Recognition and case studies

Science Olympiad — AIR 1

2006 · All India Rank 1

Run by the Science Olympiad Foundation (SOF) — a New Delhi-based nonprofit founded in 1998 by Mahabir Singh with a group of academicians, scientists, and media personalities. NSO was SOF's very first Olympiad and has since grown into one of Asia's largest school science competitions.

• Organizer: Science Olympiad Foundation (SOF), est. 1998
• Scale today: 91,000+ schools across 70+ countries
• Format: two-level test of scientific reasoning & logic, classes 1–12
• Result: All India Rank 1, 2006

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Special Prize, Dr. Y.S. Rajan

2006 · Presented by Dr. Y.S. Rajan

Dr. Y.S. Rajan is a physicist and Honorary Distinguished Professor at ISRO, where he served as Scientific Secretary during its formative growth into a full-scale service organization. He co-authored “India 2020: A Vision for the New Millennium” with Dr. APJ Abdul Kalam and was awarded the Padma Shri in 2012 for contributions to science and engineering.

• Role: Honorary Distinguished Professor, ISRO; former Scientific Secretary, ISRO
• Co-author, “India 2020” with Dr. APJ Abdul Kalam
• Padma Shri, 2012 — science & engineering
• Presented this prize in recognition of the same academic effort, 2006

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Geography Olympiad, CMS Lucknow

2006 — 2007 · CMS Lucknow — model exhibit and international delegates

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DLW Sansthan Quiz — State Rank 1

Varanasi · 1st Rank, State-wise

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School Recognition

Class 7 · 2nd Rank

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Case Studies — Technical Deep Dives

Proof of work · Two technical deep dives, written up in full

A short technical deck covering two real problems: reverse-engineering a live production WebGL shader with no source access, and designing a three-layer client-side architecture for graceful failure under any browser or GPU condition.

• Case 1 — recovered a "gravity lens" cursor-warp shader from a shipped, minified JS bundle with zero source access, then validated the finding by reimplementing it
• Case 2 — a three-layer resilience architecture (feature detection → containment boundary → content-equivalent fallback), the same pattern this site's own WebGL fallback uses

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Security Log Analysis: Performance Case Study

Proof of work · Engineering report, 15 October 2026 · From a 14-minute run to under five, with the evidence

A pipeline that reads Windows security event logs and flags suspicious activity was verified against one complete real Security log: 188,406 records, parsed in full with no sampling, every enabled rule and detector run. Round 1 did not meet its memory goal, and the report said so. Round 2 cut pipeline time by 75% (849 s to 209 s), peak worker memory by 62% (3,628 to 1,393 MiB) and the result handoff by 94% (440 to 26 MiB), with zero swap and ten of ten analytical outputs unchanged.

• Measured on one log and one VM. Database saving, browser latency and concurrency were not measured, and are listed as open findings
• Shown as a GRC-style findings register: 10 findings with risk before and after controls, a heat map, controls and evidence
• The risk ratings and ISO/IEC 27001 references are my indicative reading, not an audit. Product and project names, paths, hashes and record values are withheld

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SOC + Field-Ops Graph (Design Exercise)

Systems design exercise — not operational SOC experience · Extending this site's own graph model to security operations

Most SOC platforms and physical-security/guard-tracking systems run as two disconnected tools — one tracks alerts, incidents, and assets; the other tracks people, zones, and shifts. This is a systems-design exercise applying the same typed-entity/typed-relation model already running live on this site's Knowledge Graph node to that gap: a digital layer (Alert, IOC, Asset, Playbook, Incident, Analyst) and a physical layer (Operator, Zone, Shift, Device), bridged by explicit cross-domain relations.

• Digital layer: Alert —triggeredBy→ IOC, Incident —investigatedBy→ Analyst, Analyst —followsPlaybook→ Playbook
• Physical layer: Operator —assignedZone→ Zone, —onShift→ Shift, —equippedWith→ Device
• The actual point of the exercise — three bridging relations: Incident —dispatchedTo→ Operator, Incident —occursAt→ Zone, Analyst —coordinatesWith→ Operator, answering "which operator is nearest this incident right now" as one graph query instead of two separate dashboards
• A schema, not a deployment — no real SIEM, GPS, or dispatch-system data behind it yet; the honest next step is real feeds into a graph database, not a bigger diagram

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