Background

As professor at the Aalborg University Business School, I lead the Data Science research at the AI:Growth lab, an am the Programme Co-Director of the M.Sc. program in Business Data Science. My research is dedicated to the development and application of data-driven methods to map and forecast technological change in order to understand its causes and consequences for economies and societies. I am actively engaged in initiatives to educate (social science) students & researchers, professionals, and policymakers in understanding, evaluating, and applying modern Data Science and Artificial Intelligence methods for data-driven decision making. My team also develops enterprise and policy software solutions for decision-centric STI intelligence and technology mapping.

Motivation

I am looking forward to sharing my experience in data science and machine learning, technology analysis, and broadly computational social science in a less formal context than traditional PhD supervision. I am happy for the opportunity to guide and support aspiring social data scientist, and helping them navigate not the dynamic technology landscape, but also potential career paths, research and professional develppmenty.

Skills, expertise, and interests

• data science
• data analytics
• data visualisation
• data mining
• big data
• time series analysis
• text analysis
• statistical and data modelling
• machine learning
• deep learning
• natural language processing (NLP)
• causality and explainability
• computational science
• complex systems and chaos
• statistics and mathematics
• network science
• social (data) science
• PhD advice

Programming languages and software

• Python
• R
• SQL

Background

I have more than 15 years in data analysis/data science in a university administration setting following graduate training to the PhD level in the social sciences with a focus on education policy with a specific focus in educational access and outcomes. My main areas of focus and strength are in data sourcing, exploratory data analysis, data visualization, and predictive modeling. At UC Berkeley I worked in the Undergraduate Admissions office and at the Haas School of Business. I have also led data teams. I mainly use r for all stages of data work, but have used Excel, SAS and SQL.

Motivation

With more than 15 years as a professional data analyst/data scientist and educator I believe I can be a good source of information for newer professionals, and to return the mentorship I received early in my career. I also hope to hone my mentoring skills and expand my network in Denmark, having moved back to Copenhagen in December 2022. At the moment my job is not data science related but I do plan on getting back to data work when my temporary contract is finished.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Data management
• Statistical and data modelling
• Social (data) science
• Career planning or change
• Work-life balance
• PhD advice
• Leadership
• Teamwork

Programming languages and software

• R
• SQL
• Excel
• SAS

Background

Originally from Nagpur, India, I am currently based in Abu Dhabi, UAE, where I work as a Senior Researcher in the Renewable and Sustainable Energy Research Center at Technology Innoation Institute (TII), United Arab Emirates; and Assistant Professor in the Center for Quantitative Genetics and Genomics (QGG) at Aarhus University, Denmark.

I was educated and trained in India and Denmark in engineering, data science, renewable energy, and computer science. At the crossroads of these fields, my research interests lie within the general area of theoretical and applied data science, time series analysis view on industrial applications such as in digital twins, artificial intelligence, bioinformatics, statistical software development, visualization techniques, and predictive analysis; and on exploring the scope of automation of the machine learning and data science methodologies.

Motivation

I’m excited to join the mentoring program as I strongly believe in giving back to the data science community. My main motivation is to guide young data scientists through the industry’s complexities, just as I was guided when starting my career. Additionally, I look forward to the personal growth and enhanced leadership skills that come with mentoring. Lastly, I’m eager to broaden my professional network and foster enriching relationships within this vibrant field.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Data mining
• Time series analysis
• Machine learning
• Deep learning
• Artificial intelligence
• Engineering
• PhD advice

Programming languages and software

• Python
• R

Background

Hi! I am Shabab, and I am a versatile individual with over 5 years of experience working in the intersection of technology and business. I have a background in Computer Science and in my career so far, I have developed multiple innovative products and solutions utilizing the newest technologies. I have worked in top-tier companies both in the industry and also in consulting – this has enabled me to wear multiple hats and gain valuable skills in several different vertical streams and industries.

I take immense pride in being able to speak both Python and Powerpoint at a native level. I enjoy writing code and solving complex problems utilizing both statistical and deep learning techniques, but what I enjoy more and prioritize is creating stories and visually appealing slides that clearly communicate how the code I write translates to business value.

