Background

Originally trained in mathematics and philosophy, I initially did PhD and postdoc within logic/good-old-fashion-AI, but then left academia to become a data scientist in industry. After 4 years in industry, I returned to academia as assistant professor at Roskilde University. In addition to a few projects applying data and machine learning to various applied problems, I am also doing research on ethical and societal aspect of data science and AI, as well as philosophy of science aspects of data science and AI. Finally, I am also interested in social network analysis and information dynamics on social media, such as polarization and echo chambers.

Motivation

I hope to support young aspiring data scientists especially in their choice between academia and industry, as I have tried both. Moreover, I hope to expand my network within data science in Denmark across academia and industry.

Skills, expertise, and interests

• data science
• data analytics
• data visualisation
• data mining
• big data
• machine learning
• deep learning
• artificial intelligence
• natural language processing (NLP)
• causality and explainability
• computational science
• network science
• social (data) science
• career planning or change
• work-life balance
• PhD advice
• teamwork

Background

I am a last year PhD student at Aalborg University. I have been studying machine learning and AI both on my free time and as a part of my research. I have also supervised several student projects regarding theoretical and practical aspects of ML/DS. Seeing how theoretical constructs are translated into actual working software is something in am strongly interested in. My research focuses on finding methods to reduce dynamical models. Before, I studied theoretical mathematics and engineering. So I would be happy to discuss either the theory or engineering applications of AI.

Motivation

My main motivation is to share what I have learned with younger researchers/aspiring data scientists. I know the field can be intimidating at parts but I can ensure it is rewarding. Moreover, I had an awesome experience as a mentee during the last edition of the program. Finally, one of the best exercises is to answer questions from people that are new to the field. It is satisfying to find new ways to understand concepts and share them with others.

Skills, expertise, and interests

• artificial intelligence
• deep learning
• machine learning
• data science
• MLOps
• statistics and mathematics
• PhD advice
• time series analysis
• data mining
• software engineering
• work-life balance
• time management
• high-performance computing
• mathematical optimisation
• academic writing skills
• bioinformatics
• engineering
• version control

Background

As the Chief Data Scientist and VP at Ønskeskyen, I spearhead the organization’s data and AI strategy, fostering innovation and driving adoption across all departments. With a robust background from VELUX, where I led data science and AI for smart home technologies, and extensive experience at GRUNDFOS in machine learning and AI solutions for industrial applications, my expertise spans data architecture, generative AI, and IoT systems. I am passionate about leveraging data to solve critical business problems and unlock new opportunities.

Motivation

Currently, as the Chief Data Scientist and VP at Ønskeskyen, I drive the organization’s data and AI strategy, fostering innovation and cross-functional collaboration. My role involves not only strategic oversight but also hands-on leadership in developing our data and AI talent pool. I am passionate about guiding teams to leverage data-driven insights and advanced AI techniques to solve critical business challenges and unlock new opportunities. Previously, as the Lead Specialist in Data Science at VELUX, I spearheaded the development of smart home technologies, integrating AI solutions to enhance living environments. My experience at VELUX involved leading agile data engineering, AI architecture, and DevOps capabilities, with a focus on generative AI and IoT systems. This role required me to build scalable data foundations, develop data governance frameworks, and innovate with algorithms for smart appliances, all while fostering a collaborative and innovative team culture. My tenure at GRUNDFOS further solidified my expertise, where I applied advanced machine learning, deep learning, and reinforcement learning techniques to solve industrial problems across sales, marketing, supply chain, and intelligent water solutions. This role allowed me to dive deep into business intelligence, recommendation systems, and demand forecasting, providing me with a comprehensive understanding of the practical applications of AI in various business domains. Throughout my career, I have been driven by a commitment to continuous learning and sharing knowledge. I believe that mentoring is a powerful way to inspire and develop the next generation of data scientists. My goal as a mentor would be to provide strategic guidance, share practical insights, and cultivate a growth mindset among mentees, empowering them to tackle complex problems with confidence and creativity.

