Meet The Team

 
Since December 2021, I am part of CoSy.Bio Institute`s dynamic young team, as assistant of Prof. Dr. Jan Baumbach.Before I started working at Hamburg University, I have been working on major international event projects as a Event Planner.  
Now, I am looking forward to support our international team and organize their daily administrative life, so they can fully enjoy researching!

I have been a science manager for CoSy.Bio since December 2021. Together with my colleague Dr. Nina Wenke, we manage grant applications, projects and day-to-day business of the institute. I did my PhD at Harvard University, where I studied how Proteus mirabilis utilizes a type VI secretion system to engage in bacterial social interactions. For my postdoctoral studies, I moved to the University of California - San Diego. Here, I used multi-platform metagenomics to study horizontal gene transfer in cheese rind microbiomes.

I’m a group leader of the Computational Genomics and Transcriptomics group (cgat-group.de). My main research interest is mechanisms of pathological conditions such as diseases with complex phenotypes and drug side effects and the role of alternative splicing. I graduated from Lomonosov Moscow State University (Moscow, Russia) and did PhD in Kharkevich Institute in Moscow in Professor Mikhail Gelfand's lab. There I studied the evolution of transcriptional regulatory networks in bacteria. During my PhD, I shortly stayed at Stowers Institute for Medical Research (Kansas-City, USA), and at Okinawa Institute of Science and Technology (Okinawa, Japan) where I went on working on the regulation of bacterial metabolic pathways. As a research scientist, I worked at the Skolkovo Institute of Science and Technology (Moscow) on 3D chromatin structure analysis. In 2019, I joined the group of Professor Jan Baumbach at the Technical University of Munich, and continued working with the group at the University of Hamburg.

 
Since October 2021, I’m one of three admins in the CoSy.bio networks Team. Before I joined Hamburg University, I had a chance to get 2 years experience in a software development company as well as 1,5 years of experience at a social media agency.
 
What's my journey here? Well, try to offer my technical knowledge and experience in an easy way to everyone who needs a solution. For our future I wish for awesome projects with nice features (and for the fun some bugs) and great new things to see and learn. 
 
 
My main interest is to stay curios can be an easy way to grow with the challenge.

I obtained my master's degree in computer science from Friedrich-Alexander University Erlangen-Nürnberg (2019). During my studies, I have been working as a professional full-stack web developer in my own company. At TUM and later UHH, I was part of the EU Horizon2020 FeatureCloud project, doing my PhD in computer science. My focus mainly lies on machine learning and data privacy in conjunction with federated systems. Today, I am working with CosyBio on dehaze, a company aiming to bring precision medicine into clinical practice. I have a passion for difficult technical challenges requiring an analytical approach and cross-domain expertise.

Since May 2022, as a postdoc at CoSy.Bio, I have been applying my neuroimmunology expertise, developed during my PhD at the University of Southern Denmark, to systems and network biology using single-cell multi-omics. Enhanced by experiences at Imperial College London, the Medical University of Vienna, and the University of Gothenburg, my research is primarily focused on multiple sclerosis. Currently, with the support of the Lundbeckfonden Postdoc Fellowship, I am dedicated to uncovering new disease mechanisms and therapeutic targets.

I am a postdoctoral researcher and junior research group leader at the Cosy.Bio lab at the University of Hamburg. I studied Biosystems Engineering at the Otto von Guericke University Magdeburg and obtained the Master’s degree for my experimental studies on adenoviral vector production in animal cell cultures, which I performed at IBET/ITQB-UNL in Lisbon, Portugal. During my PhD, I continued infection research in the dry lab and built mathematical models of virus replication dynamics to support the optimization of influenza vaccine production at the Bioprocess Engineering department at the Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg. At Cosy.Bio, my team and me develop innovative computational methods that link bioinformatics multi-omics analysis with dynamic models to improve model predictions for complex diseases and biological processes, such as bone defect healing within the SyMBoD project. Furthermore, I am developing methodologies for artificial intelligence-based research of defective interfering particles within the Vir-AI-DIP project. Using machine and deep learning techniques we analyze and optimize the antiviral potential of defective viral genomes for improved prevention and treatment of infectious diseases.