To summarize, I have a very diverse background and I am looking forward to sharing my experiences with those interested.

Motivation

In my 5 years of professional experience, I have tried several different things, and in those 5 years, I have failed more times than I have succeeded. But that is also what I have enjoyed the most because each failure presented me with the opportunity to learn something new – and this is what defines me as a person. I always thrive to try new things and learn new things. In connection to that, in recent years, I have felt a strong need to share my experiences, or more so, my failures, with a broader audience. I would like to impact future technology enthusiasts by sharing my experiences with them and hoping it helps them to repeat my mistakes, but rather make new mistakes. In addition to that, I have worked as a mentor for a few years now (I have also been a part of the previous round here at DDSA) and I thoroughly enjoy this. I feel I am making an impact and I am able to help people – I would very much like to continue doing it.

Skills, expertise, and interests

• data science
• data analytics
• big data
• time series analysis
• text analysis
• statistical and data modelling
• machine learning
• artificial intelligence
• natural language processing (NLP)
• MLOps
• causality and explainability
• economics, finance, and business
• entrepreneurship and startups
• consulting
• engineering
• software engineering
• career planning or change
• work-life balance
• leadership

Programming languages and software

• Python
• R
• SQL
• Java
• Scala
• JavaScript
• C++/C
• C#
• PHP
• Shell Scripting (e.g., Bash)
• Excel
• Apache Hadoop
• Apache Spark

Background

Chen Li is an Assistant Professor in the Department of Materials and Production at Aalborg University. He is certified by NVIDIA as University Ambassador. Chen Li’s research mainly focuses on Natural Language Processing (NLP), Data Analysis and Deep Learning. He has years of experience in dialogue systems, entity recognition, and text mining. He has a deep understanding of SOTA neural network models, particularly Transformers like BERT and GPT, and their applications in NLP. He has successfully applied NLP techniques in multimodal contexts, specifically in Conversational AI and Text Mining.

He successfully takes NLP projects from concept to production, particularly in the manufacturing and business domains. He collaborated closely with cross-functional teams (e.g., robotics engineers, cognitive scientists, business experts) to understand unique requirements and develop tailored NLP solutions.

Motivation

With a deep understanding of SOTA neural network models, particularly Transformers like BERT and GPT, I have successfully applied NLP techniques in multimodal contexts, such as text mining, sentiment analysis, and conversational AI. Taking NLP projects from concept to production in manufacturing and business domains, I collaborate closely with cross-functional teams, tailoring NLP solutions to unique requirements. My proficiency in deploying NLP models at scale ensures seamless integration into real-world applications, driving innovation and improving research outcomes. I am enthusiastic about contributing to the mentoring community by sharing my expertise and experiences with fellow mentees.

Skills, expertise, and interests

• Data science
• Data analytics
• Time series analysis
• Text analysis
• Machine learning
• Deep learning
• Artificial intelligence
• Natural language processing (NLP)

Programming languages and software

• Python
• SQL
• JavaScript

Background

I studied Computer Science as an Undergraduate and PhD student in England before moving to Denmark to become an assistant professor. Now, I explore research within Data Science and Information Science, within areas including decision support systems and explainable AI, personalisation and recommender systems, and data wrangling. I explore such topics from their technical perspectives along with consideration of their humanistic impact within society, and how this may in turn feedback to, and interplay with, technical concerns. I envisage potential to provide mentorship discourse within areas including, pursuing a PhD, consideration of data science within the Humanities, Personalisation & Explainable AI, Decision Support Systems, studying/working abroad, and Programming in R.

Motivation

My motivations for joining the program include looking to support emerging data scientists by sharing my data science and academic experiences. At the same time, I anticipate opportunities for having my own perspectives and perceptions expanded, contributing to a joint continuous learning journey. I’m motivated to give back to the community whilst also having an opportunity to hopefully develop my supervisory and mentoring skills. Additionally, as someone who moved to Denmark only a few years ago I’m keen to learn more about those perusing data science endeavours within the county.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Big data
• Data management
• Artificial intelligence
• Causality and explainability
• Software engineering
• Social (data) science
• PhD advice

Programming languages and software

• R

Background

I am originally from India from where I did my Masters in Bioinformatics. In Denmark, I came to purse my Ph.D. and afterwards have been working at BRIC and Rigshospitalet as Senior Scientist. My expertise is in analysis of data (genomic) arising from Patients and Mice to understand biological basis of diseases such as cancer. I can offer my expertise in data analysis and visualisation using R and my experiences in pursuing Ph.D in Denmark.

