جست‌وجوی استاد و پژوهشگر

Laura Eloمشاهده پروفایل

استاد

• Computational Biomedicine
• Medical Bioinformatics
• Data Science
• +۷ مورد دیگر

Laura Elo serves as Professor of Computational Medicine and Head of the Medical Bioinformatics Centre at the University of Turku, Finland. She concurrently holds the position of Research Director at Turku Bioscience Centre and acts as InFLAMES Flagship Contact, driving interdisciplinary biomedical research initiatives. Her academic foundation includes a PhD in Applied Mathematics (2007) and Adjunct Professorship in Biomathematics (2011), establishing her quantitative expertise before transitioning into biomedical applications. Her research program focuses on transforming molecular and clinical datasets through statistical modeling and advanced machine learning . Key thrusts include robust computational tools for proteome/epigenome analysis, AI-driven digital health diagnostics, and computational systems immunology for immune-mediated diseases. This work directly addresses challenges in reproducibility and scalability of high-throughput biotechnology data. Analysis of her recent publications reveals dominant themes in type 1 diabetes biomarker discovery , multi-omics integration , and immune system modeling , with strong emphasis on clinical translation through collaborations with experimental and medical teams. Her scientific recognition includes: JDRF Career Development Award Professor Elo actively trains MSc/PhD students and postdoctoral fellows while leading major research initiatives including ERC grants. Her teaching portfolio spans Bioinformatics Journal Club, AI in Diagnostics, and Systems Biology courses. The Elo Lab (https://elolab.utu.fi) operates as a hub for computational biomedicine, developing open-source tools like CellRomeR while maintaining close ties with Turku Bioscience Centre's experimental facilities for validating computational predictions in immunology and metabolic disease contexts.

Harri Lähdesmäkiمشاهده پروفایل

دانشیار

• Probabilistic Machine Learning
• Deep Generative Models
• Artificial Intelligence
• +۴ مورد دیگر

Harri Lähdesmäki is an Associate Professor (tenured) at the Department of Computer Science, Aalto University, where he leads the Computational Systems Biology research group. His work focuses on probabilistic machine learning and deep generative models with applications in biomedicine and molecular biology. Key Research Interests: Probabilistic machine learning, deep generative models, computational biology, bioinformatics, longitudinal data modeling Contact: harri.lahdesmaki@aalto.fi | Konemiehentie 2, 02150 Espoo, Finland His recent publications highlight advancements in: Gaussian process priors for scalable deep generative models Single-cell analysis of immune repertoires in leukemia and diabetes Probabilistic deconvolution methods for RNA-seq data Epigenetic analysis using hidden Markov and mixed models Transformer-based survival prediction and missing data handling Harri’s work integrates mechanistic modeling with Bayesian inference, particularly applied to immunology, cancer biology, and early disease prediction.

Outi Salo-Ahenمشاهده پروفایل

مدرس ارشد

• Pharmaceutical Chemistry
• Molecular Modeling
• Drug Design
• +۵ مورد دیگر

Senior Lecturer Outi Salo-Ahen is affiliated with Åbo Akademi University's Faculty of Natural Sciences and Engineering , Department of Pharmacy. Her research focuses on computational pharmacology, drug design, and pharmaceutical chemistry, particularly targeting chemokine receptors (CCR5/CXCR4) and transient receptor potential channels (TRPA1) for therapeutic applications. Doctor of Pharmacy (2006, University of Kuopio/UEF) MSc in Pharmaceutical Chemistry (2001, UEF) BSc in Pharmacy (1999, UEF) University Pedagogy Modules 1-5 (2012-2015) Her work contributes to UN Sustainable Development Goals through education and pharmaceutical innovation . Recent research trends include: Antimicrobial resistance solutions TRPA1 channel modulation Nanotechnology-enabled drug delivery Multi-target HIV-1 inhibitors 3D printing of biocompatible materials Computational analysis of nucleic acid frameworks She actively supervises doctoral projects, serves on assessment panels, and leads collaborations like Nordic Pharmaceutical Translation and Innovation. Her 60+ publications demonstrate expertise in molecular modeling and drug discovery.

