In our Haskell in Production series, we interview developers and technical leaders from companies that use Haskell for real-world tasks. We cover benefits, downsides, common pitfalls, and tips for building useful Haskell products. Our today’s guest is Syed Jafri, a Senior Software Engineer at Caribou – a company that helps car owners get quotes on refinancing and insurance. He managed to successfully pitch and introduce Haskell at Caribou. They are currently using it for some of the services […]

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Most infrastructure teams have a moment where someone says “we should build a platform.” The motivation is real: teams are duplicating work, the current setup is hard to use consistently, and a more structured approach would help. A few months later, the platform is a Terraform module collection, a GitLab CI template, a shared repository of scripts, and a README that several people have tried to keep current. That is a useful thing. It is not a platform. […]

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arXiv:2602.17751v1 Announce Type: new Abstract: Biodiversity loss poses a significant threat to humanity, making wildlife monitoring essential for assessing ecosystem health. Avian species are ideal subjects for this due to their popularity and the ease of identifying them through their distinctive songs. Traditionalavian monitoring methods require manual counting and are therefore costly and inefficient. In passive acoustic monitoring, soundscapes are recorded over long periods of time. The recordings are analyzed to identify bird species afterwards. Machine learning methods […]

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For years, we’ve treated coding interviews as the gateway to software engineering. Solve a few algorithm problems under pressure, and you’re “in.” Struggle with them, and suddenly your ability as an engineer is questioned. But here’s the uncomfortable truth: LeetCode-style interviews have never been a reliable measure of engineering skill. At best, they’re a hit-or-miss signal. Sometimes you’re in the zone. Sometimes the pressure gets to you. Sometimes you’ve seen a similar problem before. Sometimes you blank out […]

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In this paper, we examine how the VTP2 extended persistence timeout policy affects and influences the performance of distance-vector and link-state routing protocols in the ad hoc network of the New Generation of Open Digital Universities (DOUNG). The problem addressed is that conventional SCTP retransmissions lack good performance when losses result from a path break rather than congestion. In classical SCTP, missing acknowledgments may trigger retransmissions even when the loss is caused by a temporary route failure rather […]

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With over 12 years architecting secure, scalable systems for millions of users, the ACM Fremont Program Chair is channeling deep engineering expertise into a community platform the Bay Area didn’t know it was missing **Fremont, California | April 2026 There is a particular kind of engineer who treats knowledge as something to be shared, not hoarded. Deepak Kole is that kind of engineer. A seasoned software professional with over twelve years of experience architecting and delivering secure, scalable, […]

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arXiv:2604.16954v1 Announce Type: new Abstract: Category-level object pose estimation is fundamental for embodied intelligence, yet achieving robust generalization to unseen instances remains challenging. However, existing methods mainly rely on simple feature extraction and aggregation, which struggle to capture category-shared topological structures and conduct semantic keypoint modeling, limiting their generalization. To address these, we propose a textbf{T}opology-Aware Learning with textbf{S}emantic textbf{M}amba for Category-Level textbf{P}ose Estimation framework (TSM-Pose). Specifically, we introduce a Topology Extractor to capture the global topological representation […]

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arXiv:2510.01349v2 Announce Type: replace-cross Abstract: Symmetry-aware methods for machine learning, such as data augmentation and equivariant architectures, encourage correct model behavior on all transformations (e.g. rotations or permutations) of the original dataset. These methods can improve generalization and sample efficiency, under the assumption that the transformed datapoints are highly probable, or “important”, under the test distribution. In this work, we develop a method for critically evaluating this assumption. In particular, we propose a metric to quantify the amount […]

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Database design is more than schemas and tables—it’s storytelling. This piece reframes relational modeling as narrative construction, showing how clear predicates create meaning, why ignoring foundational rules leads to poor performance, and why AI can’t fix broken data structures. Strong databases come from humans who understand the story their data must tell.

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