Motivation

My motivation is to share my enthusiasm of data analysis with aspiring data scientists and share my experiences in how this field can help in treating diseases such as cancer. Along the way, I also think I can also learn from the aspirations and experiences of the young data scientists and how they think this field can help in solving my of the current issues that our society faces, including climate change, industry productivity, food security and human health.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Time series analysis
• Bioinformatics
• Life science
• PhD advice

Programming languages and software

• R
• Shell Scripting (e.g., Bash)

Background

Machine learning, Survival analysis, Explainable AI

Motivation

I want to share my successes and failures with younger data scientists. I would like to contribute to the growth of data science in Denmark.

Skills, expertise, and interests

• Data science
• Machine learning
• Causality and explainability
• Health and medical science
• PhD advice

Programming languages and software

• Python
• R

Background

Before arriving in my current fantasticly inspiring position and enjoyed 12 years within Novo Nordisk, where I started as project manager and grew into team leader, manager and director. I worked in the fields of clinical data standards, data governance, data management and innovation collaborating a lot with both biostatistics and regulatory authorities, and have thereby grown extensive experience in the pharmaceutical data value chain,
The broader area I belonged to of 2000 people was around 2 years ago renamed to Data Science.

I am an experienced leader, having led both leaders and employees, made large re-organisations, driven councils and projects, built up organisations both in DK and India, and represented Novo Nordisk on different large industry associations/consortia.

In my current job I work with the academic data science environments at all 8 eight Danish universities, and aim to connect the national data science community across academia, private and public sectors.

Motivation

I wish to offer sparring based on my career experiences and thereby support younger professionals with some of the dilemmas career development poses to us all.
And I also very much hope for some reverse-mentoring, in the sense that I believe I can learn a lot from younger professionals – I hope to learn and grow my perspectives through the sparring sessions.

I haven’t coded in 15 years, I can not offer sparring on concrete technical topics – If you would like that, then pick some of the great other mentors lined up here 🙂

Skills, expertise, and interests

• Career planning or change
• Work-life balance
• Leadership
• Teamwork

Background

I used to be a scientist specializing in experimental research on protein folding, with a physics background and a master’s degree in biophysics. I spent five years at Novo Nordisk researching proteins before realizing that my true passion lay in data science. Approximately 18 months ago, I made the switch to data science because I found the data analysis and handling aspects of my work to be more intriguing than the wet lab work involved in biology research. These days, I am a data scientist at NTT Data, where I focus mainly on machine learning and forecasting tasks, as well as promoting the adoption of AI in the industry. Additionally, I write about my work and interests and strive to educate others within and beyond the field.

Motivation

I have always had a passion for teaching and sharing knowledge. I find that by breaking down complex topics and explaining them to others, I gain a better understanding of the material myself. Whether I’m teaching advanced concepts to management or simplifying ideas for younger students, I appreciate the opportunity to engage with my field in a deeper way.

Teaching also allows me to meet people with diverse backgrounds and job profiles. I enjoy learning about their perspectives and how they approach problems. These interactions have broadened my horizons and enriched my understanding of the subjects I teach.

