Best Reviewer Award from KDD 2024 and my reflections on the conference

From August 25–29, I attended and presented at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024) in the vibrant city of Barcelona, Spain. The conference was held at the stunning Centre de Convencions Internacional de Barcelona, bringing together top minds in data science, machine learning, and AI research. Here are a few highlights from my week in the Catalan capital.

Best Reviewer Award

I was honored to receive a Best Reviewer Award, an unexpected but deeply gratifying recognition from the KDD community. Peer review is crucial to maintaining the conference’s high standards, and I’m grateful to have contributed to that process.

Mentoring at the Undergraduate Consortium

One of my most rewarding experiences was serving as a mentor at the Undergraduate Consortium. The Day 1 Undergraduate Consortium Social Event provided a friendly setting for sharing advice, discussing research ideas, and learning from one another’s perspectives. Meeting so many bright and motivated undergraduates confirmed my belief that the future of data science is in good hands.

Main Track Paper Presentations

I had the privilege of presenting two main track papers at this year’s conference – both as oral presentations and posters. These projects are the result of extensive collaboration with my fantastic team and our partners. Seeing attendees’ enthusiasm, questions, and feedback was a major highlight. It was a true delight to engage in spirited conversations about the work, its real-world applications, and possible future directions.

The accepted papers are:

• Senane Z, Cao L, Buchner VL, Tashiro Y, You L, Herman PA, Nordahl M, Tu R, Von Ehrenheim V. Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask.
• Cao L, von Ehrenheim V, Granroth-Wilding M, Anselmo Stahl R, McCornack A, Catovic A, Cavalcanti Rocha DD. CompanyKG2: A Large-Scale Heterogeneous Graph for Company Similarity Quantification.

Workshop Paper Presentation

Drew McCornack from our team represented EQT Group Motherbrain during the Workshop on Machine Learning in Finance (MLF), presenting our collaborative paper on the topic of sourcing investment targets for Venture and Growth Capital using multivariate time series Transformer. We later had the opportunity to publish an extended version with ICANN (International Conference on Artificial Neural Networks) 2024, further broadening the discussion around applying deep learning for venture and growth capital investment.

• Cao L, Halvardsson G, McCornack A, von Ehrenheim V, Herman P. Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems.

Team Moments and Networking

Outside of the formal sessions, I greatly enjoyed connecting with colleagues and fellow researchers. Special shout-out to Zineb, Drew, and Dhiana for making this KDD an unforgettable experience – your insights and camaraderie are invaluable.

In Summary

SIGKDD 2024 demonstrated once again the importance of collaboration and knowledge-sharing in the data science community. From receiving the Best Reviewer Award to mentoring future data scientists and sharing our research findings, every moment in Barcelona was filled with inspiration. I look forward to building upon these experiences, continuing to explore cutting-edge AI techniques, and hopefully seeing many of you at future conferences.