From d0a578dc4cde6a404bf4373caad13142bfc35c33 Mon Sep 17 00:00:00 2001 From: rohanpatel2002 Date: Thu, 14 May 2026 12:04:56 +0530 Subject: [PATCH] feat: added a featured publication section --- src/routes/index.tsx | 462 ++++++++++++++++++++++++++++--------------- 1 file changed, 303 insertions(+), 159 deletions(-) diff --git a/src/routes/index.tsx b/src/routes/index.tsx index fcabc7d..7e24947 100644 --- a/src/routes/index.tsx +++ b/src/routes/index.tsx @@ -141,7 +141,6 @@ function Hero() { - {/* scroll cue */} @@ -159,8 +158,150 @@ function Hero() { ); } +const rulesData = [ + { + id: "01", + title: "Maximize Context Density", + subtitle: "Keyword proximity weighting", + blurb: "Modern applicant routing systems weigh semantic proximity over raw string matching. Action verbs coupled with absolute metric clusters score up to 3.4x higher pass indices.", + code: `package pipeline + +// Rule 01: Context Density Weighting +func EvaluateImpact(bullet string) float64 { + verbs := ExtractActionVerbs(bullet) + metrics := ParseAbsoluteMetrics(bullet) + + if len(verbs) > 0 && len(metrics) > 0 { + return CalculateProximityScore(verbs[0], metrics[0]) * 1.5 + } + return 0.2 // Orphaned string weight +}` + }, + { + id: "02", + title: "Term Vector Proximity", + subtitle: "Explicit schema taxonomy bindings", + blurb: "Avoid unstructured creative section headers. Parsers map documents into standard taxonomy nodes. Using canonical section identifiers ensures guaranteed parsing extraction.", + code: `package taxonomy + +// Rule 02: Explicit Schema Encodings +var CanonicalHeaders = map[string]TaxonomyNode{ + "EXPERIENCE": NodeProfessionalHistory, + "PUBLICATIONS": NodeScholarlyResearch, + "SKILLS": NodeTechnicalCapabilities, +} + +func ExtractSection(token string) (TaxonomyNode, bool) { + // Exact schema bindings pass parsing layers natively + node, exists := CanonicalHeaders[strings.ToUpper(token)] + return node, exists +}` + }, + { + id: "03", + title: "Optical Stream Flattening", + subtitle: "Deterministic flow formatting", + blurb: "Complex column floats and custom graphical glyphs fail standard optical character recognition streams. Pure, single-column nested flow layouts ensure flawless string normalization.", + code: `package textstream + +// Rule 03: Flatten Structural Floats +func NormalizeDocumentStream(layout Node) string { + if layout.HasFloat() || layout.IsMultiColumn() { + // Warning: Non-linear character stream injection risk + return FlattenOpticalStream(layout, StripFormatting) + } + return DirectBufferRead(layout) +}` + } +]; + +function BookDeck() { + const [activeTab, setActiveTab] = useState(0); + const rule = rulesData[activeTab]; + + return ( +
+
+

[ FEATURED PUBLICATION ]

 + + +

+ Distilling algorithmic applicant tracking systems (ATS) into concrete document engineering contracts. Explore interactive execution modules from the book below. +

+ + +
+ + {/* Left controls */} +
+
+ [ ALGORITHMIC CONTRACTS ] +
+ {rulesData.map((r, i) => ( + + ))} +
+
+ +
+

+ "{rule.blurb}" +

+
+
+ {/* Right IDE layout */} +
+ {/* IDE Header tabs */} +
+
+ + + + evaluator_rule_{rule.id}.go +
+ Go 1.22 runtime +
+ {/* IDE body */} +
+ + + 
+                      {rule.code}
+
+ + +
+
+ +
+ +
+
+ ); +} function Index() { const { open } = useContactModal(); @@ -176,18 +317,18 @@ function Index() {

[ ABOUT ]

- -
- -

- I'm fascinated by building systems that behave well under load, intent, and time. - Whether it's a deployment gate that catches bad pushes, a semantic document engine, - or an AI code reviewer — I care about the parts most people skip: the data model, - the failure modes, and the shape of the API. Currently building at Praalak Tech Solutions - and interning as a Research Software Engineer at the Physical Research Laboratory. -

- -
+ +
+ +

+ I'm fascinated by building systems that behave well under load, intent, and time. + Whether it's a deployment gate that catches bad pushes, a semantic document engine, + or an AI code reviewer — I care about the parts most people skip: the data model, + the failure modes, and the shape of the API. Currently building at Praalak Tech Solutions + and interning as a Research Software Engineer at the Physical Research Laboratory. +