Skills, expertise, and interests

• data science
• data analytics
• data visualisation
• data mining
• big data
• time series analysis
• statistical and data modelling
• machine learning
• deep learning
• artificial intelligence
• MLOps
• statistics and mathematics
• health and medical science
• life science

Programming languages and software

• Python
• SQL
• Rust
• PowerBI

Background

Sneha Das is a tenure-track assistant professor with the section for Statistics and Data Analysis (STATS) at the Department of Applied Mathematics and Computer Science (Compute), Technical University of Denmark (DTU). She received her PhD from Aalto University, Finland in 2021 within Speech and Language Technology, her MSc degree in Communication and Multimedia Engineering from Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany in 2016 and her Bachelor degree in Electronics and Communication Engineering in 2013 (BMS Institute of Technology, India). Sneha was born in Kolkata, India.
She works on multi-sensory data modelling with shared perspective from statistics, low-resource machine-learning and signal processing for applications in mental health and well-being. She is specifically interested in speech and multi-modal technology founded on equity and inclusiveness, whereby her current research focuses on technology for children and atypical populations.

Motivation

I was part of the mentoring program in Spring 2023. I would like to continue mentoring for fall 2023 as well.

Skills, expertise, and interests

• Data science
• Data visualisation
• Time series analysis
• Statistical and data modelling
• Machine learning
• Deep learning
• Artificial intelligence
• Natural language processing (NLP)
• Speech processing
• Audio processing
• Computational science
• Statistics and mathematics
• PhD advice

Programming languages and software

• Python
• R
• MATLAB

Background

I am Senior Data Scientist at Amsterdam Data Collective, a data science agency dedicated to leveraging the power of data for a better future. My role is multifaceted and ranges from coding to architecture to project management but it all revolves around using data to drive decision making.

Prior to this I have worked in data science in the financial industry, where my team and I developed full stack data science products to internal colleagues and directly to 1+ million customers.

I have an MSc. in mathematical modelling and computation from DTU along with a BSc. in mathematics and technology.

Motivation

I want to give back to the data science community and support aspiring data scientists in their professionel journeys. Having been part of the pilot mentor program, I experienced first-hand the positive impact of mentorship on the careers and personal development of mentees, which reinforced my desire to continue in this role.

In my career, I’ve navigated the challenges of being a new graduate and transitioning roles within the data science field. I believe these experiences have equipped me with valuable insights that I can share with mentees, especially those at the beginning of their careers or considering a career change. Whether it’s technical sparring, problem-solving with data science, or understanding end-to-end data science processes, I am eager to share my knowledge and experiences.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Statistical and data modelling
• Machine learning
• Natural language processing (NLP)
• MLOps
• Statistics and mathematics
• Consulting
• Engineering
• Career planning or change
• Work-life balance
• Teamwork
• DevOps
• End-to-end implementation
• Problem solving

Programming languages and software

• Python
• R
• SQL

Background

Mathematical modelling, MRI physics, image analysis, brain, synchrotron imaging, computer science., health science.
I am a group leader, experiences in supervision at all levels and to handle stress, carrier doubts, strategic considerations, general advices etc.

Motivation

I would like to help early state people making them moving forward in their carrier – if they want themself 🙂
I can provide them tools and guidance. I prefer having my focus on the development of the person and not solving practical scientific issues like programming and experimental designs – unless the mentee really needed my skills for this.

Skills, expertise, and interests

• image analysis
• machine learning
• image processing
• consulting
• health and medical science
• life science
• work-life balance
• PhD advice
• leadership
• teamwork

Background

I am the Head og Data Science and Data Management Centre of Excellences at Danish Crown, where I have the task of building and extending the reach of these two teams within the organisation. Both teams are key in Danish Crowns ambitions to become more data-driven. I joined Danish Crown almost two years ago after having spent ten years in the UK both working and studying. I worked at a small Data Science consultancy both as a consultant and as a technical director, and thus have experience from technical work, but also winning new business and engaging with clients. I initially moved to the UK to pursue a DPhil in mathematics at the University of Oxford, which I completed in 2015 and have worked in industry ever since. Although my time now is spent more on management and leadership, I still enjoy getting into the technical details. My technical expertises are within forecasting and optimisation.

Motivation

I’d like to help new data scientist get the best start on their career. I have experience from 10 years abroad both studying and working. I have both worked in small companies and large enterprises. I am happy to share my experiences with those who are about to kick-start their career. I have previously been a mentor and the conversations I had with the mentees were always very giving and gave me the opportunity to learn new things myself as well.

