Competitions: Beyond the Kaggle Leaderboard

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In this talk, Tatiana, Staff Software Engineer at LinkedIn, shares her journey from academic physics to becoming a Kaggle Master and winning the Sound Demixing Challenge. We explore how to use machine learning competitions as a strategic tool to build a high-impact career and bridge the gap between theory and production.You’ll learn about: * Turning competition code into professional GitHub repos. * Converting results into papers for NIPS and CVPR. * How LLMs are changing the benchmark for AI competitions. * Why hands-on implementation beats passive learning. * Using Topcoder and AI Crowd for research-driven goals. * Practical steps for your very first model submission.Links: * Rise: 3 Practical Steps for Advancing Your Career, Standing Out as a Leader, and Liking Your Life. By Patty Azzarello https://www.porchlightbooks.com/pages/author/Patty_Azzarello-16156396 - awesome book about why doing good is not enough, and what else you need to do to promote your career (same applies to competitions) * AICrowd - https://www.aicrowd.com/challenges * Grand challenges - https://grand-challenge.org/challenges/ * Kaggle competitions - https://www.kaggle.com/competitions * TopCoder challenge SpaceNet 9 - https://www.topcoder.com/challenges/9620f66a-767e-40ac-81d5-5cc61274b186(no current active competitions, but they appear) * Medium blog post with instruction - https://medium.com/data-science/writing-papers-tech-reports-after-kaggle-competitions-ee504fc0c4c1 * Kaggle Solution Write-Up Documentation - https://www.kaggle.com/solution-write-up-documentation * Evaluating Machine Learning Agents on Machine Learning Engineering - https://arxiv.org/abs/2410.07095 * Machine Learning Engineering Agent via Search and Targeted Refinement - https://arxiv.org/html/2506.15692v2 * AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench - chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2507.02554TIMECODES:00:00 Tatiana’s journey from academia to staff software engineer06:01 Machine learning applications in physics and signal processing09:13 Skill development and domain diversification on Kaggle13:35 Agentic AI benchmarks and automated competition entries17:43 Deep technical mastery versus leaderboard gamification23:04 Hands-on implementation and the illusion of learning26:01 Specialized platforms and fair competition environments31:35 Academic publications and research from silver medals35:24 GitHub repositories and engineering portfolio building39:02 Technical marketing via blog posts and LinkedIn43:25 Innovative approaches for academic conference submissions47:21 Research challenges at NIPS and CVPR workshops52:51 Medical imaging platforms and specialized recommendations57:46 First submission strategies for beginners01:00:56 Asynchronous collaboration and competition team dynamicsPerfect for data scientists and engineers looking to transition from academia or build a formal portfolio using Kaggle as a career-advancement tool.Connect with Tatiana: * Linkedin - https://www.linkedin.com/in/tatigabru/

Applied AI 2026 Berlin Conference Interview

The conference highlighted a critical shift in the technology and engineering ecosystem, moving away from passive implementations toward autonomous AI systems, collaborative communities, and robust engineering guardrails. Discussions centered on the practical architecture required to scale AI safely, the evolution of modern developer tools, and the importance of cross-border technical collaboration. Ultimately, the insights underscored that the future of technology relies on blending rigorous infrastructure with human-centric ecosystem growth. Florian Hönicke an expert in engineering infrastructure, explored the operational shifting of cloud services and the challenges of secure temporary access provisioning. He detailed strategies for managing transient credentials for large groups and autonomous agents using automated serverless functions without exposing long-lived access keys. His central thesis argues that true engineering rigor requires deterministic, self-expiring security layers at the container level. Stella Buhalis, a technical community and developer relations leader, addressed the human dynamics fueling open-source ecosystems and community-driven adoption. She emphasized that long-term project viability stems from structured developer onboarding and lower cognitive barriers rather than pure marketing outreach. Her key insight is that building trusted technical communities acts as the ultimate feedback loop for improving developer experience and software reliability. Błażej Nowakowski, a backend systems architect, focused on database migration paradigms and the optimization of high-dimensional vector search at the network edge. He analyzed real-world infrastructure friction points, specifically isolating SQLite database lock conflicts and remote data sync latencies on serverless architectures. He noted that decoupling persistent remote backends from the core runtime is crucial for maintaining low-latency, multi-cloud application performance. Alena Astrakhantseva, a talent strategy and engineering education specialist, outlined the rapid evolution of technical training as the industry shifts from traditional development to autonomous AI flows. She analyzed how continuous testing, real-time monitoring, and structured evaluation frameworks must become core competencies for new developers. Her notable perspective highlights that the next wave of technical talent must be hired for systemic engineering rigor over simple syntax mastery. Zhen Ming Ng (Babypro), an open-source library maintainer and developer, demonstrated automation workflows for package deployment and baseline library compliance. He focused on minimizing framework overhead by substituting heavy, resource-intensive dependencies with lightweight tokenizers and compact client drivers. His core perspective is that library design must prioritize minimalism to remain functional across edge-native runtime environments. Connect with speakers: Florian HönickeCloud Infrastructure & DevOps Engineer Specialisthttps://www.linkedin.com/in/florian-h%C3%B6nicke-b902b6aa [https://www.google.com/search?q=https://www.linkedin.com/in/florian-h%25C3%25B6nicke-b902b6aa] Stella BuhalisDeveloper Relations & Technical Community Leadhttps://www.linkedin.com/in/stella-buhalis [https://www.linkedin.com/in/stella-buhalis] Błażej NowakowskiBackend Systems Architect & Database Engineerhttps://www.linkedin.com/in/b%C5%82a%C5%BCej-nowakowski-096716168/ [https://www.linkedin.com/in/b%C5%82a%C5%BCej-nowakowski-096716168/] Alena AstrakhantsevaTechnical Talent Strategist & Engineering Educatorhttps://www.linkedin.com/in/alenaastra/ [https://www.linkedin.com/in/alenaastra/] Zhen Ming Ng (Babypro)Open Source Software Maintainer & Core Developerhttps://www.linkedin.com/in/ming91/ [https://www.linkedin.com/in/ming91/]

19. kesä 202654 min

Competitions: Beyond the Kaggle Leaderboard - Tatiana Habruseva

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