In May 2021, I started as a PhD student at CoSy.Bio (UHH). My current tasks include work surrounding the REPO-TRIAL drug repurposing project. I contribute in the development of network-based drug repurposing solutions but also in the research for applications of LLMs in systems medicine for knowledge generation and extraction. In August 2020, I joined the Chair of Experimental Bioinformatics at TUM for the thesis of my Bioinformatics master's degree.There, I focused on the development of a web application for the analysis and exploration of heterogeneous molecular disease networks.

I'm a Ph.D. student from the Cancer Epigenetics research group at Universidad Autónoma Metropolitana in Mexico. I received a Bachelor's degree in Pharmaceutical Chemistry and a Master's degree in Biochemistry from Universidad Nacional Autónoma de México. My research project is co-supervised by Prof. Dr. Jan Baumbach and Prof. Dr. Maya Topf and is focused on studying the role of BORIS in ovarian cancer through transcriptomic analysis and molecular modeling.

I am a research associate at the CoSy.Bio lab since April 2023, working on the DrugSiderAI and PosyMed projects. I earned a B.Sc. in Electrical Engineering from IAU and an M.Sc. in Biomedical Engineering from AUT. During my master’s program, I gained experience in signal processing and machine learning (ML) methods for biomedical applications. Following my graduation, I conducted research on applying ML techniques to transcriptomic data, with the aim of advancing personalized medicine. Additionally, I focused on network-based approaches and gained experience working with graph convolutional neural networks to capture the complex relationships in biological data. My primary research interest lies at the crossroads of applying network-based ML to the field of medicine. I am excited to continue exploring this field and contributing to cutting-edge research as part of the CoSy.Bio team.

After receiving a bachelor's degree in Biotechnology at the University of Stuttgart, I relocated to the University of Hamburg to pursue a Master's degree in Bioinformatics. During this time, I joined CoSy.Bio for my master thesis on Defective Interfering Particles (DIPs) and employed Machine Learning to reveal the mechanisms of their generation. Since July 2023 I am a PhD student to continue this research. Besides that I am also developing a neural network using federated learning to enhance the quality of live for patients dealing with prostate cancer while preserving their data privacy.

I'm a Ph.D. student at CoSy.Bio and part of the FeatureCloud/REPO-TRIAL project (Horizon2020). I received my B.Sc. in Medical Informatics and M.Sc. in Bioinformatics from the Eberhard Karls University Tübingen. In my master thesis, I implemented a Random Survival Forest (RSF) Python package to predict the survival of blood cancer patients based on molecular data. My focus lies on machine learning in biomedical applications. 

I am a PhD student at the Bernhard Nocht Institute for Tropical Medicine (BNITM) and am involved in research into mosquito biology. My focus is on the application of machine learning to analyse patterns in mosquito wings. This research aims to improve our understanding of mosquito biology and vector surveillance methods, contributing to the overall goal of mitigating the impact of mosquito-borne diseases such as malaria and dengue fever. My academic path began with a degree in biochemistry at the University of Würzburg, later switching to health sciences in Hamburg. I am particularly interested in computer vision and the extraction of biologically relevant information from images. Before my current job, I did research at DESY, where I studied X-ray diffraction patterns through the lens of machine learning and at the BNITM to investigate the usefulness of open access data for disease modelling.

I have been a PhD student at the Chair of Computational Systems Biology at the University of Hamburg since January 2023 and I am part of the PhysioAI project. The primary aim of PhysioAI is to assess and enhance AI-powered multimodal tools for measuring physical activity in osteoarthritis treatment. I am particularly interested in Deep Learning, Transfer Learning, and Federated Learning. I received an M.Sc. in Computer Science from QIAU in 2021. My master's thesis focused on the research of recommender systems using machine learning techniques. Throughout my studies, I worked for over 5 years in tech companies as a web developer.

I am a PhD student engaged in a collaborative project on Nanopore sequencing between the Outbreak Preparedness and Response (OPR) group at the Bernhard-Nocht-Institute for tropical medicine (BNITM) and CoSyBio. I came to CoSyBio in 2021 as a master’s student when I implemented CAMI, a tool for disease module identification. I then moved on to work on my master’s thesis which involved the AI-based analysis of time series sequencing data of influenza A virus Defective Interfering Particles. I hold a master’s degree in bioinformatics from the University of Hamburg and a bachelor’s degree in biotechnology from the Technical University of Braunschweig.Currently, my PhD research involves the exploration of genome dynamics of hemorrhagic fever viruses in Nanopore sequencing data with a focus on defective viral genomes.