Skills, expertise, and interests

• data science
• data analytics
• data visualisation
• data mining
• big data
• data management
• time series analysis
• statistical and data modelling
• machine learning
• MLOps
• cloud computing
• statistics and mathematics
• consulting
• software engineering
• environmental sciences & sustainability
• career planning or change
• work-life balance
• PhD advice
• leadership

Programming languages and software

• Python
• R
• SQL
• PowerBI
• Excel

Background

I have many years experience working in data science and quantitative analyst roles in finance. In recent years I have transitioned into a team lead role of various teams covering machine learning and analytics. I am a Chartered Financial Analyst and hold separate masters degrees in Economics and Bioinformatics. I can help in setting goals, solving problems, finding jobs, and I am happy to make my network available as well if needed. I am a strong believer in the value on ongoing education and believe that right answers can be brought about by an approach of intellectual humility and openness to new ideas, which helps ask the right questions. I am based in Copenhagen.

Motivation

I have contributed as a mentor in three different forums both in Denmark and in the UK. Helping others is a very meaningful activity, for which reason I am looking to return to this forum. I have also benefitted from having a senior mentor in my most recent role, which has helped me tremendously.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Machine learning
• Deep learning
• MLOps
• Bioinformatics
• Economics, finance, and business
• Entrepreneurship and startups
• Leadership

Programming languages and software

• Python
• R
• SQL
• Excel

Background

After about 12 years in corporate setting environment working with software, data and algorithms, I am equipped with the necessary expereince to communicate and convery relevant real world industry challenges to students coming out of studies and how they can controbute and leave their mark in the challenges big companies face.

Motivation

Sharing expereince and knowledge, getting acquainted with latest curriculum within data science from the universities, expanding network, potentially finding great candidates for collboration in projects, talk about potential data science projects, read thesis papers and more 🙂

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Data mining
• Big data
• Data management
• Time series analysis
• Text analysis
• Statistical and data modelling
• Machine learning
• Deep learning
• Artificial intelligence
• Natural language processing (NLP)
• Speech processing
• MLOps
• Cloud computing
• Statistics and mathematics
• Economics, finance, and business
• Engineering
• Software engineering
• Environmental sciences & sustainability
• Career planning or change
• Work-life balance
• Teamwork

Programming languages and software

• Python
• SQL
• PowerBI
• Tableau
• Apache Spark

Background

Currently in the midst of my PhD programme at ITU, at the NERDS group (NEtworks, Data, and Society); working on several interdisciplinary projects in the field of geospatial data science, with a focus on sustainable transportation (mostly data-driven planning of urban bicycle networks). I’ve studied Transcultural Communication, Technical Physics, Environmental Science, and Complexity Science. Before focusing on my academic career, I’ve also worked in many different places (administration, consulting, tourism, education…). I am/was also quite active in several NGOs and grassroots organisations, leaning very much to the left. My current technical focus is all things geospatial data science, in the Python universe.

Motivation

I find it important to offer to others what I would have wished for my younger self: advice, support, cheering on & encouragement, or just a shoulder to (figuratively) cry on about how complicated things can get out there. I’ve participated in several mentoring programmes (both as mentee and as mentor) and I’m passionate about how powerful the outcomes can be, for both sides. I’ve learned to understand and present my rather unconventional (one might say too patchy?) curriculum as a big strength, and would like to share encouragement (and self-marketing hacks) with others who are in similar situations of still looking for the right way forward. Last but not least – I think that I can learn a lot from my mentee(s) and about their life & education situations.

Skills, expertise, and interests

• Data science
• Computational science
• Complex systems and chaos
• Network science
• Environmental sciences & sustainability
• Social (data) science
• Career planning or change
• Work-life balance
• PhD advice
• Complexity science
• Geospatial data science
• Sustainable transportation
• Urban planning
• Mental health and well-being
• Time management
• Transcultural communication
• Academic writing skills

Programming languages and software

• Python

Background

I am a final year PhD student at DTU Compute. My work is focused on meaningful uncertainty quantification for deep generative segmentation models, especially for applications in medical image analysis. I am supervised by Aasa Feragen and Jes Frellsen and funded by the Center for Basic Machine Learning Research in Life Science (MLLS). I am part of the Pioneer Centre for AI in Copenhagen. Previously to my PhD studies, I obtained a B.Sc. and M.Sc. in Mathematics and Management from Ulm University, where I specialized in financial modelling and machine learning. I wrote my thesis on a text mining method for analyzing conversational data. During my studies, I did internships in equity derivative trading and exchange traded funds structuring.