• Artificial Intelligence
• Data Science
• Computational Creativity
• +۲ مورد دیگر

Hannu Toivonen is a Full Professor of Computer Science at the University of Helsinki, affiliated with the Faculty of Science and the Department of Computer Science. He leads the Discovery Research Group and is part of the Helsinki Institute for Information Technology (HIIT) and the Finnish Center for Artificial Intelligence (FCAI). He obtained his PhD in Computer Science from the University of Helsinki in 1996 and has held his professorship since 2002. His research spans Artificial Intelligence , Data Science , Computational Creativity , and Data Mining , with applications in generative art, automated journalism, and bioinformatics. His research focuses on: Developing AI systems for creative tasks (e.g., poetry, music, and art generation) Cross-lingual natural language processing and unsupervised learning Ethical and societal implications of AI in media and labor Analysis of his 15 most recent publications (2021–2025) reveals a strong emphasis on computational creativity and AI-driven content generation , with interdisciplinary applications in digital humanities, journalism, and biology. Trends include ethical AI frameworks, human-AI collaboration, and innovative evaluation methods for generative systems. Scientific Awards & Honors: Knight, First Class, Order of the White Rose of Finland (2019) Best Applied Research Award, IEEE ICDM (1998) Honorary Member of TKO-äly (2010) Member of Finnish Academy of Science and Letters He has supervised over 20 doctoral theses and secured ~7 MEUR in grants (e.g., EU projects: Embeddia , Newseye ). He leads the Discovery Research Group and collaborates with institutions like VUB (Belgium) as a Francqui International Professor (2025).

• Bioinformatics
• Computer Science
• Algorithms
• +۳ مورد دیگر

Dr. Juha Kärkkäinen is a University Lecturer and Principal Investigator at the Department of Computer Science, University of Helsinki, specializing in Algorithmic Bioinformatics. He supervises PhD students in the Doctoral Programme in Computer Science and actively contributes to research outputs and academic events. Institution: University of Helsinki Department: Department of Computer Science Rank: Lecturer His research focuses on string processing , data structures , and combinatorial pattern matching , with recent work on bijective Burrows-Wheeler transforms, LCP arrays, and efficient string indexing. Google Scholar lists publications spanning 2024 to 1999, highlighting his expertise in algorithm design and compression techniques . Notably, he has participated in and organized events like the International Workshop on Combinatorial Algorithms and delivered a keynote speech at the 1st Summer School on Bioinformatics Algorithms. While no explicit awards are detailed, his editorial roles in scientific collections and conferences underscore his academic influence.

Antti Posoمشاهده پروفایل

استاد

• Drug Design
• Molecular Modeling
• Anti-Cancer Drugs
• +۳ مورد دیگر

Antti Poso is a Professor of Drug Design at the University of Eastern Finland (Kuopio), affiliated with the School of Pharmacy under the Faculty of Health Sciences. His research focuses on computer-aided molecular design, particularly targeting anti-cancer drugs and anti-microbials. Key projects include the EDCMET project (2019–2024) and the GeneCellNano Flagship (2020–2028). He leads the Molecular Modeling and Drug Design Research Group, specializing in QSAR analysis, kinase inhibition profiling, and systems-level drug response modeling. Recent work includes studies on SARS-CoV-2 inhibitors, endocrine disruptors, and bacterial pathogenesis. His findings bridge chemical structure with biological outcomes, leveraging computational tools like CCA and molecular dynamics simulations. Collaborations span medicinal chemistry, pharmacology, and systems biology, contributing to both academic and applied drug discovery efforts. Education: Not explicitly stated in texts; assumed to hold advanced degrees in pharmacy or chemistry. Research Themes: Drug design, molecular modeling, QSAR, computational biology, and anti-infective agents. Key Contributions: Over 150+ publications, including influential works on chemoinformatics-driven drug response analysis and structure-based inhibitor design. Publications highlight advancements in kinase inhibitors, anti-microbial strategies, and viral hijacking mechanisms. His work emphasizes translating computational insights into therapeutic solutions for cancer, infectious diseases, and metabolic disorders.

