SciPy India Blog

SciPy India × BangPypers Meetup, February 2026

2026-02-21T00:00:00+00:00

Srihari Thyagarajan, Agriya Khetarpal

There’s been a running conversation among us about holding offline events, in collaboration with other communities, as a way to grow SciPy India beyond our online calls. BangPypers was the natural first call, owing to their activity, consistency, and the community they’ve built. We reached out, had a few calls working through what a joint meetup would look like, and put together a plan. On Saturday, February 21st, 2026, that plan became an afternoon at Amadeus Software Labs in Bengaluru.

Details

Date: February 21st, 2026
Time: 11:00 to 14:30 IST
Venue: Amadeus Software Labs India Pvt Ltd, Kadubeesanahalli, Marathahalli, Bengaluru
Meetup page: SciPy India × BangPypers meetup
Photos: Meetup photos

Photo album

Background

This was a joint effort between SciPy India and BangPypers, with Amadeus hosting us at their Bengaluru office. It was the second time BangPypers had done a meetup at this venue. The call for proposals came from both communities, posting across both handles and reaching out to speakers from each network. Bengaluru was BangPypers’ home ground, and a chance to see how a more scientific computing-oriented programme would land there.

Agenda

Welcome and introductions
Garbage In, Garbage Out: Engineering Reliable LLM Systems Beyond the Prompt by Anirudh Sethuraman
From User to Maintainer: My NumPy Journey by Ganesh Kathiresan
Break
Python Annotations and t-strings: Python metaprogramming in the modern age by Tushar Sadhwani
Lightning talks
Closing remarks and lunch

Talks

Priyanka from Amadeus opened the day by introducing Amadeus and the other organizers before we moved into the talks.

Garbage In, Garbage Out (Anirudh Sethuraman)

Anirudh talked about building reliable LLM systems, walking through something he had actually built (slides). The focus was on the data pipeline, indexing, chunking, and how quality issues cascade from there. He also touched on frameworks like LlamaIndex: what they offer, where they fall short, and why understanding those limits matters before you commit to one over a custom design. The talk generated a fair bit of discussion around retrieval strategies and where these pipelines tend to break.

From User to Maintainer (Ganesh Kathiresan)

Ganesh was the first to arrive, and I had a good conversation with him before things got going. He is a NumPy maintainer and Senior SDE at Amazon.

He used a Quarto slide deck with runnable code, worth calling out because the examples weren’t just illustrative, they were live. His journey into open source started in 2019 with a Clang GC contribution, and he moved into NumPy in 2020. Some of his contributions: show_runtime() for inspecting NumPy’s runtime configuration, an integer division optimization that got roughly an 80% speedup, and bitwise_count().

His advice was grounded: start small, run local tests before you submit anything, and keep showing up. On using AI-generated code for OSS, he was careful to frame it not as a blanket no, but as something to be cautious about since it tends to miss the context maintainers actually care about. The talk drew a lot of conversation. People gathered around him afterwards and he stayed back for a while, patient with it all.

Python Annotations and t-strings (Tushar Sadhwani)

Tushar is a BangPypers regular. This was a very technical talk, mostly live demos with some slides, naturally spoken. He covered Python annotations and t-strings (PEP 750 territory) and ran for around 40 to 45 minutes. It ran long in the good way, where time disappears and nobody minds.

Lightning Talks

We finalized the lightning talks at the break around 1:40 PM. Both ran about 10 to 12 minutes each:

Load balancing project by Nischal Jain
Metagenomics: classifying a billion base pairs per second with Kraken2 by Anand Reddy Pandikunta

Aftermath

A couple of people walked up afterwards saying they wanted to get involved with SciPy India. That counts for more than a dozen online signups. The people who make that effort in person are the ones who actually follow through. This is why offline meetups matter.

Toward the close, Jayita and I pitched FOSSHack by FOSS United, where BangPypers and SciPy India are community partners. We shared a QR code and briefly highlighted the Partner Projects.

Thanks to everyone who showed up, asked questions, and stayed back for discussions. Thanks to all the speakers for their practical talks, to Amadeus for hosting us, and to the BangPypers organizers for making this joint event happen.

If you want to stay involved with SciPy India, join our Zulip chat, follow our social channels, and keep an eye out for the next meetup.

If you want to stay involved with BangPypers, find them on LinkedIn, Twitter, Instagram, join their Discord, or check their CFP repo for upcoming talks.