Motivation

In my career so far, I have found it very valuable to speak to people as much as possible, especially before important decisions such as pursuing a PhD or not. While I believe you should always be careful with advice from others who do not bear any of the consequences of your decision, I am convinced that one can nothing but profit from new perspectives. I think this initiative hits the spot and is a great opportunity for both sides to learn. Helping young scientists find their way towards work or a project they will enjoy is time well spent. In my career so far I have found it very valuable to speak to people as much as possible, especially before making important decisions such as pursuing a PhD or not. While I believe you should always be careful with advice from others who do not bear any of the consequences of your decision, I am convinced that one can nothing but profit from new perspectives. I think this initiative hits the spot and is a great opportunity for both sides to learn

Skills, expertise, and interests

• Data science
• Data analytics
• Data mining
• Machine learning
• Deep learning
• Artificial intelligence
• Computer vision
• Statistics and mathematics
• Economics, finance, and business
• PhD advice

Programming languages and software

• Python
• SQL
• Excel
• Shell Scripting (e.g., Bash)

Background

I have a strong background in computer science, software engineering, and computational biology. Throughout my career, I have gained experience in both industry and academia, working in various roles and across different countries. Currently, I hold a leadership position at DTU Biosustain, where I head the data science platform and lead the Multi-omics Network Analytics research group (MoNA).

At MoNA, we leverage graph-based approaches to effectively structure, integrate, analyze, and interpret multi-omics data. Our primary focus is on tackling environmental and human health challenges. Specifically, our research focuses on understanding the mechanisms behind microbial community assembly and adaptation in response to abiotic factors, environmental degradation, and diseases. To accomplish this, we employ a multidisciplinary approach, integrating diverse data modalities such as metaomics and metabolomics data.

Motivation

Throughout my career, I have had the privilege of working in diverse fields and holding various positions in both industry and academia. These experiences have provided me with valuable insights and knowledge that I believe can be of great value to young scientists who are starting their journeys. I have encountered different challenges, collaborated with diverse teams, and navigated different professional environments. Sharing these experiences with aspiring scientists can help them gain a broader perspective and prepare them for the road ahead.

Moreover, my roles in leadership positions have allowed me to develop a good understanding of what effective management requires. Sharing this experience can contribute to the professional development of mentees.

Further, I believe that participating in this program will also be a valuable learning experience for me.

Skills, expertise, and interests

• Data science
• Data analytics
• Data mining
• Big data
• Bioinformatics
• Health and medical science
• Software engineering
• Network science
• Career planning or change
• Leadership

Programming languages and software

• Python
• R

Background

I am Head of Machine Learning at Corti, a scaleup company bringing machine learning to written and spoken healthcare conversations. Prior to that, I worked in data science in the pharmaceutical industry at Novo Nordisk.
My academic background is in bioinformatics and I have obtained Bachelor, Master, and PhD degrees in this interdisciplinary field. I am originally from Germany but have lived and worked in Denmark for the last ~ten years with my family.

Motivation

I have been part of the previous iteration of the mentoring programme – both as a mentor and mentee – and learned a lot in both roles. As a mentor, I would like to share my experience related to career planning, technical leadership especially within data and machine learning, working in small and large companies, transitioning from a PhD to industry, my technical expertise, and more.

Skills, expertise, and interests

• data science
• data visualisation
• text analysis
• machine learning
• deep learning
• artificial intelligence
• natural language processing (NLP)
• speech processing
• MLOps
• bioinformatics
• cloud computing
• entrepreneurship and startups
• health and medical science
• pharmaceutics
• software engineering
• life science
• career planning or change
• work-life balance
• leadership
• teamwork

Programming languages and software

• Python
• R
• SQL

Background

Muniba Talha has been nominated as Top 100 in Nordics within Data Analytics AI and Machine learning. She is a lecturer in Business Economics and IT at Copenhagen School of Design and Technology (KEA) where she teaches Data Science, Machine Learning, Data Visualization, and Big Data along with some courses on Project Management, Digital Strategy, and Digitalization.

