I build machine learning pipelines that actually work in production — not just notebooks that look good in demos. Most of my work revolves around tabular data: gradient boosting (LightGBM, XGBoost, CatBoost), tabular deep learning (TabNet, TabPFN), and causal inference. I've spent a lot of time on the unglamorous but critical parts — feature engineering, handling imbalanced datasets, model calibration, and making sure results are interpretable and reproducible. A few things I've shipped: A cancer risk prediction system for a medical research team (AUC > 0.84), with full feature importance analysis and threshold strategy reports. A 3D reconstruction pipeline based on Structure-from-Motion, robust enough to handle blurry and low-texture inputs. That work led to 2 software copyrights and a patent under review. A causal boosting framework (CBDT) for heterogeneous treatment effect estimation — benchmarked on IHDP, ACIC, and MIMIC-III. Paper currently under submission. Quantitative models for financial risk — credit scoring with XGBoost and TabNet, A/B testing on simulated datasets, ended up improving accuracy by 15% and cutting false positives by 20%. I'm comfortable working with financial data, backtesting pipelines, and building risk models from scratch. I also work with OpenClaw for robotic manipulation tasks and have experience integrating it into simulation and control workflows. On the tools side: Python is my daily driver, along with PyTorch, Transformers, Optuna, and Git. I write clean, documented code — not the kind you need to reverse-engineer to understand. I'm finishing up a B.Eng. in Software Engineering (Beijing University of Technology × UCD joint program, class of 2026). Kaggle Gold and Silver medalist. If any of this sounds relevant to what you're working on, drop me a message. I usually reply within a few hours.

Senior developer who builds smart systems that actually make work easier. I love taking complex processes, automating them, and turning data into actionable insights that drive real results. I have worked with businesses across healthcare, legal, insurance, and logistics to automate workflows, handle huge volumes of data, and leverage AI to solve real-world challenges. In my past work, I have: 📄 Built AI-powered case creation tools for law firms reducing manual work while ensuring accuracy 🏥 Developed clinical systems for cancer treatment workflows helping healthcare teams make faster, data-driven decisions 🗂 Created document and check processing platforms handling thousands of files across legal cases with minimal manual intervention I work at the intersection of Python, AI, and automation 🤖 Build predictive models, NLP tools, and intelligent workflows 🔗 Integrate APIs and connect systems for seamless operations 💡 Develop interactive AI applications using OpenAI, LangChain, and other modern tools ⚙ Ensure reliable deployment and smooth post-launch operation Here’s how I can help you ✅ Automate repetitive tasks to save time and reduce errors ✅ Turn data into insights with analytics and AI-driven tools ✅ Build AI-powered products like chatbots, recommendation systems, and predictive models ✅ Streamline workflows with connected systems and intelligent backend solutions If you want to make your systems smarter, faster, and more productive, let’s connect. I enjoy collaborating with clients to design solutions that actually make life easier and more efficient.

I'm a Top Rated quantitative developer on Upwork, currently completing my MS in Data Science at Harvard, with production experience building and shipping algorithmic trading systems across futures, options, and equities. My work spans the full pipeline: from signal research and rigorous backtesting through execution architecture and live broker deployment. Over the years I've collaborated with professional traders, systematic fund managers, and independent CTAs on strategy research, execution system builds, and quantitative infrastructure — working with live accounts and real capital, not toy portfolios. - Research Philosophy Most algorithmic trading research fails before it reaches live markets. The reasons are almost always the same: data snooping bias, fragile parameterization, fill simulation that doesn't reflect actual execution, and strategy logic never stress-tested against regime change. My research process is designed to make it hard to fool yourself. That means strict chronological train/test splits with no parameter bleedthrough, walk-forward optimization over anchored and rolling windows, block bootstrap for inference on autocorrelated returns, and parameter sweep frameworks built to expose fragility rather than maximize backtest metrics. A strategy that only works on one parameterization isn't a strategy, it's a coincidence. I care about robustness across parameter space, regime stability, and understanding exactly why a signal works before scaling it. I work extensively in QuantConnect's LEAN engine for research-grade backtesting and live account deployment, though deployment targets vary by strategy and client stack. IB TWS via ibapi, Tradovate, and NinjaTrader are all in regular rotation depending on execution requirements. I build custom analytics layers on top of backtest output: Sharpe decomposition, drawdown attribution, execution cost modeling, and signal decay analysis, because standard tearsheet metrics rarely tell the full story. - Strategy Coverage My research spans futures (NQ, ES), SPX and index options, ETFs, and crypto. Strategy types I've built and validated in production include intraday momentum and trend-following systems, mean reversion and stat-arb frameworks, breakout and scalp architectures with dynamic sizing tiers, options strategies including iron condors, defined-risk vertical spreads, 45-DTE and 0DTE SPX structures with delta-based hedge logic, and GEX (gamma exposure) driven directional frameworks using open-interest-weighted dealer positioning data. It's an area where the signal literature is still thin and where getting the methodology right matters more than most people acknowledge. - Execution Engineering The research-to-live gap is where most systems break. I build execution infrastructure that closes that gap: Interactive Brokers TWS via ibapi with state machine architectures, order ladder geometry, true breakeven calculations with commission and slippage factored in, and hedge math for multi-leg positions. On the NQ/ES side I've built and audited scalp bot execution logic on Tradovate, integrated Databento for professional tick data pipelines with proper validation against reference data, and developed Pine Script strategies and indicators on TradingView for signal prototyping before committing to full implementation. I'm also familiar with NinjaTrader's execution environment and ATM framework. Code I deliver is production-standard: structured logging, explicit edge-case handling, clean separation of signal and execution layers, and documented at a level where the system is maintainable after handoff. - What I Work On: - Strategy Research & Backtesting: QuantConnect/LEAN, Backtrader, Zipline, VectorBT, QuantLib, Python - Execution Systems: IB TWS/ibapi, Tradovate API, NinjaTrader, REST/WebSocket broker integrations, FIX Protocol - Retail Platform Development: MQL4/MQL5 (MetaTrader 4/5), Pine Script (TradingView), NinjaScript (NinjaTrader 8), EasyLanguage (TradeStation), ThinkScript (Thinkorswim), cAlgo/C# (cTrader), AFL (AmiBroker) - Broker APIs: Interactive Brokers, Alpaca, TD Ameritrade, Tradovate, Oanda, Databento - Crypto Platforms & APIs: Binance, Bybit, OKX, Kraken, Coinbase Advanced Trade, Bitfinex, Deribit (options/derivatives), KuCoin, Gate io, Freqtrade, Hummingbot, 3Commas, Pionex, Gunbot, ccxt (unified exchange library) - Statistical Testing: Walk-forward testing, parameter sweep analysis, Monte Carlo simulation, bootstrap inference - Full-Stack Delivery: Data ingestion → signal research → backtesting → live deployment

