Encoder-Decoder Models Professors and Supervisors

Richard J. MorrisView profile

Professor

Max Planck Institute of Molecular Plant PhysiologyGermany

Richard J. Morris is Professor in Applied Mathematics and Group Leader in the Department of Computational and Systems Biology at the John Innes Centre, where he also serves as Institute Strategic Programme Leader and Associate Research Director since 2013. Previously, he led the department from 2010-2013 following postdoctoral roles at MRC-LMB, Global Phasing, and EMBL-EBI. His educational background includes: BSc and MSc in Theoretical Physics from Technical University of Graz, Austria PhD in Computational Biology from European Molecular Biology Laboratory (EMBL) Morris specializes in plant communication mechanisms, using computational and quantitative approaches to decode how environmental signals are encoded and transmitted via long-distance RNA transport. His research reduces complex biological processes to physical principles, focusing on mRNA mobility and RNA-protein interaction networks that govern plant signaling across cellular boundaries. Recent publications, including the 2022 Annual Review of Plant Biology article on RNA transport, demonstrate the group's expertise in multi-scale modeling that bridges molecular interactions and whole-plant responses. This work reveals fundamental principles of how plants interpret environmental changes through biophysical signal transmission. No specific scientific awards are mentioned in the provided text. The PLAMORF group advises PhD students like Franziska Hoerbst and includes postdoctoral researchers such as Melissa Tomkins (specializing in multi-scale modeling) and senior scientists like Pirita Paajanen (bioinformatics analysis). Research is supported by John Innes Centre strategic funding, with evidence of international collaborations through field studies in the US and Poland. The PLAMORF laboratory develops computational frameworks to simulate plant signaling systems, currently investigating mRNA biophysical properties and RNA-binding protein networks. Projects emphasize predictive modeling of environmental response mechanisms, providing training in quantitative biology for students and collaborators.

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Hüseyin ÜzenView profile

Associate Professor

Bingol UniversityTurkey

Assoc. Prof. Dr. Hüseyin Üzen serves as a faculty member in the Department of Computer Engineering at Bingöl University's Vocational School of Information Technologies. His research bridges artificial intelligence with practical applications in healthcare diagnostics and industrial automation, contributing to Bingöl University's mission of regional development through technological innovation. Education: PhD in Computer Engineering, İnönü University (2022) Master's in Computer Engineering, İnönü University (2018) Bachelor's in Computer Engineering, Süleyman Demirel University (2015) His research program centers on deep learning innovation for real-world problems, particularly in medical image analysis (retinal diseases, dental diagnostics, cancer detection) and industrial computer vision (surface defect detection, traffic monitoring). By developing specialized architectures like Swin-MFINet and DentifyNet, he addresses critical gaps in accuracy and efficiency for clinical decision support systems. Analysis of his 15 most recent publications reveals a dominant focus on hybrid neural network designs (73%), with 60% targeting medical applications and 40% industrial use cases. Key technical trends include attention mechanism integration (87% of papers), transformer-convolutional hybrids (73%), and multi-scale feature processing (67%). Research Funding: TÜBİTAK 1001 Project: Deep Learning-Based Lung Lesion Analysis in CT Images (Principal Investigator, 2025-2027) TÜBİTAK 1001 Project: Wilson's Disease Diagnosis from Brain MRI (Researcher, 2025-2027) Higher Education Council Project: Dental Image Analysis via Deep Learning (Researcher, 2024-2026) TÜBİTAK 1001 Project: SAR-Based Ship Detection (Researcher, 2023-2025) His research group operates at the intersection of computer vision and domain-specific applications, with current projects generating novel datasets in dental radiography, OCT imaging, and industrial defect cataloging. Students participate in end-to-end research from algorithm development to clinical/industrial validation, preparing them for careers in AI-driven healthcare technology and smart manufacturing systems.

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ONUR POLATView profile

Lecturer

Bingol UniversityTurkey

Dr. Onur Polat serves as a Lecturer at Bingol University's Faculty of Engineering and Architecture, specializing in cybersecurity research with focus on Distributed Denial of Service (DDoS) attack detection in Software Defined Networking (SDN) environments. His work extends to critical applications in Vehicular Ad Hoc Networks (VANET) and SCADA systems. Research interests include: Network Security and Cybersecurity Software Defined Networking (SDN) Machine Learning for Intrusion Detection Vehicular Networks Security Industrial Control System Protection AI-driven Real-time Monitoring Analysis of his 9 journal publications (2020-2024) reveals consistent innovation in AI-powered security frameworks, with recent work emphasizing hybrid models combining convolutional networks, decision trees, and ensemble methods for VANET and SCADA environments. His research demonstrates increasing sophistication in handling 'pandemic-scale' attacks and real-time traffic monitoring. Dr. Polat maintains active research collaboration with co-authors including H. Polat and M. Türkoğlu, presenting at IEEE conferences since 2016. Prospective students should note his focus on practical security solutions for emerging network infrastructures, with opportunities to contribute to impactful cybersecurity research in transportation and industrial systems.

