through-Making
• +3 more

Bruna Goveia da Rocha is an Assistant Professor at the Department of Industrial Design, Eindhoven University of Technology. Her research focuses on advancing research-through-making practices, particularly through textile innovation and material experimentation from a more-than-human perspective. She explores how samples and sample-making can drive creative and technological breakthroughs in digital craftsmanship. Education: PhD in Industrial Design, TU/e (2023), thesis: 'Becoming Travelers: Reflecting on the Emerging Practices of Sample Making in Digital Craftsmanship' MSc in Industrial Design, TU/e (2015), thesis: 'Flow: In the path towards embodied guidance' BSc in Product Design, Universidade Positivo (2012) Research interests include: Material agency and serendipity in design Documentation strategies for digital craftsmanship Embodied interaction through textiles and smart materials Sample archives as dynamic knowledge repositories Her recent work investigates how 'diffractive re-interpretations' of material samples can uncover hidden potentials, as seen in projects like 'Making in the Dark' (2024). She also explores negotiations between designers and fabrication machines, such as in 'Entering the 3D printer' (2024). Lab affiliations include the 'Making With…' group at TU/e, focused on collaborative material exploration. Her work bridges traditional craftsmanship with digital fabrication techniques, emphasizing iterative and embodied design processes.

Mark WissinkView profile

Professor

• Private Law
• Law of Obligations
• Contract Law
• +3 more

Prof. Mark Wissink is a Professor of Private Law, specializing in Law of Obligations, at the University of Groningen's Faculty of Law. He concurrently serves as the Attorney General of the Supreme Court of the Netherlands. Wissink holds degrees from Leiden University (LL.B., 1985) and Columbia University School of Law (LL.M., 1986), with a doctorate from Leiden University (cum laude, 2001). He has held roles including Academic Director of the International and Comparative Private Law master's program, Department Chair, and NWO board member. His research focuses on contract law, consumer protection, real estate transactions, and European legal harmonization. He has authored influential publications like Huurrechtmemo and serves on editorial boards for legal journals such as Tijdschrift voor Privaatrecht . Awards include the Gouden Peer contractenrecht. Wissink actively participates in legal education, supervising over 11 doctoral candidates and teaching courses on EU private law. Education: Leiden University (LL.B., 1985), Columbia University (LL.M., 1986), Leiden University (PhD, 2001) Research interests emphasize practical applications of private law, particularly unfair contract terms, voidability, and consumer rights. His work bridges Dutch legal practice with EU directives, contributing to judicial harmonization in commercial and housing law. Recent publications analyze lease agreements, statutory limitations, and cross-border consumer disputes. He maintains strong ties to legal practice through advisory roles in courts and professional organizations. Awards: Gouden Peer contractenrecht (2025) Teaching and supervision include leading master’s programs and mentoring students in contract law and comparative private law. He has organized major legal conferences, including the Gronings Huurrechtcongres and EU financial services conferences. Editorial leadership extends to journals like WR, tijdschrift voor huurrecht and Vermogensrechtelijke Analyses .