Hwayoung L. Top-Executive

Ph.D. Quant & Engineering Director with 12+ years of global experience (UK, Saudi Arabia, Korea).Mission: To serve and empower others by sharing unique global insights and technical expertise, striving to make a meaningful difference in every project I undertake.저의 직업적 소명은 '경험의 공유를 통한 타인의 성장을 돕는 것'에 있습니다. 글로벌 무대에서 겪은 특별한 경험을 바탕으로 타인의 짐을 덜어주는 삶을 지향합니다. 때로는 시간과 체력의 한계가 있더라도, '할 수 있는 데까지는 해보자'는 마음가짐으로 공동체의 발전과 비즈니스의 성공에 헌신합니다.I bridge deep financial domain knowledge (Computational Finance) with cutting-edge AI technologies (LLMs, LangGraph) to build robust, automated trading ecosystems and high-performance risk engines. My expertise lies in fusing complex derivatives math with modern software engineering (Rust, Python, MLOps) to drive tangible business value and technical moats.영국(Invesco), 사우디아라비아(PIF), 한국을 거치며 Computational Finance 박사로서 쌓은 학문적 깊이와 12년의 글로벌 실무 경험을 보유한 시니어 엔지니어입니다. 파생상품 수학, Rust/Python 기반의 고성능 엔지니어링, 그리고 최신 LLM 아키텍처를 결합하여 견고한 자동 매매 생태계와 금융 솔루션을 구축하는 데 특화되어 있습니다.Core Expertise & AchievementsNext-Gen Financial AI: 금융 도메인 지식과 최신 AI 기술을 접목하여, Quant Engine과 LLM(LangChain/LangGraph)을 통합한 시나리오 테스팅 및 동적 자산 배분(MVO) 시스템을 구축했습니다.Global Risk Management: 사우디 국부펀드(PIF)에서 리스크 엔진 고도화 및 스트레스 테스트 시스템을 성공적으로 구현했으며, VaR, ES 등 복잡한 리스크 지표 산출 및 거버넌스 수립에 능숙합니다.Robust Systems Engineering: 고성능 컴퓨팅(HPC) 기술을 활용해 대용량 금융 데이터를 처리하며, 데이터 수집부터 배포까지의 End-to-End MLOps 파이프라인을 설계·운영합니다.Technical SkillsFinance: Derivatives Pricing, Risk Modeling, Mean-Variance Optimization (MVO), Portfolio Strategy.AI/ML: LLM Agents, RAG, NLP (News Sentiment Analysis), PyTorch, Scikit-Learn.Engineering: Python, Rust, Java, Kotlin, SQL, C++, LangChain, Airflow, n8n. High-Performance Computing.

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Industry: Medicine and Biology
Headquarters: Seoul, Seoul
Title: Technical Manager
Company: Qunova Computing
Company Industry: Information Technology And Services
Company Website: qunovacomputing.com
Company Linkedin: linkedin.com/company/qunova-computing
Company Size: 11-50
Current Job Duration: 3 mos
Country: South Korea
Languages: English, Korean
Work Experience: Title: Technical Manager Company: Qunova Computing Company URL: https://www.linkedin.com/company/qunova-computing/ Industry: Information Technology And Services Company Size: 11-50 Location: Seoul, South Korea Country: None Employment Type: None Start At: 05-2026 Ends At: Present Description: None Title: Senior ML & LLM Engineer (part-time) Company: None Company URL: None Industry: None Company Size: None Location: Hanam Country: None Employment Type: None Start At: 02-2026 Ends At: Present Description: None Title: OptIQ Technologies Company: None Company URL: https://www.linkedin.com/company/krxoptionadvisor/ Industry: None Company Size: None Location: None Country: None Employment Type: None Start At: 12-2025 Ends At: Present Description: Key Focus: Global Asset Allocation | Market Analytics | Residency Planning Strategic Asset Acquisition: Secured a high-value unit (3xxx) at 360 Riverside Crescent (Sobha Hartland II). Strategically selected for its "View Premium" to maximize exit value and long-term capital appreciation. Quantitative Market Analysis: Leveraged transaction data and developer track records to conduct rigorous due diligence on Dubai’s property trends, ensuring risk-adjusted returns. Legal & Residency Management: Successfully navigated UAE’s legal landscape to obtain a 2-Year Investor Visa, establishing a permanent operational base and enhancing professional negotiation leverage in the region., A specialized Quant Developer focused on building high-performance trading infrastructure that integrates rigorous Risk Management Systems (RMS) with cutting-edge AI research. I ensure that quantitative strategies are not only executed flawlessly but are also governed by robust, real-time risk controls. Core Engineering Strategy RMS Development & Real-time Control: I design and implement high-availability Risk Management Systems (RMS) to monitor exposure and enforce limits in real-time. Leveraging C++ and Rust, I build low-latency pre-trade risk checks and automated circuit breakers