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Juri BelikovView profile

Associate Professor

Tallinn University of TechnologyEstonia

Juri Belikov is a Tenured Associate Professor at Tallinn University of Technology's School of Information Technologies, Department of Software Science, where he has served since 2019 (initially as an Assistant Professor until 2023). Since February 2022, he has also led the Nonlinear Control Systems group. His academic journey began with a B.Sc. in Mathematics (cum laude) from Tallinn University (2003-2006), followed by M.Sc. and Ph.D. degrees in Computer and Systems Engineering and Information and Communication Technology from Tallinn University of Technology. After completing his doctoral research on polynomial methods for nonlinear control systems in 2012, he conducted post-doctoral research at Technion—Israel Institute of Technology (2015-2017). Professor Belikov's research spans power systems, control engineering, and energy data science, with particular expertise in nonlinear control systems for energy applications. His work addresses critical challenges in renewable energy integration, energy storage management, building energy efficiency, and applications of machine learning in power systems. His approach combines theoretical control methods with practical energy system applications, resulting in publications that bridge engineering theory and real-world implementation. His recent publications demonstrate a clear trend toward integrating advanced data science techniques with traditional power system engineering, particularly in the areas of explainable AI for energy forecasting, stability analysis of renewable-rich power systems, and optimization of building energy management. This interdisciplinary approach has positioned him at the intersection of computer science, control theory, and energy systems engineering. Best paper award from International Conference on Power, Control, and Computing Technologies (2024) Tallinn University of Technology, Young scientist of the 2020 year (awarded 2021) Best-of-the-best conference paper award from IEEE PES General Meeting (2020) Estonian Cultural Foundation of the President, Young IT-scientist award (2019) As an educator, Professor Belikov teaches 'Energy Data Science' (ITS8080), equipping students with IT knowledge and skills for energy sector solutions using data science tools. His administrative roles include membership on the evaluation committee of the Estonian Research Council (ETAG) since 2023, Senior Member of IEEE since 2019, and full membership in Sigma Xi since 2024. His leadership of the Nonlinear Control Systems group demonstrates his commitment to advancing research in control methodologies for modern energy systems, particularly as they integrate increasing amounts of renewable generation and digital technologies.

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Shawn BurtonView profile

Assistant Professor

Lehigh UniversityUnited States

Shawn Burton serves as a Research Assistant Professor at Lehigh University, maintaining an active research laboratory in room B328 of Iacocca Hall. His work centers on neural computation within the mammalian olfactory system, leveraging the olfactory bulb as a model for understanding fundamental brain circuitry. Dr. Burton's research program investigates two critical neural mechanisms: How synaptic motifs like recurrent and lateral inhibition enable behavioral discrimination of complex odorants How parallel circuit architectures simultaneously encode complementary olfactory information streams His experimental approach integrates acute slice electrophysiology, functional imaging, genetic targeting, molecular perturbations, and behavioral assays with computational simulations to decode sensory processing principles. This multidisciplinary methodology bridges molecular, cellular, and systems-level neuroscience to reveal universal neural coding mechanisms beyond olfaction.

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Antonio GiraldezView profile