IndiaFOSS 2025 | Devroom – FOSS in Science

2025-09-21T00:00:00+00:00

Srihari Thyagarajan, Agriya Khetarpal

This blog post is our account of SciPy India’s participation in the FOSS in Science devroom at IndiaFOSS 2025, held in Bengaluru. Here, we describe the devroom as it happened, including the talks, discussions, and the incredible diversity of applications of free and open-source software in scientific research and practice across India.

Details

Date: September 21st, 2025
Time: 10:00 to 13:00 IST
Venue: NIMHANS Convention Centre, Bengaluru
YouTube livestream: https://www.youtube.com/watch?v=NyQced4oJVM

Video

Background

IndiaFOSS 2025 brought together the Indian FOSS community for two days of talks, workshops, and networking. Among the various devrooms, the FOSS in Science devroom carved out a space for researchers, practitioners, and enthusiasts to discuss how open-source software is transforming scientific work — topics included data acquisition in STEM education, formalizing mathematical proofs, tracking bird populations, and building digital public infrastructure for landscape planning.

Agenda

We had an ambitious lineup spanning the entire day. Here’s what the devroom covered:

Welcome and opening remarks
KuttyPy: A no cost transformation of the ubiquitous Arduino into an affordable data acquisition system for STEM by Jithin B P
Understanding API dispatching in Scientific Python Ecosystem by Aditi Juneja
The Array API Standard: One ring to rule them all by Pradyot Ranjan
Zarr: Cloud-optimised, N-dimensional, typed array storage by Sanket Verma
Assessing the State of India’s Birds using FOSS by Pradeep Koulgi
Collaborative CAD & GIS in JupyterLab by Arjun Verma
Break and networking
The CoRE stack open-source initiative by Dr. Aaditeshwar Seth
Formalizing Mathematics and Scientific Computing with an Open-Source Theorem Prover by Sagnik Saha
Empowering Open Science with Scalable Interactive Computing Environments in India by Kriyanshi Shah
Beyond the smokescreen: interactive in-browser FOSS tools for science communication and evidence-based environmental policy by Agriya Khetarpal
The Observability of Everything: Instrumenting Science with DevOps Tools by Aftab S
Breaking into the Black Box: Making LLMs Transparent for Science by Alosh Denny
Signal Over Noise: Benchmarking Time Series Models with sktime by Jigyasu Krishnan
Closing remarks and community announcements

Highlights

Jithin B P’s presentation on KuttyPy kicked off the devroom with a practical demonstration of how a modified bootloader can transform ubiquitous Arduino boards into real-time data acquisition systems without the traditional compile-upload cycle. The approach is elegant in its simplicity: by enabling direct register-level access through a Python library, students and educators can interact with sensors and actuators in real-time, making embedded systems education far more accessible and immediate. Jithin’s work has already found its way into outreach programs teaching kids embedded systems, with a curriculum that builds from binary number systems to programming basics. The upcoming STEM turtle board, with onboard motor drivers and sensors that can interact with other turtles, promises to bring Logo-like programming into the physical world in a delightfully tangible way.

Aditi Juneja’s talk on API dispatching in the Scientific Python ecosystem addressed a fundamental challenge: how do libraries like NetworkX, NumPy and scikit-image enable users to transparently switch between different computational backends for improved performance? Her presentation walked through the evolution from if-else conditions to decorator-based dispatching, showcasing how NetworkX supports both type-based and name-based dispatching with fallback mechanisms, while NumPy relies on type-based dispatching through __array_function__, and scikit-image uses entry points for greater flexibility. The talk clarified what’s often hidden plumbing in scientific software, making it clear how these design choices affect both library developers and end users.

Pradyot Ranjan’s presentation on the Array API Standard made a convincing argument for why the widespread use of array libraries — NumPy, CuPy, PyTorch, JAX, and others — requires a standardised API specification. The standard aims to provide consistent APIs and array operations across different Python libraries, enabling backend-agnostic code that can run on CPUs, GPUs, or specialized hardware without modification. This is the kind of infrastructure work that doesn’t make headlines but makes everything else possible: when consumer libraries like scikit-learn can write against the Array API instead of assuming NumPy, the entire ecosystem becomes more interoperable and sustainable.

Sanket Verma, a long-time maintainer of Zarr and a Technical and Administrative Board member of the NumFOCUS, presented what’s new with Zarr, the cloud-optimized storage format for N-dimensional arrays. Created initially by Alistair Miles in 2016 for handling massive genomic datasets from malaria research, Zarr’s approach of dividing large arrays into compressed chunks that can be stored and loaded selectively has proven transformative for scientific computing at scale. The recently released Zarr Python 3 brings a leaner specification, improved handling of high-latency storage, and extensibility through entry point mechanisms for custom stores and codecs. With institutions using Zarr to store datasets approaching petabytes in the cloud, Sanket’s update on the active community — weekly meetings, office hours, and a welcoming environment for new contributors — reinforced that this is infrastructure built for the long haul.