to ensure system stability under extreme market volatility. Agentic Research Pipelines: I architect LLM-driven research workflows using LangChain and LangGraph. By building custom AI agents, I automate the extraction of insights from unstructured data, accelerating the discovery of new Alpha signals and streamlining the quantitative research process. Front-Office Strategy Support: I bridge the gap between researchers and the market by translating complex models into production-ready trading logic. Using Python, MATLAB, and Kotlin, I provide the technical support necessary to optimize strategy execution and improve hit rates. Scalable Infrastructure: I ensure the entire stack is future-proof by utilizing Docker and Kubernetes for orchestration, allowing for the seamless scaling of trading engines, RMS components, and research agents. Technical Stack Systems & RMS: C++, Rust, Java, Kotlin Data & Research: Python, MATLAB, SQL AI Orchestration: LangChain, LangGraph (Agentic Workflows) Infrastructure: Docker, Kubernetes, Target: developing profitable FX market making (MM) strategies adjusted for Market Impact (MI, https://bit.ly/4aVOL6t) Quantitative strategy development: expert in designing portfolios using FX spot/options/futures strategies and Mean-Variance Optimisation (MVO). ​Backtesting & validation: proven track record in conducting rigorous backtests to verify strategy viability and building efficient execution models. ​AI & agentic workflows: architecting financial RAG systems and multi-agent automation using LangChain and LangGraph. ​Technical stack: proficient in Python and Matlab for high-performance computing, with deployment expertise in AWS (EKS) and Kubernetes. ​I thrive at the intersection of finance and technology to translate complex technical milestones into tangible business outcomes. ​퀀트 전략 수립: FX 전략, 평균-분산 최적화(MVO) 등을 활용한 최적의 포트폴리오 설계. ​백테스팅 및 검증: 엄격한 백테스팅을 통해 전략의 유효성을 검토하고, 실제 시장 환경에 적합한 실행 모델 구축. ​AI & 에이전틱 워크플로우: LangChain 및 LangGraph 기반의 금융 RAG 시스템과 멀티 에이전트 자동화 시스템 설계. ​기술 스택: Python, Matlab을 활용한 고성능 연산 및 AWS(EKS), Kubernetes 기반의 확장성 있는 아키텍처 구현., I am currently running several side projects focused on Reinforcement Learning (RL) prototyping. These are purely academic pursuits dedicated to technical mastery and self-study, with no intent to monetise or build a business. https://cryptolifeblck.notion.site/TQC-Truncated-Quantile-Critics-31a6585be6ea80a595e5c9ab11aa5d2e?source=copy_link [Technical Focus] - TQC (Truncated Quantile Critics): Implementing state-of-the-art agents to manage aleatoric uncertainty and mitigate overestimation bias, ensuring stable control for HVAC and Energy Storage Systems (ESS). EMS (Energy Management System) Optimization: Engineering end-to-end loops that synchronize real-time forecasting with autonomous control to maximize efficiency within Smart City environments. Developing AI-driven energy management systems for Smart Cities, integrating LLM-based data synthesis and Reinforcement Learning (RL) for real-time energy load optimization and ESG compliance. [The Learning Curve: A Work in Progress] To be candid, I am still navigating the vast and often steep learning curve of Reinforcement Learning. I don't claim to be an expert—yet. However, my philosophy is to learn by doing. I recognise that there are gaps in my current understanding of RL's deeper nuances, but I view each project as a laboratory. By repeatedly applying these advanced techniques—like TQC—across diverse domains, I am systematically refining my technical intuition. With every bug fixed and reward function tuned, the picture becomes clearer. I am committed to this process of continuous prototyping, confident that the synergy between study and execution will lead to true technical proficiency. [Engineering Philosophy] I prioritize technical integrity and executability over pure domain knowledge. My 'Technical-First' approach focuses on building robust architectures where complex RL models seamlessly integrate with production databases. I believe in letting the code demonstrate the solution., Every pet owner knows the "Golden Time" panic—not knowing if a symptom is a