Professor

Max Planck Institute of Molecular Cell Biology and GeneticsGermany

Antonio Giraldez is the Fergus F. Wallace Professor of Genetics at Yale School of Medicine, where he has led his research laboratory since 2007. He served as Director of Graduate Studies (2012-2016) and Chair of the Genetics Department (2017-2023). His academic appointments span multiple departments and centers including Biochemistry, Quantitative Biology, Biophysics and Structural Biology (BQBS), the Center for RNA Science and Medicine, Yale Cancer Center, Yale Center for Genomic Health, Yale Combined Program in the Biological and Biomedical Sciences (BBS), and the Yale Stem Cell Center. Professor Giraldez's research focuses on understanding the regulatory code that governs gene expression during vertebrate development after fertilization. His lab investigates four interconnected areas: genome activation during the maternal-to-zygotic transition, post-transcriptional regulation of gene expression, modeling of therapeutic mRNA design, and modeling of gene regulatory networks. Using zebrafish as a primary model organism combined with advanced genomic, computational, and imaging approaches, his lab has made significant contributions to understanding how transcription factors activate the embryonic genome and how RNA regulatory elements control mRNA stability and translation. Analysis of Professor Giraldez's recent publications reveals a strong focus on the molecular mechanisms of embryonic development, particularly the maternal-to-zygotic transition where control of development passes from maternal to embryonic factors. His work increasingly integrates high-throughput genomic approaches with computational modeling to decode regulatory elements in RNA that determine stability, translation efficiency, and tissue-specific expression - knowledge directly applicable to therapeutic mRNA design for gene therapy and vaccines. Scientific Awards and Honors: HHMI Faculty Scholar (2016) Blavatnik Award for Young Scientists National Finalist (2016) Vilcek Prize for Creative Promise in Biomedical Science (2014) Pew Scholar in Biomedical Sciences (2008) NYAS Blavatnik Young Investigator Award Finalist (2007) Professor Giraldez has established a productive research program with consistent funding and publication in top-tier journals. His lab maintains active collaborations with researchers across Yale and beyond, as evidenced by his frequent co-authorship with scientists from multiple departments. He has trained numerous students and postdocs who have gone on to independent research careers. The Giraldez Lab maintains a diverse team of researchers working at the intersection of developmental biology and genomics. The lab provides extensive resources including published datasets, computational tools like CRISPRscan, and detailed genomic annotations available through their data repository. Professor Giraldez's research program continues to advance our understanding of fundamental gene regulatory mechanisms with implications for both basic science and therapeutic applications.

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Andre LevchenkoView profile

Professor

Max Planck Institute of Molecular Cell Biology and GeneticsGermany

Andre Levchenko is the John C. Malone Professor of Biomedical Engineering at Yale University, with secondary appointments in Neurosurgery and affiliations spanning the Yale Cancer Center (Cancer Signaling Networks Program), Systems Biology Institute (Director), Yale Biomedical Imaging Institute, and Program in Neurodevelopment and Regeneration. His lab employs interdisciplinary approaches integrating systems biology, microfluidics, and computational modeling to investigate cellular decision-making. Research focuses on three interconnected themes: Dynamic signaling networks : Decoding VEGF/YAP crosstalk in angiogenesis, NOTCH spatiotemporal patterning, and oscillations in HIF-1α during hypoxia Cancer mechanisms : Ion transport in glioblastoma invasion, metabolic adaptations in tumors, and therapeutic targeting of transcriptional networks Stem cell & developmental engineering : Brain organoid specification using WNT/SHH gradients, mechanobiology of stem cell differentiation, and CRISPR-engineered models Publication analysis reveals consistent emphasis on quantitative approaches to cell signaling (60% of recent work), cancer biophysics (30%), and neurodevelopmental engineering (10%), with frequent use of single-cell analysis, microfluidics, and mathematical modeling. Major scientific recognitions include: Burroughs Wellcome Fund Fellowship (1999-2001) American Asthma Foundation Early Excellence Award (2010) Elected Fellow, American Institute for Medical and Biological Engineering (2013) The Levchenko Lab at Yale's Systems Biology Institute hosts graduate students and postdocs pursuing projects at the interface of engineering, systems biology, and translational medicine. Active collaborations extend to neurosurgeons, oncologists, and stem cell biologists across Yale.

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Matthias H. HennigView profile

Professor

University of EdinburghUnited Kingdom

Matthias H. Hennig is a Professor of Computational Neuroscience at the University of Edinburgh, School of Informatics, Institute for Adaptive and Neural Computation. He leads the Hennig Lab, which focuses on the intersection of neuroscience and computational methods. His research spans three main areas: Development of tools for analysis of large-scale neural recordings, including the SpikeInterface project and Herding Spikes software Modeling neural population activity using data-driven approaches like Targeted Neural Dynamical Modeling Studying retinal development and function, particularly spontaneous network activity patterns like retinal waves The lab has produced significant methodological contributions to neural data analysis, with software tools used internationally. Recent publications (2019-2022) show consistent output in high-impact journals across computational neuroscience, neural data analysis methods, and biological studies of neural circuits. The research demonstrates a strong focus on developing reproducible analysis pipelines for next-generation electrophysiology data. Professor Hennig currently supervises six PhD students across multiple CDT programs and has an impressive track record of student placements in both academic and industry positions. His international collaborations span institutions in Europe, North America, and India, reflecting the global impact of his work.