Simon Puglisiمشاهده پروفایل

استاد

• Algorithms
• Bioinformatics
• Data Compression
• +۳ مورد دیگر

Simon Puglisi is a Professor at the University of Helsinki's Department of Computer Science, within the Faculty of Science. His research focuses on algorithms, bioinformatics, data compression, and string processing, with notable contributions to genomic data analysis and efficient indexing techniques. He holds the Alberto Apostolico Best Paper Award (2021) and leads the WILL # CHAIR # BOSSA project (2025–2029). His work includes scalable k-mer indexing tools like Themisto and advancements in Lempel-Ziv compression and suffix tree algorithms. He frequently collaborates internationally, participates in editorial roles for journals like the ACM Journal of Experimental Algorithmics , and contributes to conferences such as the International Symposium on Combinatorial Pattern Matching. Research Interests: Algorithm design for string processing and bioinformatics Efficient data structures for genomic data Compression techniques (e.g., Lempel-Ziv, Burrows-Wheeler) Dynamic and space-efficient algorithms Grants & Projects: WILL # CHAIR # BOSSA (2025–2029) Ongoing collaborations with institutions like the University of Melbourne and King's College London

Miia Lindströmمشاهده پروفایل

استاد

• Veterinary Science
• Food Safety
• Clostridium botulinum
• +۴ مورد دیگر

Miia Lindström is a Professor at the University of Helsinki's Faculty of Veterinary Medicine, specializing in Food Hygiene and Environmental Health. She serves as a Supervisor for the Doctoral Programme in Clinical Veterinary Medicine and the Doctoral Programme in Food Chain and Health, and is a key member of Helsinki One Health (HOH), which aims to make the University of Helsinki one of the world's most recognized institutions in One Health research by 2025. Her research primarily focuses on veterinary science, particularly Clostridium botulinum and botulinum neurotoxins, food safety, microbiology, and food hygiene. Her work spans fundamental research on bacterial pathogenesis, sporulation mechanisms, and neurotoxin production, as well as practical applications in food safety and public health. She has contributed significantly to understanding how bacterial pathogens contaminate food sources and how they can be controlled. Analysis of her recent publications reveals a strong trend toward molecular and genomic approaches to understanding bacterial pathogenesis, particularly focusing on Clostridium botulinum. Her research increasingly integrates structural biology, genomics, and microbiome analysis to understand bacterial adaptation, toxin mechanisms, and host-pathogen interactions. She has also expanded her research to include insect vectors of bacterial pathogens and the role of mobile genetic elements in bacterial adaptation. As an active member of Helsinki One Health, Professor Lindström has contributed to profiling One Health research at the University of Helsinki, focusing on food safety, antimicrobial resistance, and risk management. Her research has substantial societal impact, particularly evident during the COVID-19 pandemic where HOH researchers were frequently featured in Finnish and international media. Professor Lindström has supervised numerous Master's and doctoral students, including Sirja Koskensalo, Anna Mertaoja, Tinja Toikka, and Hanna Castro. She has been involved in multiple significant research projects, including 'Understanding the Clostridium Spore' (CLOSPORE) and 'A Clostridal Biology Network' (CLOSTNET), which have received substantial funding and involved international collaborations. Her professional activities include extensive conference participation, peer reviewing for journals like Food Control and Research in Microbiology, and numerous public engagements. She has been particularly active in the Annual Finnish Veterinary Congress and various international conferences on botulism research and food microbiology.

Ville Paavilainenمشاهده پروفایل

پژوهشگر

• Biochemistry
• Cell Biology
• Molecular Biology
• +۹ مورد دیگر

Ville Paavilainen is a Research Director at the Institute of Biotechnology, University of Helsinki, and supervisor for doctoral programs in Biomedicine and Integrative Life Science. With a postdoctoral background at the University of California, San Francisco (2008–2014), he focuses on Biochemistry , Cell Biology , and Molecular Biology , particularly mechanisms of protein translocation, membrane biology, and structural modeling. His research includes groundbreaking work on Sec61 translocon inhibition for cancer therapy and mitochondrial gene expression noise . Recent publications address lipid scrambling pathways, glioma stem cell targeting, and actin regulation. Active projects span EU-funded drug discovery and NIH collaborations. Key scientific contributions include Elucidating Sec61-client interactions Developing computational models for signal peptide prediction Uncovering mitochondrial-ER communication mechanisms He has supervised PhD theses (e.g., Paul Carlson) and contributed to over 39 research outputs. His work bridges structural biology, computational modeling, and translational pharmacology, with applications in tumor biology and neurodegenerative disease research.