midnight emergency or a minor hiccup. At LinkVet, LinkVet is bridging the information gap between pet parents and veterinary clinics. We’ve built an AI-driven medical routing ecosystem that doesn't just find a hospital—it finds the right one based on specialized equipment (CT/MRI) and clinical expertise. By integrating a retro-style gamified health engine, we turn the tedious task of health logging into a rewarding experience, creating the world’s most granular longitudinal pet health dataset for predictive AI and personalized nutrition. Currently scaling the 9-core service model—from smart triage to pet insurance data standardization—as we prepare for global expansion into the US markets., I’m currently running a few side projects purely for self-study. My goal is simply to sharpen my AI skills, not to monetize them or start a business. I just wanted to clarify that this is entirely about learning. With my experience as a Backend & Quantitative Developer, I specialize in building high-performance financial systems. My expertise spans from developing complex option trading engines to creating scalable hybrid quant architectures using Python, C++, Rust, Kotlin and Java. Currently, I am leveraging this technical background to help innovate the landscape, an AI-driven Edu-tech platform., I am dedicated to bridging macroeconomic insights with quantitative analysis to enhance trading strategies. https://cryptolifeblck.notion.site/Project-Title-LLM-Driven-Multi-Agent-Quantitative-Option-Strategy-Optimizer-2e46585be6ea8056aebfe9c66dcdc9a6 • Created an NLP pipeline using LangChain-LangGraph and GPT to quantify market sentiment and adjust portfolio cash ratios. • Designed dynamic risk management systems to protect against high-risk positions during market volatility. • Integrated a fully functional brokerage Open API for real-time data access and trading execution via WebSocket. Global Vision & Strategic Alliance We are not merely developing a platform; we are establishing a new global benchmark for financial services. This partnership marks a pivotal step in our expansion into the US and the Middle East, directly aligning with initiatives like Saudi Vision 2030. By integrating our proprietary AI consumption engines and financial frameworks—powered by LLM (LangGraph) and FastAPI—we are delivering a real-time intelligence ecosystem. Together, we are bridging the gap between sophisticated financial engineering and everyday accessibility, ensuring that the next generation is equipped with the tools for lifelong financial success., My involvement in various AI side projects is driven entirely by a desire for self-improvement. Please note that these are non-commercial ventures intended only for skill development. I am a forward-thinking professional dedicated to creating high-impact solutions in the Digital Therapeutics (DTx) space, while maintaining a keen eye on global investment opportunities. Currently, I am leading the development of 'LifeOn', an AI-driven "Life-Log Platform" designed to transform chronic disease management. At LifeOn, we are solving the "23-hour gap" in patient care—the time spent outside the doctor's office. By utilizing advanced LangGraph-based AI engines and Pydantic data schemas, our platform analyzes the real-time correlations between medication, supplements, and vital signs like blood glucose and pressure. My goal is to empower users through our "LifeOn Care+" subscription model, providing data-backed insights and professional coaching. AI Architecture & Development: Designed the "Chronic-Insight" module using Python to analyze the impact of nutritional supplements on vital signs, ensuring 100% data integrity through rigorous schemas. Product Vision: Developed the "Life-Log" vision to evolve a simple supplement recommendation service into a comprehensive healthcare platform. Business Model Innovation: Engineered the "LifeOn Care+" membership, integrating 24/7 AI health assistants ("Dr. Bot") and weekly precision reports to create recurring revenue streams. Expert Integration: Built reporting tools that allow medical professionals to interpret complex patient data in