AI Engineer with 4+ years of hands-on experience specializing in Data Science and Computer Vision. I partner with clients to build intelligent, scalable systems that turn complex data into actionable insights and automate visual tasks. My focus is on delivering end-to-end AI solutions, from data preprocessing and model development to deployment. I leverage my professional experience and my B.Tech in Artificial Intelligence to solve complex, real-world problems. Key Project: Co-authored a published algorithm for an object detection system ("Aadarsha Dristi") designed to enhance mobility for visually impaired individuals, demonstrating practical expertise in applying deep learning to computer vision challenges. My services include: Data Science: Predictive Modeling, Statistical Analysis, NLP, and Data-Driven Insights. Computer Vision: Object Detection, Image Recognition, Semantic Segmentation, and Video Analysis. Key Technologies: Programming: Python AI/ML: TensorFlow, PyTorch, Scikit-learn, Keras Computer Vision: OpenCV Data Tools: Pandas, NumPy, Matplotlib Let's collaborate to bring your AI-driven project to life. Send me a message to discuss your goals.

About Me I’m a Senior Full-Stack Engineer with 6+ years of hands-on experience delivering end-to-end AI and software solutions that solve real-world business problems. I specialize in React, Node, AI, machine learning, deep learning, NLP, and full-stack web development, helping startups and enterprises turn their ideas into intelligent, scalable products. ⸻ What I Bring to the Table: 🔹 Natural Language Processing (NLP): Expert in GPT-4, LLAMA 3, BERT, and other transformer models for tasks like text classification, semantic search, summarization, and chatbot development. 🔹 Computer Vision & Deep Learning: Developed high-accuracy models for object detection, classification, and segmentation using YOLOv5/YOLOv8, DINOv2, PaddleOCR, and PyTorch/TensorFlow. 🔹 Machine Learning & Predictive Analytics: Built models for forecasting, anomaly detection, and recommendation systems with strong focus on interpretability and performance. 🔹 Generative AI & LLM-based Applications: Experience building RAG pipelines, LLM agents, vector DB search, ChatGPT-powered bots, and fine-tuned domain-specific models. 🔹 Full Stack Development: Skilled in MERN / MEAN stack, Python (Django, FastAPI, Flask), REST APIs, GraphQL, and building responsive UIs using React. 🔹 DevOps & Cloud AI Deployment: End-to-end deployment using Docker, Kubernetes, and CI/CD pipelines. Cloud-native experience with AWS, GCP, Azure. ⸻ Industries I’ve Worked In: Healthcare, Dental Imaging, LegalTech, E-commerce, Fintech, Automotive, GIS, and SaaS. ⸻ If you’re looking for someone who can understand your vision, execute on both AI and software levels, and deliver production-grade systems — let’s talk. ⸻ Tech Stack: Python, PyTorch, TensorFlow, Transformers, LangChain, FastAPI, Django, React, Node.js, MongoDB, PostgreSQL, AWS, GCP, Docker, Kubernetes, LLMs (GPT-4, LLAMA, Claude, etc.)