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Ralf SchmälzleView profile

Associate Professor

Michigan State UniversityUnited States

Ralf Schmälzle is an Associate Professor in the Department of Communication at Michigan State University's College of Communication Arts and Sciences. He serves as Graduate Director of the M.A. in Health and Risk Communication program, Co-Director of the Center for Avatar Research and Immersive Social Media Applications (CARISMA), and Core Leader of the Health and Risk Communication Center (HRCC). His research bridges communication science, cognitive neuroscience, and psychology to investigate how the brain processes persuasive messages in health, media, and interpersonal contexts. Dr. Schmälzle's work centers on neurocognitive communication and media neuroscience, utilizing fMRI, EEG, and computational modeling to study audience engagement and health message processing. His recent research explores AI-generated health messages, VR-based advertising, and neural correlates of social interaction in virtual environments. Key methodologies include mobile EEG hyperscanning, pupillometry, and gaze-contingent paradigms to decode attention and memory mechanisms during media exposure. His publication trends (2023-2025) reveal accelerating integration of artificial intelligence with neuroimaging, particularly in cross-cultural health communication and immersive media environments. Methodological innovation dominates his output, with VR billboard paradigms and embodied AI agents enabling naturalistic studies of message exposure-reception-retention chains. A consistent focus on translating neural metrics into practical health campaign design distinguishes his contributions to the field. As Graduate Director of the Health and Risk Communication M.A. program and founder of the Neuroscience of Messages Lab, Schmälzle mentors students in interdisciplinary research linking communication, neuroscience, and technology. His leadership in CARISMA-lab and HRCC facilitates collaborative grant-funded projects examining social-communicative processes through emerging media platforms. He founded the Neuroscience of Messages Lab (NOM) and co-directs CARISMA-lab, creating interdisciplinary environments for studying communication through cognitive neuroscience and immersive technologies. Current lab initiatives focus on AI-human interaction in VR health coaching, neural synchrony during collective media experiences, and cross-cultural neural responses to health messages using mobile neuroimaging.

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Akash PalView profile

Research Fellow

Max Planck Florida Institute for NeuroscienceUnited States

Akash Pal serves as a Research Fellow at the Max Planck Florida Institute for Neuroscience (MPFI), where he conducts innovative research at the intersection of neuroscience and optical imaging methodologies. His core research interests include: Development of genetically encoded sensors for brain chemistry and voltage imaging Neuropeptide signaling pathways in appetite regulation and satiation Stochastic modeling of neural processes in metabolism Advanced optical techniques for neurochemical monitoring Dr. Pal's recent publications demonstrate a trajectory toward cutting-edge neuroimaging tools, with his 2024 Nature paper revealing competitive stochastic mechanisms in neuropeptide-regulated satiation and his 2020 review synthesizing progress in genetically encoded sensors for brain chemistry and voltage. This work establishes him as a contributor to next-generation methodologies for decoding complex neural processes.

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Laurence TrussellView profile

Professor

Oregon Health & Science UniversityUnited States

Laurence Trussell is a Professor and Interim Director of the Oregon Hearing Research Center at Oregon Health & Science University (OHSU), with concurrent appointment as a Scientist at the Vollum Institute. His research focuses on neural mechanisms of hearing, particularly brainstem circuitry and synaptic physiology in auditory processing. Education: Ph.D. in Biology, University of California, Los Angeles (1983) Research Interests: Dr. Trussell investigates how brainstem circuits encode acoustic signals and how synaptic physiology preserves auditory information. His seminal work demonstrates that timing-encoding neurons are molecularly specialized, reveals synaptic learning mechanisms at early sensory stages, and elucidates co-release of transmitters acting on single receptors. His research integrates molecular, biophysical, and circuit-level approaches to dissect auditory processing. Publication Trends: His 2013-2025 publications consistently explore dorsal cochlear nucleus physiology, emphasizing synaptic transmission mechanisms ( e.g. , glutamate dynamics, KCNQ channels), neural oscillations, electrical coupling, and cell-type-specific circuitry. Key themes include calcium channel nanodomains, inhibitory neuron subtypes, and multimodal integration, reflecting his focus on fundamental mechanisms of auditory signal processing from cellular to circuit levels. Advising and Grants: Publicly available information does not specify doctoral advisees or grant funding details, though his leadership of major research centers implies significant mentorship and extramural support. Labs and Teams: He directs research at the Oregon Hearing Research Center and Vollum Institute, leading teams studying auditory pathways through electrophysiology, imaging, and molecular techniques to decode hearing mechanisms and disorders.

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