Ilkka Kronholmمشاهده پروفایل

دانشیار

• Evolutionary Biology
• Epigenetics
• Genetic Variation
• +۴ مورد دیگر

Ilkka Kronholm is an Associate Professor in evolutionary biology at the University of Jyväskylä, affiliated with the Department of Biological and Environmental Science under the Faculty of Mathematics and Science. His research focuses on understanding how genetic and epigenetic variation drives evolutionary adaptation in response to environmental changes. Key areas include epigenetic modifications, chromatin structure impacts on mutation rates, and experimental evolution using microbial systems. Recent work emphasizes the role of epigenetics in microbial adaptation to fluctuating temperatures and stress conditions. Collaborative projects include analyzing fungal growth dynamics via microfluidics and exploring the evolutionary consequences of prophage activation in bacterial pathogens. Kronholm's lab utilizes genomic, bioinformatic, and quantitative genetics approaches to bridge mechanistic and evolutionary questions. Publications highlight themes like epigenetic regulation of antimicrobial resistance, transgenerational effects in fungi, and the interplay between mutation spectra and chromatin architecture. His work contributes to theoretical frameworks linking short-term phenotypic plasticity with long-term evolutionary trajectories.

Jouni Järvinenمشاهده پروفایل

مدرس

• Rough Set Theory
• Lattice Theory
• Non-Classical Logics
• +۴ مورد دیگر

Jouni Järvinen is a University Lecturer in Software Engineering at LUT University in Lahti, Finland, and a Docent in the Department of Mathematics and Statistics at the University of Turku. He holds a PhD in Mathematics and serves as a Mathematics Consultant at TXODDS. His work bridges theoretical and applied research across multiple domains. Affiliations : LUT School of Engineering Sciences, University of Turku Education : PhD in Mathematics Research Interests lie at the intersection of Rough Set Theory , Lattice Theory , and Non-Classical Logics . He explores algebraic structures like Nelson algebras, Kleene algebras, and Galois connections, applying them to problems in Artificial Intelligence and Bioinformatics . His work often connects abstract mathematical frameworks to practical applications in Information Systems and Machine Learning . Publication Trends reveal a focus on Rough Sets and Algebraic Structures across 51 works (2025–1998). Recent studies (2025–2020) examine multigranular rough sets, pseudocomplemented Kleene algebras, and relational correspondences for fuzzy rough approximations. Earlier works (2015–2007) address topics like Tolerance-Based Rough Sets , Galois Connections , and Natural Language Disambiguation . Peer Review Activities include contributions to journals such as Fuzzy Sets and Systems , International Journal of Approximate Reasoning , and Studia Logica . His research spans Theoretical Computer Science , Mathematical Logic , and Biomedical Data Analysis .

• Bioinformatics
• Computational Genomics
• Protein Structure Analysis
• +۳ مورد دیگر

Liisa Holm is a Professor at the Institute of Biotechnology, University of Helsinki, and a supervisor in the Doctoral Programme in Integrative Life Science. Her research focuses on computational genomics, structural bioinformatics, and protein function prediction. Research Interests : Computational biology, protein structure analysis, machine learning applications in genomics Key Projects : HiLIFE Grand Challenge (antimicrobial resistance), burn wound infection metagenomics, protein structural aging studies Recent Trends : Holm's work spans protein structure comparison (DALI algorithm), pan-genome analysis of protein crops (faba bean), and aging-related structural changes in proteins. She also contributes to AI-driven advancements in structural biology. Scientific Awards : 2024 Nobel Prize in Chemistry (for AI-driven protein research) Leadership Roles : Project leader for Academy of Finland grants, member of international scientific committees