Pradeep Koulgi’s talk on assessing the State of India’s Birds using FOSS demonstrated the power of citizen science data at scale. This initiative involves a partnership of 14 organizations that rely on millions of observations contributed by birdwatchers to the eBird platform. Together, they create trend analyses and distribution maps for over 940 bird species, all of which are published publicly and free of charge. Their MYNA web tool enables users to generate localized regional reports, transforming this vast dataset into actionable insights for conservation efforts. What stood out most was Pradeep’s openness about the challenges they face. As the data corpus grows exponentially, the process of computing and analyzing it becomes increasingly difficult without expertise in FOSS tools and scalable infrastructure. Their journey—moving from struggles with computational bottlenecks to developing scalable, cost-effective solutions with FOSS—is a narrative that many scientific projects can relate to.

Arjun Verma’s presentation on collaborative CAD & GIS in JupyterLab showcased Jupyter CAD and Jupyter GIS as browser-native applications that bring parametric 3D modeling and full-featured GIS capabilities directly into the notebook environment. Built on Open Cascade and OpenLayers compiled to WebAssembly, these tools support everything from boolean operations and fillets in CAD to advanced symbology and time sliders in GIS — all while maintaining collaborative editing and Python API integration. The vision here is clear: reproducible, shareable workflows where code, visualization, and analysis live together, whether you’re analyzing climate patterns, planning land use, or teaching spatial concepts.

After a much-needed break — Dr. Aaditeshwar Seth presented the CoRE stack, a digital public infrastructure initiative aimed at helping communities make informed decisions about their landscapes. Rather than starting with technology and looking for problems, the CoRE stack begins by understanding what communities are trying to solve and using machine learning, satellite data, and hydrological modeling to make marginalized groups more visible and empowered. The stack’s layered approach — data collection, modeling, analytics — generates indicators for landscape planning using open data from satellites and government sources. Tools like “Know Your Landscape” for area-level planning and “Commons Connect” for community volunteers to geotag interventions demonstrate a community-based approach to landscape stewardship. Their goal of supporting 25,000 landscape stewards across India, potentially funded through innovative models like carbon credits, shows ambitious thinking about scale and sustainability.

Sagnik Saha’s talk on formalizing mathematics and scientific computing with Lean, an open-source theorem prover, introduced a world where mathematical proofs are not just written but verified by software. Formalization ensures reproducibility and streamlines peer review by making mathematical logic programmable and checkable. Lean’s dependent type system and interactive theorem proving have already been used to verify major projects like the liquid tensor experiment and formalize entire textbooks on analysis. The community is active and growing globally, but as Sagnik noted, India has fewer than ten contributors currently — a gap that represents both a challenge and an opportunity for the community.

Kriyanshi Shah’s presentation on empowering open science with scalable interactive computing environments tackled a problem familiar to anyone who’s tried to onboard new researchers to scientific computing: installation is hard, especially in air-gapped systems without internet access. Her solution, built on JupyterHub and Kubernetes, provides scalable, secure, domain-customizable computing environments with Docker containers preloaded with scientific libraries. Each user gets a ready-to-go environment with minimal technical overhead, mounted with shared satellite data volumes. What started as infrastructure for researchers is now expanding to enable data sharing and interaction with custom satellite datasets across more scientific domains.

Agriya Khetarpal’s presentation on interactive in-browser FOSS tools for science communication and evidence-based environmental policy, argued that science communication often fails not because scientists aren’t trying, but because of structural barriers — pedagogical, sociopolitical, and monetary. Using the example of air pollution in New Delhi, where stubble burning has decreased 71% over five years, yet pollution remains severe due to vehicular emissions and industry, Agriya demonstrated how Pyodide and JupyterLite enable data analysis and visualization entirely in the browser. These tools lower barriers to entry, allowing journalists, policymakers, and citizens to engage with data interactively without requiring high-performance computing infrastructure. When science communication is reproducible, interactive, and accessible, we move closer to evidence-based policy that serves everyone, especially vulnerable communities disproportionately affected by misdirected resources.

Aftab’s talk on instrumenting science with DevOps tools confronted an uncomfortable truth: over 50% of published scientific findings cannot be reproduced. The reproducibility crisis isn’t just embarrassing; it’s expensive and undermines trust in science. His solution — research ops, or the application of DevOps practices to scientific research — uses tools like Git for versioning manuscripts and datasets, Docker for packaging environments, and Kubernetes for orchestrating computational workflows. CI/CD pipelines automate repetitive tasks, improving efficiency and reducing human error. While implementing these practices comes with cultural and technical challenges (scientists learning new tools, integrating with legacy systems), the potential to improve collaboration, reproducibility, and the reliability of scientific findings makes it worthwhile.