Skills, expertise, and interests

• data science
• machine learning
• deep learning
• artificial intelligence
• statistical and data modelling
• MLOps
• career planning or change
• big data
• data visualisation
• problem solving
• statistics and mathematics
• time series analysis
• computer vision
• cloud computing
• project management
• leadership
• work-life balance
• business innovation
• economics, finance, and business
• strategy
• DevOps
• end-to-end implementation

Background

I’m a postdoctoral researcher specializing in machine learning, with a focus on clinical and genetic data. I hold a PhD in biomedical science and engineering from Aalborg University. My research experience includes developing machine learning models for binary classification, survival analysis, and regression, applied to various data types, including tabular data and biosignals. Additionally, I have mentored professionals such as medical doctors and bioinformaticians, as well as students from diverse fields.

Motivation

I’m eager to join the mentoring program to support upcoming data scientists and researchers in understanding the field, its opportunities, and challenges. I also aim to expand my network and exchange new ideas. Given the ubiquity of ML/AI, finding the right path to learn about it is crucial for researchers from diverse backgrounds.

Skills, expertise, and interests

• data science
• machine learning
• artificial intelligence
• data analytics
• statistical and data modelling
• data visualisation
• problem solving
• statistics and mathematics
• causality and explainability
• consulting
• time series analysis
• data mining
• computational science
• high-performance computing
• health and medical science
• bioinformatics
• academic writing skills
• engineering
• version control
• PhD advice

Background

I am an assistant professor at Aalborg University working in the intersection of machine learning, and graph theory. My academic journey began with a Bachelor’s degree in Mathematics from Bogazici University, followed by a Master’s degree at the same university. I obtained my Ph.D. degree from Paris-Saclay University, and during my doctoral studies, I was interested in the representation learning methods for predictive graph-structured data and published several papers in high-impact journals and conferences. At Aalborg University, I have been working on the metagenomics binning problem and on the integration of heterogeneous environmental factors with bacterial genome data. I also teach a course including various topics of machine learning and data science, and I supervise both undergraduate and graduate students.

Motivation

I would like to join the DDSA Mentoring Program as a mentor because I believe in the value of guidance and knowledge sharing. I am passionate about helping young and aspiring data scientists achieve their personal and professional growth. Mentoring not only benefits the mentees but also offers me the opportunity to grow. Engaging with mentees brings fresh perspectives, encourages the exchange of ideas, and helps expand my professional network both within and beyond the academic community.

Skills, expertise, and interests

• data science
• machine learning
• artificial intelligence
• statistical and data modelling
• bioinformatics
• network science

Background

I am an assistant professor in energy with a profound commitment to addressing climate change through the lens of AI. With extensive experience at prestigious institutions like IIT, NUS, MIT, and University of Edinburgh, my research focuses on developing energy-efficient algorithms to meet the soaring computing demands of our energy systems, while also exploring the transformative potential of neuromorphic computing in enhancing the security and reliability of critical infrastructure. Passionate about education and innovation, my vision is to drive sustainable solutions with significant contribution to science for a greener future.

Motivation

Excited to embark on mentoring in neuromorphic computing. It’s a cutting-edge field pushing the boundaries of conventional computing. With its potential to revolutionize AI and computing, raising awareness and providing training is crucial. Joining as a mentor allows me to share insights, nurture young talent, and contribute to shaping the future of computing architecture in Denmark.

Skills, expertise, and interests

• machine learning
• deep learning
• artificial intelligence
• computational science
• end-to-end implementation
• digitalisation
• neuromorphic computing

Background

I’m a geographer with passion for geospatial data and the interactions between data, space, people and environment. I did my education in Geography and Geoinformatics, whereI first specialized in urban planning and more recently in geoinformatics and geospatial data, where I was able to publish some work during my studies. During my work experience, I’ve been able to work on many different projects, under a large diversity of themes, which I think is one of the coolest parts of working with geospatial data. Besides the processing and manipulation of data, my daily work is focused on the analysis of geospatial data, as well as building systems and workflows that facilitate the production of geospatial solutions. What I am passionate about is the ability to combine both the technology and the analytics framed by different disciplines and geographies, where different sciences can influence the approach to take. As examples, at my current work I’ve been part of mapping historical stonewalls in Denmark using Deep Learning, mapping rural agents for financial inclusion in Ghana, network analysis on local mobility for the future Light Rail train in Copenhagen, or mapping invasive species using satellite imagery and machine learning in Denmark.