Since May 2021, I have been actively involved as a Ph.D. research assistant at the CoSy.Bio lab at the University of Hamburg, where my work plays a crucial role in the EU Horizon 2020 FeatureCloud project. I hold a Master of Science in Artificial Intelligence from IUST, culminating in a thesis that explored hybrid recommendation systems using Bayesian networks. Currently, my research is predominantly centered around privacy-preserving Federated Learning, with a special emphasis on its applications within biomedicine, including single-cell RNA-seq and medical imaging data.

I started as a Ph.D. student at CoSy.Bio in August 2023. My research focus is the computational analysis of spatial multi-omics image data in a collaboration with the Universitätsklinikum Hamurg-Eppendorf (UKE). I earned my Bachelor's and Master's degree in medical engineering (at RAC Remagen and FAU Erlangen), where I specialized in utilizing deep learning and computer vision methods for medical image analysis. Before starting my Ph.D. I also worked as a software engineer for a company doing medical imaging software.

Since January 2024, I have been working as research associate at the Institute for Computational Systems Biology at the University of Hamburg contributing to the dAIbetes-Net project. This initiative involves developing a federated database network to connect and structure data in local repositories distributed around the globe, while respecting patient data privacy by design. Prior to my tenure at the CoSy.Bio laboratory, my professional journey included positions as a Developer and Data Analyst, culminating in the successful completion of an M.Sc. degree in Computer Science from the University of Southern Denmark in 2022. My professional interests span diverse domains with a focus on areas such as Data Science and Governance, Blockchain, Generative AI, and Federated/Distributed Learning etc.

Since January 2024 I am a PhD student at CoSy.Bio for the projects FeatureCloud (https://featurecloud.ai/) and dAIbetes. I completed my Bachelor of Science in Applied Computer Science at the University of Applied Sciences and Arts Hannover, followed by a Master of Science in Computer Science at the University of Vienna, specialising in Data Science. In my master thesis I worked on the combination of session- and sequence-based recommender systems in a dynamic Graph Neural Network (GNN), in particular on the development of hierarchical dynamic GNNs.
 
My current research aims at developing privacy-preserving tools that make federated collaboration not only easier, but almost effortless. By merging theory and practice, my goal is to create innovative solutions to complex challenges that redefine the way we think about data collaboration and privacy.

Since March 2023, I've joined CoSy.Bio as a visiting researcher and have started a PhD at TUM's Proteomics and Bioanalytics chair. I have an interdisciplinary background in pharmacy and computational and molecular biology, and am interested in tool development for personalized medicine and biomarker discovery. As part of the CLINSPECT-M project, my focus is on federated learning in mass-spectrometry proteomics. Currently, I am developing FedProt, a novel method for privacy-preserving federated differential protein expression analysis. Additionally, I am involved in developing UnPaSt, the unsupervised patient stratification method, and clinical RNAseq data analysis.

Starting from May 2022 I will work as a HiWi at CoSy.Bio. Right now I am in the bioinformatics master programm of UHH. Before that, I graduated from the University of Bayreuth with a bachelor's degree in biology with specialization in molecular biology and gene technology.

I am a bioinformatics master's student at the Technical University of Munich (TUM) and Ludwig Maximilian University of Munich (LMU). I joined the CoSy.Bio team as a HIWI in Spring 2022 to acquire hands-on experience and hone my practical skills. I am currently involved in the REPO-TRIAL drug repurposing project, where my primary task is to validate computational predictions using a range of techniques such as statistical analysis and data visualization.

Since October 2024, I joined CoSy.Bio as a research associate to write my Master's thesis under the supervision of Dr. Fernando Miguel Delgado Chaves. I am currently enrolled in the Faculty of Data Science at Sapienza University in Rome, where I also did my Bachelor's degree in Statistics. After taking some courses at the university that got me interested in Bioinformatics, I had the opportunity to join CoSy.Bio, where I will work on the ChatDRex project with the aim of integrating BiCoN into an LLM agent running on our Ollama server. The BiCoN tool, which clusters patients and omics data by leveraging network constraints, will be executed on our server and the LLM will interact with it through API calls. This integration will enable the LLM to submit jobs to BiCoN, check their status, and retrieve results, thereby allowing researchers to utilize BiCoN's capabilities using natural language queries.