Rupali Rajendra Bhadaneمشاهده پروفایل

پژوهشگر

• Computational Biology
• Drug Design
• Molecular Dynamics Simulations
• +۹ مورد دیگر

Rupali Rajendra Bhadane is a postdoctoral researcher at Åbo Akademi University's Pharmaceutical Science Laboratory (PSL) and Structural Bioinformatics Laboratory (SBL), contributing to interdisciplinary science under the Faculty of Natural Sciences and Technology. Her work spans computational biology, drug design, and sustainable material development. PhD in Pharmacy 8 years of undergraduate teaching experience Her research integrates virtual screening , molecular dynamics simulations , and DFT calculations to advance drug discovery (e.g., Glycomimetic SGLT2 inhibitors , HDAC-2 modulators ), while also applying computational methods to analyze bio-based adhesive materials and virus-mimetic nanoparticles . Recent publications highlight her work on Covid-19 spike protein mutations , g-quadruplex targeting , and core/shell nanostructures for siRNA delivery. She actively contributes to datasets through the Finnish National Protein Crystallography Consortium and European Synchrotron Radiation Facility . Current projects include D2V: From Dust to Value (2023-2026), focusing on circular bio-based residues with Business Finland funding. Her work aligns with UN SDGs for health innovation and environmental sustainability.

Simone Rubinacciمشاهده پروفایل

پژوهشگر

• Population Genetics
• Statistical Genetics
• Genomic Data Analysis
• +۳ مورد دیگر

Simone Rubinacci is a Senior Researcher and Group leader at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, since September 2024, following postdoctoral fellowships at Harvard Medical School (2023-2024) and the University of Lausanne (2019-2022). Her academic foundation includes a DPhil in Statistics from the University of Oxford (2016-2020). Her educational trajectory: DPhil in Statistics, University of Oxford (2016-2020) Postgraduate student, Systems Biology Doctoral Training Centre, University of Oxford (2015-2016) MSc in Computer Science, University of Milano-Bicocca (2012-2015) BSc in Computer Science, University of Milano-Bicocca (2009-2012) Rubinacci pioneers statistical methods for large-scale genomic datasets, specializing in haplotype analysis and structural variation in human genomes. Her work extracts insights from noisy data like low-coverage sequencing and SNP arrays, directly addressing population structure and disease genetics. She bridges computational statistics with biomedical applications to decode genetic diversity and disease mechanisms. Her 2024-2025 publications reveal intense focus on genomic data infrastructure: haplotype reference panels, imputation techniques, and polygenic risk scoring. Key innovations include SURFBAT for family-based association testing, UK Biobank imputation frameworks, and ancient DNA damage mitigation—collectively advancing precision genomics through computational rigor. Major recognitions: Epstein Award Finalist, ASHG 2024 Epstein Award Semifinalist, ASHG 2020 Swiss National Science Foundation Postdoc.Mobility fellowship EPSRC PhD salary award She has taught statistics and computer science at Oxford, Lausanne, and Milano-Bicocca. Current funding includes UK Biobank credits for haplotype phasing and her FIMM-EMBL project 'Integrating identity-by-descent and phasing to unveil novel insights on disease mechanisms' (2024-2029). As FIMM-EMBL Group leader, she directs genomic methodology development within Helsinki's Faculty of Medicine and contributes to the university-wide DIVSOL-Humt profiling initiative for data-intensive societal research.

• Nanotechnology
• Computational Chemistry
• Surface Chemistry
• +۳ مورد دیگر

Nian Wu is a Postdoctoral Researcher at the Department of Applied Physics, Aalto University. Their work bridges computational chemistry and nanoscale surface science. Research Focus: Surfaces and Interfaces at the Nanoscale Email: nian.wu@aalto.fi Research Interests: Nanotechnology for molecular adsorption analysis Deep learning applications in scanning probe microscopy Protein-ligand interaction modeling Publications (2023-2024): Recent work includes studies on lignocellulosic molecule adsorption and protein-ligand interactions, combining machine learning with surface analysis techniques. Collaborations: Works with researchers across multiple institutions, including Joakim Jestilä, Adam Foster, and Peter Liljeroth.