Alosh Denny’s presentation on making LLMs transparent for science addressed the black-box problem of large language models: we see the output but not the reasoning. Using open-source tools like TransformerLens and Prisma 2, Alosh demonstrated how to peek into LLMs’ internal workings — tracing the exact path of how they process questions, visualizing attention heat maps showing word relevance, and even examining neurons in multimodal models to understand how they identify images. For scientific applications, where understanding how a model arrives at conclusions is as important as the conclusions themselves, these interpretability tools are essential for building trust and identifying failure modes.

Jigyasu Krishnan closed out the technical program with his talk on benchmarking time series models with sktime. sktime provides a unified, community-governed framework with consistent APIs across all models, the largest model zoo in the ecosystem, and dataset loaders for popular benchmarks. The upcoming “collections” feature — sets of predefined models, datasets, metrics, and cross-validation strategies — will make reproducing and extending studies even easier. It’s the kind of infrastructure that makes science more efficient and reproducible by reducing friction in the experimental process.

Closing remarks

After a full day of talks spanning hardware hacking, infrastructure design, data analysis, policy, and everything in between, the devroom concluded with announcements about the SciPy India community. We shared information about our first community call in July, our upcoming plans for more community calls and workshops, and our hopes for an in-person conference later this year or early next year. We encouraged attendees to join our Zulip chat, check out our open-source repositories, and fill out the feedback form with their thoughts on the community and preferences for future events.

Livestream

The full FOSS in Science devroom was livestreamed on YouTube for those who couldn’t attend in person. The recording remains available for viewing at your convenience, with timestamps for individual talks.

Videos

Individual talk recordings are now available in the FOSS in Science devroom playlist. Here’s the complete schedule with links to each presentation:

Talk	Speaker	Video
KuttyPy: A no cost transformation of the ubiquitous Arduino into an affordable data acquisition system for STEM	Jithin B P	YouTube
Understanding API Dispatching in Scientific Python ecosystem	Aditi Juneja	YouTube
The Array API Standard: One ring to rule them all	Pradyot Ranjan	YouTube
Zarr: Cloud-optimised, N-dimensional, typed array storage	Sanket Verma	YouTube
Assessing the State of India’s Birds using FOSS	Pradeep Koulgi	YouTube
Collaborative CAD & GIS in JupyterLab	Arjun Verma	YouTube
The CoRE stack open-source initiative	Dr. Aaditeshwar Seth	YouTube
Formalizing Mathematics and Scientific Computing with an Open-Source Theorem Prover	Sagnik Saha	YouTube
Empowering Open Science with Scalable Interactive Computing Environments in India	Kriyanshi Shah	YouTube
Beyond the smokescreen: interactive in-browser FOSS tools for science communication and evidence-based environmental policy	Agriya Khetarpal	YouTube
The Observability of Everything: Instrumenting Science with DevOps Tools	Aftab S	YouTube
Breaking into the Black Box: Making LLMs Transparent for Science	Alosh Denny	YouTube
Signal Over Noise: Benchmarking Time Series Models with sktime	Jigyasu Krishnan	YouTube

In a nutshell

Thank you to everyone who spoke, attended, asked questions, and contributed to making the FOSS in Science devroom at IndiaFOSS 2025 a success. To the speakers who travelled to Bengaluru and prepared thoughtful presentations showcasing their work: your contributions made the day what it was. To FOSS United for organizing IndiaFOSS and providing us with the platform and infrastructure to host the devroom: we’re grateful for your continued support of the FOSS community in India.

We look forward to seeing you at future community events, whether online or in person! To stay updated, join our Zulip chat and follow us on our social channels. And to you, the reader, thank you for taking the time to read about our day in Bengaluru. We hope it inspires you to explore, contribute, and connect with the scientific FOSS community.

SciPy India Community Call #1 – July 2025

2025-07-26T00:00:00+00:00

Agriya Khetarpal, Aditi Juneja, and Srihari Thyagarajan

This blog post is our account of our first SciPy India community call held on July 26th, 2025. Here, we describe the call as it happened, including updates from the community, the speakers and their presentations, and our discussions on future plans.