I am a master's student at Sapienza, university of Rome. I am graduating in Data Science and I am working on my master's thesis at CoSy.Bio institute under the supervision of Dr. Fernando M. Delgado Chaves. I got my bachelor degree in Electronic Engineering at University of Catania. 
My thesis focuses on the integration of DIGEST software to an LLM-based chatbot to provide a comprehensive and easy-to-use tool for clinicians and biologists that do not have expertise in informatics. It is part of a more extensive  project involving the implementation of an interface allowing researcher to access NeDRex, a complex database for genomic research and drug discovery. 

I am currently pursuing my Master’s in Bioinformatics at the Technical University of Munich, where I also completed my Bachelor's degree in the same field. Since October 2024, I have been working as a HiWi with the CoSyBio team, supporting the research of Jeanine Liebold and Khalique Newaz. My focus is on using machine learning and bioinformatics tools to predict protein-protein interactions, particularly in the context of alternative splicing. I still live in Munich and can’t wait to move to Hamburg to continue my scientific journey here!

Prof. Schmidt, MD PhD PharmD, is a visiting Professor of Pharmacology and Personalised Medicine working in Systems Medicine and drug repurposing from Maastricht University, Netherlands, and a collaborator in the H2020 projects REPO-TRIAL and FeatureCloud.

• Justus Wolff, Postdoc

• Fabio Boniolo, Postdoc at Dana-Farber Cancer Institute, Boston

• Melisa Klug,Field Application Scientist at Standard BioTools,Munich

• Michael Lauber,

• Tim Rose,Postdoc at Universität Heidelberg

• Marisol Salgado Albarrán, Postdoc at Universidad Nacional Autónoma de México

• Tim Kacprowski, Professor at Technical University of Brunswik

• Richard Röttger, Professor at University of Southern Denmark

• Anne-Christin Hauschild, Assistant Professor at University of Marburg

• David B. Blumenthal, Assistant Professor at University of Erlangen

• Josch Pauling, Group leader at Technical University of Munich

• Markus List, Group leader at Technical University of Munich

• Olga Lazareva, Postdoc at DKFZ Heidelberg

• Afsaneh Mohammadnejad, Assistant Professor at University of Southern Denmark

• Richa Batra, Postdoc at Helmholtz Center Munich

• Nicolas Alcaraz, Postdoc at Copenhagen University

• Eudes Barbosa, Postdoc at Helmholtz Center Munich

• Douglas Parise, Postdoc at Laboratory of Cellular and Molecular Genetics (UFMG), Brazil

• Mariana Parise, Postdoc  at Laboratory of Cellular and Molecular Genetics (UFMG), Brazil

• Alexander Groenning, Postdoc at Copenhagen University

• Jesper Lund, Postdoc at Hasso-Plattner-Institute Potsdam

• Evans Kataka, Data Scientist at Procter & Gamble

• Diogo Marinho, Postdoc at Roskilde University Hospital

• Lucas Ferreira, Postdoc at Imperial College London

• Pen Sun, Senior Bioinformatician at Bayer AG Berlin

• Rashid Ibragimov, Data Scientist at IBM Deutschland GmbH

• Tobias Wittkop, Senior Data Scientist at Adaptive Biotechnologies Lmtd

• Christian Wiwie, Bioinformatician at Qiagen Aarhus

• Anna Hartebrodt, PhD student at University of Southern Denmark

• Gregor Sturm, PhD student at Innsbruck Medical Center

• Paulo Vinicius Carvalho, Postdoc at University of Southern Denmark

• Simon Larsen, Senior Data Scientists at Energienet, Denmark

• Weilong Li, Postdoc at University of Helsinki, Finland

• Amit Fenn, Postdoc

• Zakaria Louadi, Postdoc

• Dr. Karen Manalastas-Cantos, Postdoc

• Dr. Sara Ashry Sayed Mohammed

• Maria Wörheide, Hemholtz Zentrum Munich

• Markus Hoffmann, NIH Bethesda

• Nikolai Köhler, Uni Heidelberg

• Michael Lauber, Hemholtz Zentrum Munich 

• Zakaria Louadi, Illumina​

• Dr. Sepideh Sadegh, Odense University Hospital

 
I joined the CoSyBio team in September 2023. 
 