+ +
@@ -205,24 +346,24 @@ function Index() { {projects.map((p, i) => ( - - - - -
-

{p.tag}

-

{p.name}

-

{p.blurb}

-
-
- {p.meta} - View → -
- + + + + +
+

{p.tag}

+

{p.name}

+

{p.blurb}

+
+
+ {p.meta} + View → +
+ @@ -283,147 +424,150 @@ function Index() { {/* Flawless 4x3 Bento Box layout */}
- - {/* Slot 1: Go / Core Engine (2 cols x 2 rows) */} - - {/* Subtle architectural background texture */} -
-
-
- Go + {/* Slot 1: Go / Core Engine (2 cols x 2 rows) */} + + {/* Subtle architectural background texture */} +
+ +
+
+ Go +
+ + [ CORE ENGINE ] +
- - [ CORE ENGINE ] - -
- -
-

Go & Backend Systems

-

- Building highly concurrent system components, robust deployment gates, and resilient API contracts engineered to perform predictably under load. -

-
- + +
+

Go & Backend Systems

+

+ Building highly concurrent system components, robust deployment gates, and resilient API contracts engineered to perform predictably under load. +

+
+ - {/* Slot 2: React & TypeScript (2 cols x 1 row) */} - -
-
- Frontend Architecture - -
-
-

React & TypeScript

-

- Type-safe, highly modular interactive user interfaces built with custom design systems, smooth motion layouts, and state predictability. -

-
- + {/* Slot 2: React & TypeScript (2 cols x 1 row) */} + +
+
+ Frontend Architecture + +
+
+

React & TypeScript

+

+ Type-safe, highly modular interactive user interfaces built with custom design systems, smooth motion layouts, and state predictability. +

+
+ - {/* Slot 3: AI Integration (1 col x 1 row) */} - -
- 🤖 - LLMs / RAG -
-
-

AI Integration

-

- Embedding pipelines, LangChain agents, and structured outputs with high-fidelity semantic validation. -

-
- + {/* Slot 3: AI Integration (1 col x 1 row) */} + +
+ 🤖 + LLMs / RAG +
+
+

AI Integration

+

+ Embedding pipelines, LangChain agents, and structured outputs with high-fidelity semantic validation. +

+
+ - {/* Slot 4: Databases (1 col x 1 row) */} - -
- 🗄️ - Persistence -
-
-

Databases

-

- Postgres, Redis, MongoDB, and pgvector optimized for low-latency relational and semantic retrievals. -

-
- + {/* Slot 4: Databases (1 col x 1 row) */} + +
+ 🗄️ + Persistence +
+
+

Databases

+

+ Postgres, Redis, MongoDB, and pgvector optimized for low-latency relational and semantic retrievals. +

+
+ - {/* Slot 5: Python (1 col x 1 row) */} - -
- PY - Scripting -
-
-

Python Engine

-

- Django REST interfaces, data parsing automation, and rapid exploratory backend pipelines. -

-
- + {/* Slot 5: Python (1 col x 1 row) */} + +
+ PY + Scripting +
+
+

Python Engine

+

+ Django REST interfaces, data parsing automation, and rapid exploratory backend pipelines. +

+
+ - {/* Slot 6: DevOps (1 col x 1 row) */} - -
- ⚡ - Infra -
-
-

DevOps & CI

-

- Docker containerization, Git governance workflows, and custom active deployment safety gates. -

-
- + {/* Slot 6: DevOps (1 col x 1 row) */} + +
+ ⚡ + Infra +
+
+

DevOps & CI

+

+ Docker containerization, Git governance workflows, and custom active deployment safety gates. +

+
+ - {/* Slot 7: Ecosystem Arsenal Track (2 cols x 1 row) */} - - [ RUNTIMES & PROTOCOLS ] -
- {["Node.js", "Supabase", "REST APIs", "gRPC", "SQL", "Postman", "Linux", "CI/CD"].map((item) => ( - - {item} - - ))} -
- + {/* Slot 7: Ecosystem Arsenal Track (2 cols x 1 row) */} + + [ RUNTIMES & PROTOCOLS ] +
+ {["Node.js", "Supabase", "REST APIs", "gRPC", "SQL", "Postman", "Linux", "CI/CD"].map((item) => ( + + {item} + + ))} +
+
+ {/* PUBLICATION DECK */} + + {/* CONTACT */} {/* CONTACT */}