Darsh Dave

AI Product Manager (Transitioning) | Data Engineer -> Product | Scaling OnlyScholar | PhD in AI @IIIT Allahabad

I build and scale AI products through research analysis, market thinking, growth strategy, and product execution.

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Darsh Dave

Vision & Goal

North Star Metrics
1B+ Lives impacted through AI products
1,000 Research papers that help society and future research
10%+ Research ideas converted into products
Vision

Business sense + research depth + data thinking create scalable, impactful products.

Build AI products that solve global problems by turning research into trusted, useful products.

Goals
Short Term
  • Build 3-5 strong AI products in the next 2-3 years.
  • Scale at least one product to 100K+ users.
Long Term
  • Publish 10-20 high-quality papers per year.
  • Keep 70%+ work at the intersection of research, product, and market execution.

Experience

01Job Experience

Own infra-level data systems, pipeline reliability, orchestration, monitoring, and platform quality.

  • Lead scalable data infrastructure improvements across ETL orchestration and warehouse workflows.
  • Improve observability with monitoring, alerting, and reliability checks for production data jobs.
  • Partner with analytics, product, and engineering teams to convert data requirements into stable systems.

Designed scalable ETL pipelines with Python, Airflow, and Snowflake while improving query performance and monitoring.

  • Designed and implemented scalable ETL pipelines using Python, Airflow, and Snowflake.
  • Optimized data models for 30% better query performance.
  • Introduced monitoring and alerting to reduce downtime by 25%.

Optimized AWS ETL/ELT pipelines, Redshift workflows, reports, and AI infrastructure.

  • Optimized AWS ETL/ELT pipelines for 40% faster execution.
  • Scaled Redshift workflows for 30% query gain.
  • Maintained MLOps stack contributing to 15% lower NPA rate.

Built Airflow workflows, optimized SQL, and helped build internal ETL framework components.

  • Built Airflow-based workflows for 30% faster data throughput.
  • Reduced retrieval times by 40% through SQL query tuning.
  • Co-created a scalable in-house ETL framework with senior engineers.

Taught data structures, database systems, Python programming, deep learning labs, and guided capstone projects.

  • Guided 100+ students per semester on capstone projects.
  • Introduced hands-on deep learning modules, improving practical understanding by 40%.
  • Supervised projects with 80%+ students scoring distinction in final evaluation.
02Business Experience

Implement and write research papers across deep learning, computer vision, NLP, machine learning, GenAI, and agentic AI.

  • Build implementations and write research papers in deep learning, computer vision, NLP, ML, GenAI, and agentic AI.
  • Write literature survey papers around the same technical domains.
  • Support topic framing, experiments, writing, and journal submission workflows.

Implemented computer vision experiments and wrote research papers and literature surveys.

  • Implemented computer vision experiments for academic research papers.
  • Converted experiments into methodology, results, and publication-ready drafts.
  • Built research-writing discipline before formalizing OnlyScholar.

Launched a dropshipping store, solved shipping timelines, reached around 100 orders, and learned hard lessons in marketing.

  • Sourced products from China and sold to customers in the USA and Canada.
  • Solved shipping time-span problems during operations.
  • Closed around 100 orders in 6 months, then shut down because marketing was weak.

Education

Computer Science Engineering Parul University · CGPA 7.19 / 10.0
  • Developed a capstone project around IoT systems.
  • Built early research exposure in deep learning.
  • Organized 5 hackathons and startup-focused events.
Computer Engineering Parul University · Gold Medalist · CGPA 9.09 / 10.0
  • Specialized in artificial intelligence, machine learning, and computer vision.
  • Received Gold Medalist recognition for academic performance.
  • Published 3 research papers during the program.
Information Technology Indian Institute of Information Technology, Allahabad
  • Working on architecture-driven AI research.
  • Exploring scene text spotting through diffusion and architectural changes.
  • Studying deep models in depth from research and implementation angles.

Skills & Expertise

Product Management

Design & Research

FigmaUI/UX DesignUser ResearchWireframing & PrototypingUsability TestingUser EmpathyCustomer Journey MappingPersona Development

Strategy & Planning

Feature PlanningProduct Vision DevelopmentFeature PrioritizationRoadmap PlanningGo-To-Market StrategyStrategic ThinkingMarket Analysis

Execution & Delivery

Agile MethodologiesSprint Planning & ExecutionCross-Functional Team LeadershipStakeholder ManagementRisk ManagementProduct Lifecycle Management

Analytics & Optimization

Analytics & Metrics TrackingA/B Testing & ExperimentationData VisualizationKPI Setting & MonitoringDocumentation & Reporting

Communication & Leadership

Communication & Presentation SkillsStorytelling for Product VisionNegotiation & Influencing SkillsChange ManagementInnovation ManagementNetworking & Relationship Building