Motivation

At my work I’ve had the opportunity to supervise students that did their master thesis or projects at our department. This experience was quite enriching, and also motivates me to apply for the mentorship program. I saw this as an exchange of knowledge and experiences, as well as a way to support aspiring professionals, with the great addition of witnessing their exciting contributions to the field. Furthermore, I believe that this will also be an important contribution for my personal growth and a learning experience, where I also hope to contribute in any way can to the mentees development path.

Skills, expertise, and interests

• machine learning
• deep learning
• data analytics
• data management
• computer vision
• consulting
• image analysis
• image processing
• urban planning
• geospatial data science
• spatial optimizations

Background

I’ve had a special focus on social data science, and am now a data scientist and consultant working with information retrieval, a bit of NLP and demand forecasting. I have experience on the technical side and project management / client relations side.

Motivation

I had a great mentor in the same program who helped me a lot. I’d like to pass it on.

Skills, expertise, and interests

• data science
• machine learning
• artificial intelligence
• data analytics
• consulting
• project management
• social (data) science
• network science
• sustainable transportation
• geospatial data science

Background

I am a political science researcher and educator with a strong interest in social data science methods. I have a PhD from the Centre for Doctoral Training in Digital Civics at Newcastle University, and most recently I have worked as a research associate at the Technical University of Munich’s Hochshule für Politik. Among other things, I have developed a masters level course on Computational Methods for political science students, and I have supervised many masters theses that utilised social data science methods. My primary research interests revolve around the intersection of digital technologies and democracy. In particular, I do research on political participation, democratic innovations, and civic participation with an emphasis on the role of digital media in this context.

Motivation

I decided to join the DDSA mentoring programme because I have recently relocated to the Copenhagen area and would like to build connections with people here, who have an interest in social data science. One of the best parts of my job as a university researcher has been to supervise and teach talented students. I enjoy seeing the academic interests of my students develop and find great pleasure in being able to contribute to their career ambitions. So I am very interested in sharing my personal experiences and getting to know any mentees with an interest in social data science, especially if they are also interested in politics and democracy.

Skills, expertise, and interests

• PhD advice
• natural language processing (NLP)
• career planning or change
• data analytics
• statistical and data modelling
• data mining
• social (data) science
• text analysis
• academic writing skills

Background

With a PhD in ML and 12+ years of experience in the industry, I have developed and delivered many ML solution to various business. It’s all around taking ML research (eg. papers and open-source code) and apply to a real-world problems and ensuring it actually runs in production. In practice I have built recommender systems, textual embeddings, user behaviour models, Bayesian bandits, Bayesian AB-test systems to name a few 🙂

Motivation

I have always been in the industry and enjoyed both supervising and lead young talent within ML and Data Science. This has lead to many skilled professional today both in startups and commercial companies. Thats’ my motivation – to support and help young talent make an impact for themselves and evolve in their career.

Skills, expertise, and interests

• data science
• machine learning
• deep learning
• artificial intelligence
• data analytics
• statistical and data modelling
• natural language processing (NLP)
• data visualisation
• statistics and mathematics
• PhD advice
• big data
• data management
• time series analysis
• data mining
• project management
• cloud computing
• leadership
• computational science
• work-life balance
• time management
• business innovation
• text analysis
• strategy
• teamwork
• end-to-end implementation
• mathematical optimisation
• academic writing skills
• engineering
• digitalisation
• code review
• version control
• software project management

Background

Andreas has 10+ years experience researching and working with AI & data in academia, as a specialist in the biomedical industry and as a consultant. Andreas has a MSc in biomedical engineering and holds a PhD in machine learning and cognitive neuroscience.