Prior to this position, Muniba worked in Project and Team lead positions delivering robust software products and developing agile teams.

Muniba is passionate about empathetic leadership, community building, diversity, and inclusion. She is the founder of Women in Data Science and Machine Learning, a community open to everyone but particularly supporting, educating, and empowering women in this field.

Motivation

I believe mentoring like teaching is a reciprocal journey and it enriches both the mentor and the mentees. In the act of teaching and imparting knowledge, I find myself deepening my own understanding of intricate data science concepts. The dynamic exchange of ideas with my mentees, who bring diverse perspectives and fresh approaches, inspires me to continually broaden my horizons. Besides that, I have a genuine desire to give back to the community.

Through mentoring, I can provide guidance and support to others on their path to success which brings me an indescribable sense of fulfilment. The opportunity to serve as a mentor will enable me to play an active role in shaping the next generation of data scientists, helping them overcome obstacles, and witnessing their remarkable transformations.

Furthermore, participating in the mentoring program opens doors to networking opportunities within the data science community which I value a lot.

Skills, expertise, and interests

• data science
• data analytics
• data visualisation
• big data
• data management
• machine learning
• consulting
• software engineering
• work-life balance
• leadership
• teamwork
• project management
• digitalisation
• business innovation
• strategy

Programming languages and software

• Python
• SQL
• PowerBI
• Excel
• Tableau

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

Programming languages and software

• Python
• R
• Excel

Background

As a consultant in the AI risk unit at EY, I assist financial institutions in mitigating model risk associated with their AI/ML-based models, primarily within the anti-financial crime domain. My role involves conducting technical reviews, performing experiments, and analyzing these models.

Prior to transitioning to the financial industry in 2018, I worked as a computer science researcher, doing a PhD and spending six years as a postdoctoral researcher. During my PhD, I specialized in probabilistic logic programming. As a postdoc, my work revolved around applied data analytics of genetics data, emphasizing high-performance computing, data quality control, imputation, data privacy, and statistical testing.

From 1999 to 2008, I worked as a software developer and cybersecurity consultant in various contexts. I held positions in early-stage startups, SMEs, and multinational corporations, and also operated as an independent consultant in my own company for several years.

Motivation

I have been inspired and guided by a diverse set of thoughtful and kind people throughout my carrier. I would like to pay it forward.

On the other hand, I seek not only to guide and inspire, but also be inspired. I expect mentoring to a two-way street, where you not only impart your expertise but also learn from your mentees and this is a large part of motivation. Explaining concepts, answering questions, and providing guidance forces you to stay up-to-date with the latest trends and advancements in the field of data science.

Finally, I hope that the relationship formed can be open up doors for both you and me, wherever our future carriers might take us.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Data mining
• Big data
• Data management
• Time series analysis
• Text analysis
• Statistical and data modelling
• Machine learning
• Deep learning
• Artificial intelligence
• Natural language processing (NLP)
• Causality and explainability
• Bioinformatics
• Computational science
• High-performance computing
• Statistics and mathematics
• Economics, finance, and business
• Consulting
• Software engineering
• Career planning or change
• Work-life balance
• Teamwork

Programming languages and software

• Python
• R
• SQL
• Java
• Scala
• JavaScript
• C++/C
• Julia
• Ruby
• PHP
• Perl
• Shell Scripting (e.g., Bash)
• Apache Spark

Background

I have a PhD in electrical and electronic engineering, obtained at Aalborg University, where I worked within the Centre for Acoustic Signal Processing Research (CASPR). During my PhD, I successfully collaborated with academic and industrial partners, specifically with Universitat Pompeu Fabra (Spain), Università di Modena e Reggio Emilia (Italy), Oticon (Denmark) and Tencent AI Lab (USA). My dissertation focused on deep-learning-based audio-visual speech enhancement and it was the basis of my postdoctoral research, which I carried on at Oticon and Aalborg University, with the purpose of investigating cutting-edge technologies for multimodal hearing assistive devices. Currently, I am using my skills and expertise within the field of medical image analysis at Novo Nordisk, aiming at helping people with chronic diseases, such as diabetes, obesity and haemophilia.

