PROFILE / 01

A little more about me.

I’m Tanush, a 19-year-old CSE student, developer, and curious maker. I love learning how things work—and building ideas into things people can use.

About meABOUT MEAnime illustration centered over the TLUX wordmarkABOUT METanush · 19 · CSE
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Currently

Learning and building

I’m pursuing a B.Tech in Computer Science and Engineering at Oriental Institute of Science and Technology. I’m in my third semester, with graduation expected in 2029.

Experience · 2026

EmergX

I completed an internship at EmergX, gaining experience working in a professional environment.

Away from the screen

A few things I enjoy

I love sketching and dancing, and anime is a favourite way to unwind. Coding has become a hobby too: I enjoy exploring a new idea and seeing where I can take it.

Curiosity, put to work

Things I work with

A growing toolkit

01Programming Languages

JavaScriptTypeScriptPythonJavaC++GoSQLHTML5CSS3

02Frontend Development

ReactNext.jsViteRedux ToolkitZustandReact QueryReact Hook FormFramer MotionTailwind CSSBootstrapMaterial UIShadcn UISassCSS ModulesStyled ComponentsResponsive DesignAccessibilityProgressive Web AppsServer-Side RenderingStatic Site Generation

03Backend Development

Node.jsExpress.jsNestJSFastAPIREST APIsGraphQLWebSocketsgRPCMicroservicesEvent-Driven ArchitectureAuthenticationAuthorizationJWTOAuth 2.0OpenAPISwaggerAPI Rate LimitingBackground Jobs

04Databases & Data Storage

PostgreSQLMySQLSQLiteSQL ServerMongoDBRedisFirebaseElasticsearchPineconeQdrantChromaDBpgvectorDatabase DesignDatabase IndexingQuery OptimizationMongoose

05DevOps & CI/CD

GitGitHubGitLabGitHub ActionsGitLab CI/CDDockerDocker ComposeKubernetesDeployment AutomationInfrastructure as Code

06Cloud Computing

Amazon Web ServicesGoogle Cloud PlatformCloudflareVercelNetlifyRenderAWS EC2AWS S3AWS LambdaAWS ECSGoogle Cloud RunGoogle Cloud StorageLoad BalancingAuto ScalingCloud SecurityCost Optimization

07Monitoring & Observability

PrometheusGrafanaELK StackElastic StackRoot Cause Analysis

08Data Analysis

Python Data AnalysisSQL Data AnalysisMicrosoft ExcelAdvanced ExcelPivot TablesPower QueryPower PivotPower BITableauPandasNumPyJupyter NotebookExploratory Data AnalysisData CleaningData ValidationData VisualizationDescriptive StatisticsHypothesis TestingA/B TestingKPI DevelopmentBusiness IntelligenceDashboard DevelopmentStatistical Analysis

09Data Science & Statistics

NumPyPandasSciPyScikit-learnMatplotlibSeabornPlotlyProbabilityLinear AlgebraStatistical InferenceRegression AnalysisCorrelation AnalysisBayesian StatisticsFeature EngineeringFeature SelectionDimensionality ReductionPrincipal Component AnalysisMissing Value ImputationOutlier DetectionModel EvaluationCross-ValidationHyperparameter TuningExperimental Design

010Machine Learning

Supervised LearningUnsupervised LearningSemi-Supervised LearningClassificationRegressionClusteringDecision TreesRandom ForestGradient BoostingXGBoostLightGBMSupport Vector MachinesK-Nearest NeighborsK-MeansDBSCANNaive BayesEnsemble LearningRecommendation SystemsModel Explainability

011Deep Learning & Computer Vision

PyTorchTensorFlowKerasNeural NetworksArtificial Neural NetworksConvolutional Neural NetworksRecurrent Neural NetworksLSTMGRUTransformersAttention MechanismsComputer VisionImage ClassificationObject DetectionImage SegmentationOpenCVYOLOTransfer LearningFine-TuningGPU Computing