Motivation

I’ve been fortunate to have been given some great advice and support from competent people in my career in AI and data. I see the DDSA mentorship program as a good opportunity for me to pay some of it forward.

Skills, expertise, and interests

• data science
• machine learning
• artificial intelligence
• data analytics
• statistical and data modelling
• MLOps
• career planning or change
• big data
• data visualisation
• natural language processing (NLP)
• problem solving
• deep learning
• statistics and mathematics
• data management
• time series analysis
• causality and explainability
• consulting
• project management
• cloud computing
• leadership
• work-life balance
• computational science
• time management
• mental health and well-being
• health and medical science
• end-to-end implementation
• life science
• forming sustainable habits

Background

I am a passionate Data Scientist with over 10 years of experience in building end-to-end Artificial Intelligence products in the Telecom, Healthcare, and Financial Services industries. With robust technical and leadership skills, I have applied AI to various business situations, helping organizations adopt data-driven solutions. Over the past decade, I have applied various machine learning methods such as classification, regression, time series analysis, and clustering, leveraging strong domain knowledge. I have deployed and maintained models in production on both Cloud and on-premise systems. I have collaborated with product managers, stakeholders, and business owners to effectively implement AI products across business units. I have worked with structured, semi-structured, and unstructured data, including near real-time and batch processing of data. I have also mentored Data Scientists and Machine Learning Engineers and helped them in their careers.

Motivation

As a seasoned Data Scientist, my motivation for joining the mentoring program stems from my desire to give back to the data science community, my thirst for continuous learning, and my enthusiasm for connecting with professionals from diverse backgrounds. I am deeply passionate about supporting young and aspiring data scientists. I believe that the field of data science is vast and constantly evolving, making it challenging for newcomers to navigate. By sharing my experiences and insights, I hope to provide guidance and support to those who are just embarking on their journey in this field. While I aim to impart knowledge, I also look forward to learning from the fresh perspectives and innovative ideas that mentees often bring to the table. This continuous learning process is what keeps me motivated and helps me stay abreast of the latest trends and technologies in data science. I am excited about the potential impact I can make and eagerly look forward to the journey ahead.

Skills, expertise, and interests

• data science
• machine learning
• deep learning
• artificial intelligence
• statistical and data modelling
• data analytics
• MLOps
• big data
• data visualisation
• natural language processing (NLP)
• problem solving
• statistics and mathematics
• data management
• causality and explainability
• time series analysis
• data mining
• computer vision
• cloud computing
• leadership
• high-performance computing
• engineering
• version control

Background

After studying at geoinformatics at AAU of Copenhagen, I have been a GIS/IT consultant at Atkins where I learned scripting for satellite image processing, web development and software development in python, C#, Java and angular. Later, I joined Metroselskabet as a backend developer where I got involved with BIM and explored scripting and low-code development for data management. Soon I’m joining Ørsted as a solutions architect in the IT department.

Motivation

I’m keen on sharing knowledge and supporting individuals who want to have a career within IT. It can be very chaotic to try and find where to start from. Luckily I’ve had myself good mentoring that helped me find what I want to learn. Therefore I am open to helping others with what I’ve learned in this journey so far.

Skills, expertise, and interests

• data visualisation
• problem solving
• data management
• software engineering
• project management
• strategy
• digitalisation
• geospatial data science
• code review
• software project management
• version control
• big data

Background

I have a background in time series analysis as well as computer vision and in general data science. I have work in defense where data is a sparse resource and in cloud where data was coming in form of 24 hours video surveillance. I have supervised multiple master thesis in the company I have worked in and I am experienced in a team lead role. I am used to help my team both as a more academic both also as MLops and software development with in data science. I have also developed and end to end machine learning platform which is a hybrid between cloud and local setup

Motivation

I join this program as I love to help other and that is part of why I took a PhD. I thrive by having the team lead role where I help others especially as a mentor role. I am focused on details in work but have also been in multiple companies so I can also give career advice and where to focus depending of what a person wants to achieve

Skills, expertise, and interests

• data science
• machine learning
• deep learning
• artificial intelligence
• data analytics
• statistical and data modelling
• MLOps
• data visualisation
• problem solving
• time series analysis
• computer vision
• image analysis
• teamwork
• image processing
• data mining