In terms of my education, I studied Business Administration and Management (BWL). Additionally, I hold a Master's Degree in Service and Development. 
 
Previously, I worked in the copper industry as a supply-chain manager.
 
As part of my current position, I provide support to the team by taking on various responsibilities such as organizing and planning tasks to ensure smooth workflow. My aim is to facilitate the Team's work so they can focus on what they do best.

As the Science Manager of CoSy.Bio, collaborating closely with my colleague Dr. Christina Saak to spearhead proposal writing, manage grant applications, and coordinate various projects. My journey with the CoSy.Bio team commenced in 2019 when I joined the Technical University Munich. Prior to this, I earned my M.Sc. in Biotechnology at the Max Planck Institute for Molecular Biomedicine in Muenster. Following this, I embarked on my doctoral research in Berlin, delving into autoimmune encephalitis at the German Center for Neurodegenerative Diseases (DZNE) and the Charité University Hospital.

I specialize in the analysis of biomedical multi-omics data, discovery of biomarkers, gene prioritization, and drug response prediction. Since May 2021, I am heading research group Computational and Systems Medicine at the UHH. We develop algorithms and create computational tools for exploration of disease heterogeneity and patient stratification, reconstruction of regulatory networks, and prioritization of drugs and drug targets. Since the privacy of patient-derived data is a major roadblock on the way of personalized medicine, we work on privacy-aware methods for distributed patients’ data analysis.

 
In October 2021, I embarked on a postdoctoral researcher journey with the CoSy.Bio team at the University of Hamburg. I am a Biotechnologist by training but I soon pivoted to Bioinformatics and Computational Biologists.
My research focuses on network and precision medicine, biomarker discovery, and large language models (like ChatGPT) for biomedical tasks. I am also interested in bridging the communication gap between clinicians and informaticians, advocating for collaborative, synergistic efforts. Beyond research, I also value science communication in the digital age, mentoring, and education.

 
I am a Postdoc at Cosy.Bio. Additionally, I am part of the Computational Systems Biology (CDL3) group at the Center for Data Science and Computing. My research interests lie in developing data (network) science approaches to explore and understand biological systems. Currently, I study the effect of alternative splicing (a phenomenon through which a single gene gives rise to multiple proteins) on the interactions between proteins.
I did my Ph.D. in Computer Science from the University of Notre Dame, USA, where I developed network-based computational methods to compare protein 3D structures. 

I am a postdoc at CoSy.Bio working on the NetMap project, where we are developing a dimensionality reduction method for single-cell molecular data based on the explanatory power of differential regulatory networks. My research interests include single-cell transcriptomics and spatial single-cell network analysis. Specifically, I focus on developing methods for inferring gene co-expression and gene regulatory networks from single-cell data and spatial single-cell data.

Since April 2023, I have joined CoSy.Bio as a postdoc. My primary research interest is employing interpretable machine learning techniques to gain new biological insights. I did my PhD under the guidance of Professor Mikhail Gelfand at IITP RAS (Moscow, Russia). My doctoral research was focused on investigating the role of mRNA secondary structure in mRNA editing of cephalopods. Additionally, I worked as a junior researcher at the Skolkovo Institute of Science and Technology and contributed to several projects in the fields of bacterial genomics and human alternative splicing research.

I’m a PhD candidate at the CoSy.Bio institute, working in close collaboration with Markus Rinschen at the UKE. Here, I use different Proteomics approaches to research inflammatory glomerular diseases in mice as well as in human tissue samples and kidney organoids. Before, I absolved my Master in Biomedicine at the MHH in Hannover and my Bachelor in Molecular Life Sciences in Lübeck. During my Master thesis, I focussed on the characterization of regulatory proteins involved in the P. aeruginosa Type III secretion system.