seconds, fostering a collaborative ecosystem between AI and human care., Just to be clear, I’m working on these AI projects just for fun and learning. I’m not looking to make any money from them—I’m just passionate about teaching myself AI. Hope that clears things up! At NutriLogic, we are closing the information gap in the supplement market by transforming medical expertise into a systematic, code-driven engine. We aren't just building a shopping mall; we are developing a high-performance healthcare platform where medical data flows seamlessly to provide safe, personalized nutrition. Core Technical Stack & Logic: Frontend: React Native (Expo) for rapid, cross-platform mobile MVP development. Backend: Python (FastAPI) optimized for medical data processing and complex algorithm implementation. Database: PostgreSQL (Supabase) for precise management of ingredient and biometric data. Recommendation Engine: A multi-stage logic that maps Symptoms → Nutrients → Products while cross-referencing contraindications. Engineering a "Medical-Grade" Moat: Agentic Workflow: Utilizing LangGraph to create a directed graph of user analysis, nutrient matching, and expert-led safety checks. Data Integrity (PHR): Standardizing National Health Insurance (NHIS) data and private health checkup results into a structured JSON schema to drive evidence-based recommendations. Expert-in-the-Loop Architecture: An enterprise-grade pipeline where medical professionals manage research in Obsidian, which is then synced via Airflow to our production database. Advanced RAG System: Integrating LangChain and pgvector to provide chatbot responses grounded in verified medical research, preventing hallucinations., I manage multiple AI side projects strictly for educational purposes. I have no interest in making a profit; I’m solely focused on mastering the technology. Just so there’s no misunderstanding! - LLM Driven Solutions: Designed LangChain·LangGraph pipelines for parameter estimation and automated state machine workflows. - Quant Engine Development: Built a Quant Engine for deep OTM call/put portfolios across four assets, enabling robust parsing and validation for expected return and covariance estimation. - Portfolio Optimization: Developed an Optimizer with hedge ratio constraints, integrating real-world restrictions such as dynamic cash allocation, long/short balance, and greeks. limits. - Automated Reporting: Automated portfolio greeks calculations and execution reporting, consolidating strike prices, positions, greeks, weights, and contract volumes. - Scenario Testing: Implemented a scenario testing framework to validate portfolios under diverse market conditions (e.g., Black Swan, liquidity crunch, inflation risk). - FX Strategy Automation: Designed USD/KRW scenario testing pipelines for automated spot, NDF, futures, and options strategies. Achievements: - Delivered KOSPI200 index option portfolios that met hedge ratio targets and provided final order sheets with key metrics (portfolio greeks, strike-level positions, weights, and volumes). - Optimized portfolio Greeks (Delta/Gamma/Vega/Theta) by integrating IV, risk reversal signals, swap points, and NDF spread indicators., As a Senior ML & LLM Engineer, I spearhead the development and optimization of cutting-edge Language Models and Machine Learning architectures. My core focus is on bridging the gap between advanced AI research and scalable, production-ready solutions. Key Responsibilities & Achievements: LLM Development & Fine-tuning: Architecting and optimizing Large Language Models (LLMs) to enhance performance for specific domain tasks. Pipeline Engineering: Designing and implementing robust end-to-end ML pipelines, including data preprocessing, model training, and deployment. Architecture Optimization: Implementing advanced techniques such as RAG (Retrieval-Augmented Generation), Prompt Engineering, and model quantization to improve inference speed and accuracy. Cross-functional Collaboration: Working closely with product and engineering teams to integrate AI capabilities into core business offerings. Infrastructure Management: Scaling AI workloads