012NLP & Generative AI

Natural Language ProcessingHugging FaceTransformersTokenizationText ClassificationSentiment AnalysisText EmbeddingsSemantic SearchVector SearchRetrieval-Augmented GenerationRAGLangChainLangGraphLangFlowOpenAI APIAnthropic APIGoogle Gemini APIOllamaHugging Face InferencePrompt EngineeringAI AgentsAgentic WorkflowsTool CallingStructured OutputsLLM EvaluationFine-Tuning LLMsModel Context ProtocolMultimodal AISpeech RecognitionText-to-Speech

013Big Data & Distributed Systems

Apache KafkaApache ZooKeeperDistributed ComputingDistributed SystemsMessage QueuesRabbitMQAmazon SQSAmazon SNSGoogle Pub/SubAzure Service BusEvent StreamingData PartitioningReplicationConsistency ModelsFault ToleranceHorizontal ScalingCAP Theorem

014Software Architecture & Engineering

Object-Oriented ProgrammingFunctional ProgrammingData StructuresAlgorithmsSystem DesignLow-Level DesignHigh-Level DesignDesign PatternsSOLID PrinciplesClean ArchitectureMonolithic ArchitectureMicroservices ArchitectureEvent-Driven ArchitectureCQRSEvent SourcingCaching StrategiesConcurrencyParallel ProgrammingDistributed Transactions (In lerning phase)ScalabilityReliability EngineeringPerformance Optimization

015Tools & Developer Productivity

VS CodeIntelliJ IDEAPyCharmWebStormJupyterLabJupyter NotebookGitHub CopilotPostmanSwagger UIFigmaNotionMarkdownRegexCron
Curious by nature. Always learning, always looking for the next idea to bring to life.

Github / 02

Building in public.

My GitHub is where I share what I’m learning, the projects I’m shaping, and the progress behind them.

GITHUB PROFILE

Tanush Patel

@tanushpatel-git
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CSE student, developer, and curious maker—learning in public and building along the way.

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GitHub activity

A year of showing up.

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EXPERIENCE / 03 · EmergX

My EmergX experience.

Three months as a remote full-stack development intern, building job-discovery and candidate-screening features.

REMOTE INTERNSHIP · 3 MONTHS · 2026

EmergX

Remote intern · Product and recruiting features

2026

Role

Remote intern

Company

EmergX

Duration

Apr 1 – Jun 30, 2026

THE EXPERIENCE

Building tools for job discovery and hiring.

During my three-month remote internship from April 1 to June 30, 2026, I worked on features for the EmergX platform that supported both job seekers and HR teams.

I built a LinkedIn job-search agent and extended the recruiting workflow with candidate questions and an Excel-style applicant view, helping bring the relevant information into one place.

MY CONTRIBUTIONS

What I built

Two features · One internship

JOB DISCOVERY AGENT

01

Find relevant roles on LinkedIn

I built an agent-powered job search that takes a user’s role and company-size preferences and turns them into relevant LinkedIn listings inside EmergX.

HOW IT WORKS

  1. 01

    Set preferences

    Choose a role such as full-stack and a company size such as 11–15 employees.

  2. 02

    Search LinkedIn

    The agent checks LinkedIn for openings that match those preferences.

  3. 03

    Review matches

    It collects the matching job details and displays them in the EmergX portal.

Job searchLinkedIn listingsAgent workflow

HIRING WORKFLOW

02

Add screening questions to applications

I extended EmergX’s existing eight-step recruiting setup with pre-application questions and a spreadsheet-style way for HR to review applicants by job.

HOW IT WORKS

  1. 01

    Create questions

    HR adds a screening step to the recruiting form and writes questions for applicants.

  2. 02

    Collect responses

    Candidates answer those questions before completing the job application.

  3. 03

    Review applicants

    HR sees each job’s applicants and their details in a sortable, Excel-style portal view.

Recruiting formsCandidate questionsApplicant management

INTERNSHIP CERTIFICATE

Completed at EmergX

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Internship completion certificate from EmergX for Tanush Patel
EmergX · Remote internship · 2026Building for hiring and job discovery

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