General & Strategic Skills

User-Centric Design & Research

User EmpathyUX/UI Design PrinciplesCustomer Feedback Analysis

Product Strategy & Roadmap

Strategic PlanningFeature PrioritizationGo-To-Market StrategyBusiness Model Canvas Creation

Data-Driven Decision Making

Analytics & Metrics TrackingA/B Testing & ExperimentationData Visualization

Collaboration & Communication

Cross-Functional Team LeadershipStakeholder ManagementAgile MethodologiesTime Management

Software & Development

Software Development Life Cycle (SDLC)Design ThinkingChange Management

AI & Data Skills

AI & Machine Learning

Deep LearningMachine LearningComputer VisionNatural Language Processing (NLP)Generative AI (GenAI)AI AgentsTransformers

AI Tools & Platforms

Lovablen8nGammaCrewAIQuillBotREST APIs

Data Engineering

SQL / NoSQLAWS GlueApache AirflowRedshiftMongoDBVector DatabasesData Vectorization

Data Management

Data WarehousingETL / ELT PipelinesData ModelingData Monitoring & Logging

Tech & Programming

Programming & Development

PythonRESTful APIsAPI Integration

Cloud & Infrastructure

AWS (EC2, S3, Lambda, Redshift)DockerCI/CD Familiarity

Tools & Operations

Git / GitHubLogging and Monitoring Tools

Product Portfolio

01Product Case Study 01

Tear down · PRD/TRD · Interactive mock design

02Product Case Study 02

User problem · product requirements · technical requirements

03Product Case Study 03

Market gap · MVP scope · launch and growth thinking

AI Portfolio

Research Publication

2024 View paper ↗

DATS: Driver Assistance Text Spotter

AIP Conference Proceedings · AIP Publishing LLC

End-to-end scene text spotting system for driver assistance. The work focuses on detecting and recognizing blurry, sheared, noisy, and small text that appears in driving environments.

  • Uses DenseNet-121 to generate higher-dimensional feature maps for scene text spotting.
  • Introduces NTDnet, a Noisy Text Detection Network, to handle difficult text cases.
  • Improves scene text spotting precision by 5.1% and shows at least 3.2% improvement across small, medium, and large text.
2023 View paper ↗

LightHARs: A Light Human Activity Recognition System

Springer Nature Singapore · ICMISC 2022 Proceedings

Privacy-aware human activity recognition system using sensor data instead of video-heavy inputs. The model is designed to reduce parameter count and computation time while keeping recognition performance strong.

  • Builds a cost-efficient deep neural network for human activity recognition.
  • Uses sensor data to reduce identity exposure compared with video-based HAR systems.
  • Outperforms existing HAR models by achieving 4.5% higher accuracy.
2023 View paper ↗

Insect Recognition: A Visionary Step Towards Smart Agriculture

AIP Conference Proceedings · AIP Publishing LLC

Computer vision system for smart agriculture that identifies crop-threatening insects so farmers can take preventive action before attacks reduce production.

  • Targets insect detection as a practical problem for drones, robots, and smart agriculture workflows.
  • Achieves 81% recognition performance with a computationally effective model.
  • Uses 1,640,423 parameters, keeping the system adaptable for existing agriculture equipment.
2020 View paper ↗

Automated Gas Leakage Security System

Journal of Emerging Technologies and Innovative Research

IoT-based toxic gas detection and alerting system for homes, offices, education spaces, and industrial environments. The system monitors gas levels continuously and sends fast alerts during leakage events.

  • Designs a microcontroller-based gas detection and safety alerting system.
  • Triggers alarm, email, SMS, and call alerts when toxic gas exceeds the normal level.
  • Focuses on faster emergency response and reducing further leakage risk.

Research execution and publication support for AI Academic Scholars.

  • Build research implementations in deep learning, computer vision, NLP, GenAI, and agentic AI.
  • Write research papers, literature surveys, methodology, experiments, results, and journal-ready drafts.
  • Support publication workflows from topic framing to submission, revision, and acceptance tracking.

Develop 1,000+ academic scholars with strong research backgrounds and relevant industry-ready skills.

OnlyScholar helps PhD scholars move forward with clarity, expert-led execution, publication focus, and structured research support.

Help every PhD scholar and academic professional publish at least one SCI paper every year.

The mission is to simplify topic selection, implementation, writing, submission, revision, and publication workflows.

Research Papers Completed25+

Implementation-backed papers, surveys, and applied AI research drafts completed.

Projects Accepted By Journals21+

Research projects moved through submission, revision, and acceptance workflows.

Projects In Pipeline15+

Active research ideas across AI, computer vision, NLP, GenAI, and agentic systems.

Projected Growth
2/mo

Completed run rate

10/mo

Projected run rate

Jul 2025 Jul 2026 Jul 2027 2/mo now 10/mo target

Completed run rate from July 2025 to July 2026, projected toward 10 projects per month by July 2027.

Contact Me

Open to AI product, research-to-product, data platform, and founder/operator conversations.

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