Since April 2020 I am a Ph.D. student at CoSy.Bio within the Sys_Care project. Before, I have been a biology master student from LMU Munich, where I have experience in working with sequencing data analysis. In my master thesis, I work at the Chair of Experimental Bioinformatics on time course network enrichment analysis on X-irradiated human fibroblast using TiCoNE and machine learning.

Since April 2022, I am a PhD student at CoSy.Bio and at the Chair of Genome Informatics of Prof. Stefan Kurtz, both at the University of Hamburg. My research interests are mainly in machine learning and deep learning, with a focus on the application of these methods to bioinformatics problems, in particular, the prediction of protein-protein interactions in the event of alternative splicing. I hold a master’s degree in Intelligent Adaptive Systems from the University of Hamburg, where I wrote my master’s thesis on feature recognition in audio and video data with deep learning. Before that, I received my bachelor’s degree in Electrical and Information Engineering from HAW Hamburg.

I'm a Ph.D. student at CoSy.Bio since April 2023 and part of the FeatureCloud and Microb-AI-Ome project.
I studied by B.Sc. of Biology at University Hamburg as well as my M.Sc. of Bioinformatics also at University Hamburg. In my master thesis I focused on privacy enhancing techniques for federated learning, especially differential privacy, while in my PhD my focus is on a federated data warehouse to allow easier data sharing in a privacy preserving manner. Generally, I'm focused on bringing privacy preserving tools for almost effortless federated collaboration.

 
From May 2021, I will start as a PhD candidate at CoSy.Bio at the University of Hamburg. After joining the Institute of Computational Biology (ICB) at Helmholtz Zentrum München, where I worked on single cell RNA seq analysis during my master internship, I extended my collaboration to work on a machine learning project with tensorflow 2. My interest in machine learning led me to the Chair of Experimental Bioinformatics at the Technical University of Munich for my master thesis, where I worked on node centrality measures for disease module identification to create new algorithms for use in drug repurposing.
In the future I will work on the development of a platform for integration of research and clinical data and interlink them with bioinformatics, machine learning and simulation models.

I’m a PhD candidate at CoSy.Bio since April 2021 after finishing my M.Sc. Computer Science at TUM. Before, I gained some experience with ligand binding site prediction using CNNs and Class Activation maps at Rostlab and with single cell analysis in human T-cell immunology at Zielinski Lab. At the Chair of Experimental Bioinformatics at TUM I worked on exon-specific differences in microRNA regulation due to alternative splicing for my Master’s thesis. Currently I'm excited to research the application of deep learning methods for extracting splice junctions from RNAseq data with low sequencing depth.

Marius graduated from WHU with a B.S. in Business Administration and from Harbour.Space University with an MBA and M.E. in Data Science. Prior to working on bringing the federated learning technology from academic usage into the market, Marius built up his own startup in preventive health, which was then sold to BEAT81.

 
I am a PhD student at the Institute for Computational Systems Biology at the University of Hamburg. I received a Bachelor's degree in Bioinformatics at the Goethe University in 2018 in Frankfurt, followed by a Master's degree in Bioinformatics at the TUM and LMU in Munich in 2021. I finished my Master's thesis by creating CADDIE, a web application for drug-repurposing in cancer. In 2019/20, I spent one year at the University of Helsinki. During my studies, I worked in different tech startups doing software development and engineering.
My research interests revolve around network-based drug repurposing as well as different approaches to in silico biomarker identification, developing tools like Drugst.One (https://drugst.one/), UnPaSt (https://apps.cosy.bio/unpast/) and the Epistasis Disease Atlas (https://epistasis-disease-atlas.com/home). 

I am a Ph.D. candidate at CoSy.Bio since January 2022. I am graduated from IUST with BS in Computer Engineering and M.Sc. in Artificial Intelligence. I have worked for more than 5 years in tech companies (such as Snapp! , TSCTMC, etc.) as a Data Scientist. At UHH I am part of the EU Horizon2020 FeatureCloud project. Currently, I am working on federated learning and Medical Image Analysis using Deep Learning. Also, I am interested in Blockchains and ‘AI, Philosophy, and Science’. 