using cloud-native environments and high-performance computing resources. Tech Stack: Languages: Python, SQL AI/ML Frameworks: PyTorch, TensorFlow, Hugging Face LLM Tools: LangChain, LlamaIndex, Vector Databases (Pinecone, Weaviate) Cloud & DevOps: AWS/GCP/Azure, Docker, Kubernetes, Supported the finance audit system product development project. Optimized the backend architecture for a real-time finance audit product, enhancing system reliability and processing speed. Enterprise AI Solutions: Architected statistical models and AI pipelines for the Deloitte-linked XBRL system and the WeKnora project., Supported the pet healthcare system development Researched and designed the AI architecture and data pipelines for a pet healthcare solution, focusing on data integrity and automation. Reliable QA System Design (RAG): - Prototyped a veterinary QA bot minimising false information by integrating domain-specific documents with Vector Search (FAISS/Pinecone). - Established a pipeline for intent classification and reference citation using LangChain. Unstructured Data Processing Pipeline (Vision AI): - Designed an end-to-end pipeline for extracting nutritional data from product images. - Validated the effectiveness of hybrid approaches combining OpenCV preprocessing with Large Multimodal Models (LMM) like GPT-4o Vision. Advanced Data Engineering & NLP: - Developed a strategy for acquiring data from dynamic web environments using headless browser automation (Playwright). - Implemented a semantic clustering prototype using Sentence-BERT to solve synonym matching issues in ingredient databases. Title: Senior Backend Architect & Quant AI Specialist (remote, part-time) Company: None Company URL: https://www.linkedin.com/company/www.tda-labs.com/ Industry: None Company Size: None Location: London Area, United Kingdom Country: None Employment Type: None Start At: 01-2026 Ends At: Present Description: None Title: Manager (part-time) Company: None Company URL: https://www.linkedin.com/company/%EC%A4%91%EC%86%8C%EB%B2%A4%EC%B2%98%EA%B8%B0%EC%97%85%EC%A7%84%ED%9D%A5%EA%B3%B5%EB%8B%A8-korea-smes-startups-agency/ Industry: None Company Size: None Location: Riyadh Region Country: None Employment Type: None Start At: 02-2025 Ends At: 03-2025 Description: None Title: Quantitative Developer Company: Public Investment Fund (Pif) Company URL: https://www.linkedin.com/company/pifsaudi/ Industry: Financial Services Company Size: 1001-5000 Location: Riyadh, Saudi Arabia Country: None Employment Type: None Start At: 02-2022 Ends At: 02-2025 Description: None Title: Senior Researcher Company: Moin, Inc. Company URL: https://www.linkedin.com/company/moin-inc./ Industry: Financial Services Company Size: 51-200 Location: Gangnam-gu, Seoul, Korea Country: None Employment Type: None Start At: 07-2018 Ends At: 01-2022 Description: None Title: Quantitative Researcher (part-time) Company: Meister Trading Company URL: https://www.linkedin.com/company/meister-trading/ Industry: None Company Size: 1-10 Location: Seoul, South Korea Country: None Employment Type: None Start At: 03-2018 Ends At: 01-2022 Description: None Title: AI engineer Company: Qraft Technologies Company URL: https://www.linkedin.com/company/qraftec/ Industry: Investment Management Company Size: 51-200 Location: Seoul, Korea Country: None Employment Type: None Start At: 06-2017 Ends At: 02-2018 Description: None Title: Senior Manager Company: Celemics, Inc. Company URL: https://www.linkedin.com/company/celemics/ Industry: Biotechnology Company Size: 51-200 Location: Seoul, South Korea Country: None Employment Type: None Start At: 09-2015 Ends At: 01-2017 Description: None
Education: School: University of Essex Degree: Doctor of Philosophy (Ph.D.), Computational Finance Activities: None School: University of Essex Degree: Master, Financial Software Engineering Activities: None School: Hanyang Cyber University Degree: MA + PhD, Architecture and Urban Engineering Activities: None
Headline: Quantitative Developer | Ph.D. in Computational Finance | RAG, Vector Search | Building Data-driven Fin-Tech Solutions
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