Details

Date: July 26th, 2025
Time: 10:00 to 13:00 IST
Platform: Jitsi Meet (online)

Agenda

We had a packed agenda for our first community call. Here’s a brief overview of what we covered:

Welcome and introductions
Talk 1: Automating ML with PyCaret by Manjunath Janardhan
Talk 2: marimo: an open-source, reactive Python notebook by Srihari Thyagarajan
Breakout sessions, discussions, and networking
Lightning talk 1: Introduction to Causal Machine Learning and pgmpy by Mohammad Razak
Lightning talk 2: Subgraph Matching: The Needle-in-a-Network Problem by Varuni H K
Closing remarks and next steps

Highlights

Manjunath Janardhan’s presentation on automating machine learning with PyCaret was insightful and demonstrated practical applications of the library, and how it makes machine learning accessible to a broader audience. Building up from machine learning from first principles, he demonstrated how PyCaret streamlines the typical machine learning pipeline — from data preprocessing and feature engineering to model training, evaluation, and deployment; abstracting away much of the complexity involved in building and deploying machine learning models, for non-experts and experts alike, whether for learning or for production. This was followed by Manjunath’s live demo of PyCaret’s capabilities using a sample dataset that provides diabetes-related features, showcasing how quickly one can build and evaluate multiple classification algorithms with “low code”, visualise their performance, and predict outcomes on new data. Manjunath, at the time of writing, is a principal AI engineer at msg global solutions, working on graph databases, generative AI solutions, and more.

Srihari Thyagarajan’s talk on marimo, an open-source, reactive Python notebook, showcased an innovative notebook format that is, in marimo’s words, “a next-generation reactive notebook, stored as Git-friendly, reproducible, deployable as a script, shareable as an app”, that enhances the interactivity and usability of Python notebooks as compared to the standard Jupyter notebook format. We were thrilled to see the enthusiasm for marimo, especially its potential for AI-related integrations and scientific use cases, and its ability to facilitate reproducible in-browser research via WebAssembly. The discussion also highlighted exciting opportunities for community contributions and integration projects with marimo, similar to how Jupyter has fostered a thriving ecosystem of extensions and plugins. As Srihari mentioned, he enjoyed his time presenting to the community and getting feedback as an early contributor, ambassador, and intern at the venture, working on topics such as interactive docs, integrations, outreach, and more.

Mohammad Razak’s lightning talk on causal machine learning and the pgmpy library provided a concise introduction to the concepts of causality in machine learning, and how pgmpy can be used to model and infer causal relationships in data. He discussed the importance of understanding causality for making informed decisions based on data (i.e., the “correlation does not imply causation” adage), and how pgmpy provides tools for building probabilistic graphical models that can capture these relationships. His talk sparked interest in the community about the applications of causal inference in various domains, including healthcare, economics, and social sciences. Mohammad Razak, at the time of writing, is developing a Rust backend for pgmpy as part of an European Summer of Code (ESoC) project, and we look forward to seeing the progress on this front.

Varuni H K’s lightning talk on subgraph matching addressed the challenges of finding smaller graphs within larger ones, a problem that is becoming increasingly important in fields such as social network analysis, bioinformatics, and recommendation systems. She introduced the concept of subgraph isomorphism and discussed various algorithms and techniques for efficient subgraph matching, including graph neural networks. Her talk generated a lively discussion among participants interested in network analyses about the potential applications of these techniques and the need for further research in this area. Varuni, at the time of writing, is a software engineer at CouchBase, working on distributed databases and vector search.

In between the talks, discussions engaged participants on various topics, including the future of SciPy India, the licensing and governance of libraries used in scientific Python projects, questions on venture capital funding for open source projects and its implications on sustainability, and several other topics.

Aftermath

The community call concluded with surveys to gather feedback from attendees, and gauge if there is interest in organising such events in person at intervals throughout the year, in addition to our regular online calls. We are also exploring if there is interest in the community for the next SciPy India conference in late 2025 or early 2026, through another survey that was shared during the call. The survey will remain open, and we encourage you to fill it out. We also received feedback on the content and overall format of the call, as well as constructive suggestions on topics for future calls, which we will take into consideration and incorporate into our planning for upcoming events. Many attendees expressed interest in volunteering and contributing to the community, which is heartening for us to see!

Livestream

Our community call was livestreamed on YouTube for those who could not attend the live session. The recording is available for viewing at your convenience.

In a nutshell

Thank you to everyone who participated and contributed to the success of our first community call! Especially, we thank our speakers for their presentations, and the discussions that followed. In addition, we are grateful to the FOSS United platform and its representatives for providing us with the necessary infrastructure to host our event online and manage registrations.

We look forward to seeing you at upcoming community calls and events! To stay updated on the same, please join our Zulip chat and follow us on our social media channels. And to you, the reader, thank you for reading!