Background

I have my bachelor’s degree in Robotics, from which I transitioned to Data Science during my masters, focusing on specifically computer vision and MLOps. I had to luck to work throughout my studies and rotate through three different R&D departments before landing my full-time position at Novo Nordisk, which allowed me to be exposed to a high variety of projects ranging from academic to technical. Some of the most recent ones were predictive maintenance, fine-grain image analysis, multi-task learning for mobile robotics and productionizing ML solutions within the highly restricted pharmaceutical industry.

Motivation

During my studies and worklife, I have been enjoying great guidance and insights from professors and industry mentors, which shaped my career direction significantly and let me meet a lot of great people. I think it is very relevant to create these relationship for growing one’s network, getting exposed to new topics or perspectives and to be able to pose questions to someone outside one’s peer group. I am still relatively early in my career with only 4 years of industry experience, which means that the experience of transitioning from studies to worklife is still fresh in my memory and I would be happy to pay forward all the guidance I got along the way!

Skills, expertise, and interests

• data science
• machine learning
• deep learning
• artificial intelligence
• MLOps
• computer vision
• cloud computing
• academic writing skills
• code review
• version control

Background

My research interests focus on using genetic, bioinformatic, and epidemiological tools to better understand neurological and psychiatric disease.

Motivation

I love giving advice and support to younger scientists. I was able to get to this position because of support I was given as a young scientist.

Skills, expertise, and interests

• bioinformatics
• big data
• statistics and mathematics
• PhD advice
• health and medical science
• mental health and well-being
• academic writing skills

Background

As a Mechatronic Engineer with a PhD in Automatic Control, I excel in mathematical modeling, nonlinear control, and signal processing. Proficient in Python, MATLAB/Simulink, Julia, and C, I have a strong grasp of machine learning and optimization techniques. Passionate about innovating AI applications to enhance business productivity, my interdisciplinary project experience has refined my skills in algorithm development and large data analysis, enabling me to tackle complex problems effectively.

Motivation

I want to join the mentoring program because I want to share what I’ve learned over the years and help others grow in their careers. I love the idea of inspiring others, especially when it comes to AI and advanced control systems.

Skills, expertise, and interests

• machine learning
• statistics and mathematics
• problem solving
• engineering

Background

Iannis is at the forefront of health data science and digital transformation in medicines, with over two decades of expertise in crafting solutions using AI, Natural Language Processing, Real World Evidence, multimodal data integration, and cloud computing. As the director of data science and engineering at leading pharmaceutical companies like Lundbeck and Novo Nordisk, he has been pivotal in seamlessly introducing AI into business processes and part of the AI in medicines discussion with FDA and EMA. Furthermore, Iannis’ contributions to international consortia, notably OHDSI.org (OMOP) and EHDEN.eu, have been instrumental for groundbreaking advancements in health data standardization, precision medicine, and Software as a Medical Device (SaMD) clinical applications. Iannis holds a PhD in Medicine and has published more than 20 scientific papers. Recently, Iannis joined the board of GENerX.life as the Chief AI Officer (CAIO), supporting pharmaceutical organizations across the world tackle AI and Data Science challenges.

Motivation

It feels great to be part of the awesome DDSA initiative. An opportunity to give back to society, and importantly to interact and learn from the brilliant data scientists that participate in the DDSA mentoring program.

Skills, expertise, and interests

• data science
• machine learning
• deep learning
• artificial intelligence
• MLOps
• career planning or change
• big data
• natural language processing (NLP)
• problem solving
• data management
• PhD advice
• causality and explainability
• data mining
• software engineering
• project management
• cloud computing
• leadership
• work-life balance
• time management
• strategy
• health and medical science
• teamwork
• DevOps
• mental health and well-being
• end-to-end implementation
• academic writing skills
• bioinformatics
• pharmaceutics
• life science
• digitalisation
• entrepreneurship and startups
• code review
• version control
• forming sustainable habits
• software project management