Motivation

I firmly believe in the power of mentorship and the transformative impact it can have. I am excited to contribute my knowledge, skills, and expertise to support and guide aspiring data scientists on their journey towards success.

One of the key reasons why I am passionate about mentoring is the opportunity to make a positive difference in someone’s life. Mentoring provides a unique platform for me to give back to the community and help others overcome challenges, discover their strengths, and achieve their goals.

Moreover, being a mentor is also an avenue for personal growth and development: mentoring allows me to enhance my leadership/communication skills and expand my professional network.

Skills, expertise, and interests

• data science
• data analytics
• data visualisation
• time series analysis
• image analysis
• machine learning
• deep learning
• artificial intelligence
• computer vision
• speech processing
• image processing
• audio processing
• health and medical science
• pharmaceutics
• PhD advice

Programming languages and software

• Python
• MATLAB

Background

I have been a doctor in computer science since 2014 and am working as a tenure-track assistant professor in DTU. My research focuses mainly on computational methodology, data analytics and visualization, machine learning, artificial intelligence, and digital solutions focus on the application within data-driven technology. I have worked in Malaysia, Iran, and Denmark and have already developed a robust research network. I am actively involved in research services such as organizing conferences and workshops and making a societal impact through competence sharing with researchers, educators, and students in the developing world.

Motivation

Support young and aspiring data scientists, and expand your network.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Data mining
• Time series analysis
• Image analysis
• Deep learning
• Artificial intelligence
• Natural language processing (NLP)
• Bioinformatics
• Computational science
• Software engineering
• PhD advice

Programming languages and software

• Python
• SQL
• PHP

Background

My main research interest lies in the management of graph data, including applying analytics and machine learning tasks. I am interested in studying new methods and algorithms, as well as developing system prototypes and proof of concepts. On the teaching side, I am involved in the Data Science and Machine Learning education at Aalborg University, where I teach Web Data Science, Data Privacy and supervise semester projects.

I hold a PhD in Information Technology from Politecnico di Milano. Before joining Aalborg University, I was a postdoc at the University of Zurich, and a research fellow at the University of Aberdeen. During my PhD, I also spent a summer at IBM Research Ireland as a research intern and a trimester at WU Vienna as a visiting student. Before getting enrolled in the PhD program, I worked for a few years as a consultant and junior researcher at CEFRIEL, a digital innovation centre in Milano.

Motivation

Throughout my career, I have met various mentors that have guided me and contributed to letting me achieve my objectives. I feel extremely lucky for these opportunities. Following my mentors’ example, I aim to help young and aspiring data scientists pursue their goals. I am interested in discussing various aspects of the data scientist career, such as academic career planning and PhD life, as well as digging into more technical aspects.

Skills, expertise, and interests

• Data science
• Data analytics
• Big data
• Data management
• Machine learning
• Artificial intelligence
• Bioinformatics
• Career planning or change
• Work-life balance
• PhD advice

Programming languages and software

• Python
• R
• SQL
• Java

Background

I am currently a PhD student at the University of Copenhagen (Department of Computer Science) and Novo Nordisk A/S (Biotech and Rare Disease), where my project is about using reinforcement learning to control pharmaceutical production. Before coming to Denmark, I completed my master’s degree in AI at the University of Amsterdam and my master’s degree in statistics at Columbia University. Before that, I studied statistics at Jinan University in China.

Motivation

During my journey in AI and data science, I have been benefiting a lot from many friends, colleagues, and mentors, and now with a bit more experience than I used to, I would like to contribute back to the community.

Skills, expertise, and interests

• Data science
• Data analytics
• Machine learning
• Deep learning
• Artificial intelligence
• Statistics and mathematics

Programming languages and software

• Python