I've been pursuing my PhD at CoSy.Bio since October 2021. My main research focus involves examining the connection between the gut microbiome and colorectal cancer, with a particular emphasis on exploring the potential applications of federated learning in this domain. Furthermore, I'm an active member of the FeatureCloud core development team, where I'm involved in implementing a federated database and overseeing various sysops tasks. While my expertise lies in Federated Learning and Random Forests, I have a deep interest in all aspects of data science!

I'm a master's student at the University of Maastricht, studying Drug Development and Neurohealth. In January 2023 I will be returning to Cosy.Bio to work on my master's thesis under the supervision of Dr. Olga Tsoy and Lena Hackl. I will be looking at tissue-specific andbloodbased biomarkers in cardiomyopathies. In 2021/2022, I first joined CoSy.Bio to work on the thesis for my MSc degree in Systems Biology (Maastricht University), under the supervision of Dr. Olga Zolotareva, working towards a federated implementation of a DNA methylation microarray data analysis workflow. Before this, I obtained a BSc (Hons) degree in Forensic Science at Anglia Ruskin University.

Starting in September 2022, I am joining CoSy.Bio as a doctoral student. I received my BS and MS from the Indian Institute of Science Education and Research (IISER) – Pune. My background is in Life Sciences and Data Sciences. During my MS thesis, I worked on Genomic Data Enhancement using Deep Learning with Dr. Xinghua Shi (Temple University, PA). My research interest encompasses the interdisciplinary areas of Biology and Machine Learning. 

I am currently enrolled in the Bioinformatics bachelor's program at TUM / LMU. I am set to join the CoSy.Bio team as a HiWi in March, where I will be working on the NeDRex project.

I currently serve as a science communicator and am entrusted with overseeing the social media presence at CoSy.Bio. My journey led me from Munich to Hamburg in 2021, where I started studying Biology at the University of Hamburg. Next year, I will be writing my Bachelor's thesis, possibly within the field of bioinformatics, because it truly fascinates me.

I am a master's student in bioinformatics at the Technical University of Munich (TUM) and Ludwig Maximilian University of Munich (LMU). For my BSc thesis I evaluated domain-domain interaction prediction methods and used the PPIDM method to infer new interactions. I will join the CoSy.Bio team from January 2024 as a HIWI and will be working to update DIGGER and NEASE, with a focus on making the tools easily available online.

I joined CoSy.Bio as a research assistant in January 2022, supporting the SyMBoD project, while completing my Master's in Bioinformatics at the TUM and LMU in Munich. My work focused on bone proteomics data analysis and a systematic review and meta-analysis of proteomics bone biomarkers for improved scaffold design. In November 2022, I began my Master's thesis, evaluating normalization approaches for protein quantification data and developing the PRONE R package and Shiny app.  
 
Currently, I’m a PhD Student in the DyHealthNet project in the DaiSyBio group of Prof. Dr. Markus List at TUM. Here, I am working in the development of a platform for dynamically exploring cohort-based data studies through multi-level network medicine. Simultaneously, I am still finalizing my work with CoSy.Bio.

I'm currently a bachelor's student in Computer Science at the University of Hamburg (UHH). I started working at CoSy.Bio in July 2024 as a HiWi, specifically as a system administrator. Originally from Freiburg, I relocated to the picturesque city of Hamburg for my studies.

I am currently a master’s student in Intelligent Adaptive Systems at the University of Hamburg. Before moving to Hamburg, I completed my Bachelor’s in Electrical and Computer Engineering in Bremen, where I gained some research experience in joint source-channel coding and signal classification.
In Fall 2024, I will join the CoSy.Bio team as a HiWi, where I will work on developing a protein language model that integrates secondary structure information.

Prof. Vasco Azevedo, DVM, M.Sc, PhD, FESC is a visiting professor in our laboratory. He holds a full professorship position at the Federal University of Minas Gerais in Belo Horizonte, Brazil. Prof. Azevedo is a pioneer of genetics of lactic acid bacteria and corynebacterium pseudotuberculosis in Brazil. He published >240 papers in bacterial genetics, functional genomics, the development of new vaccines against and diagnostics for infectious diseases, as well as on the bioinformatics analyses of transcriptomics and proteomics data sets. He is associate editor of Genetics and Molecular Research, and member of the editorial boards of the Open Veterinary Science Journal and the International Journal of Microbiology.