I work on machine learning and statistical data analysis with Python. I have a Master’s in Computational Physics, and I’m used to working with noisy data, testing models carefully, and turning complex data into clear results. What I can help with: Machine learning Statistical analysis Data cleaning Python automation Data visualization Clear reports

I'm a Data Professional, Data Scientist, Machine Learning and AI engineer, and Software Engineer with 10+ Years of Experience in Tech. I leverage tech and data to drive insights and build intelligent systems using Data, ML and AI using Python, R, Tableau, PowerBI, Data Studio, as well as scalable software systems in Django, PostgreSQL, MySQL and APIs. In my experience, I have been helping businesses and individuals build data and software systems such as CRMs, Enterprise Software, Web Apps, automation for marketing and sales processes, digital marketing and use of AI in driving Business Productivity. Whether you need data analysis, data extraction, data mining, exploratory analysis, machine learning, or AI model and software app development or CRM design and implement, I can help. 1. Proficient in Python, R, SQL, TensorFlow, PyTorch, Airflow, PowerBI, Tableau, and Scikit-learn 2. Experienced in data management, data analysis, data mining, data visualization, and building end-to-end machine learning pipelines; conversant with design and management of CRMs (Zoho, PipeDrive, Hubspot, Salesforce, Freshsales) and automation. 3. Strong background in statistical modeling, deep learning, and natural language processing 4. I am a Full stack software engineer with experience in Django, SQL and APIs. Let's connect and grow together😊

Expert-Vetted Gen AI Engineer | Harvard and Columbia Alumni (Top 1% of Freelancers on Upwork) I am a highly experienced Generative AI Engineer who has worked with clients across multiple industries including finance, academia, e-commerce, construction, medicine, and web design. I provided high-quality solutions for all of my clients, earning me outstanding reviews and a 100% Job Success Rating. My areas of expertise include Large Language Models (LLMs), Generative AI, Chatbots, Data Science, AI Dashboard Development, Natural Language Processing, Data Visualization, and Statistics. In addition to my experience as an AI Engineer, I also have deep knowledge in grant writing, academic publishing, and clinical data analysis, having both written successful NIH and biotech grants and published 10+ manuscripts in high-impact academic journals such as Nature and Gastroenterology. SKILLS: * Extensive Experience with Prompt Engineering with many different LLMs such as OpneAI, Claude, Mistral, Gemini, Llama, Gemma, CodeLama, and Vicuna. * Built 20+ AI dashboards with Streamlit, Gradio, and HuggigngFace for clients to easily access solutions * Created Vector Databases and Retrieval-Augmented Generation Software to train LLMs on personal data such as PDFs, Word Documents, YouTube Videos, Images, and Excel Spreadsheets. * Proficient in leading AI solutions to production using AWS, GitHub, Langchain, LlamaIndex, LangSmith, LangFuse, and other AI tools. * Strong background in programming languages (Python, R, Javascript, SQL) and Data Science/Machine Learning frameworks (TensorFlow, Keras, PyTorch, scikit-learn, numpy, pandas) * Expertise in EHR, ICD-10 codes, clinical database management, clinical data analysis, and HIPAA compliance * Experience with Business Intelligence platforms such as Tableau, PowerBI, and Excel PROJECTS/ACCOMPLISHMENTS: * Co-Founder and CTO of a biotech company, Daldot which was acquired by Nutromics, an Australian MedTech company in 2021 * Developed the AI Algorithm for Shopify App that gained 10K+ users within a month * AI TikTok Influencer with 10K+ followers and 1M+ likes * Columbia University SEAS GSA Black History Month Alumni Spotlight 2023 * 2nd Place in the Columbia University Data Science Institute COVID-19 Data Challenge * Published 10+ manuscripts in high-impact journals such as Nature and Gastroenterology SPEAKING ENGAGEMENTS: * Guest Lecturer at Columbia University, Cornell Tech, Roux Institute, and Founder Institute for entrepreneurship, AI, and freelancing. * Developed a course on emotional intelligence for startup founders at Harvard University with 1,000+ students enrolled. * Presented research at the American Society of Clinical Oncology (ASCO) and Columbia University Data Science Institute Machine Learning in Science & Engineering Conference. EDUCATION: * Master's in Data Science from Columbia University * Bachelor's in Biophysics from Harvard University I have a 100% success rate in provided top-tier solutions across diverse sectors. Whether you need a custom solution or expert guidance, I am committed to leveraging the power of AI to elevate your business to the next level. Let's innovate together!

As a Rhodes Scholar with a doctorate in theoretical physics from Oxford University, I am well versed in both the scientific and creative arts. Whether your project requires an analysis of data, a design of apparatus, or a literal presentation of information, you can put me to work with confidence that the final product will exceed your expectations. My publications appear regularly in reputable journals and cover a wide range of topics. My consultancy Alphawave Research can help you address many of your technical needs, whether academic, commercial, or industrial, on a tight schedule and with spectacular results. What I practice is best described as inductive reasoning, otherwise known as inferential statistics. Inferential statistics encompasses both descriptive statistics (e.g. hypothesis testing) and predictive statistics (e.g. forecasting). A good description of what I do is found in D. S. Sivia's Data Analysis: A Bayesian Tutorial. That book is a quick read and easily skimmed, so if you can find it in your library or bookstore, please have a look at it. If you like what's going on there, you'll like what I can do for you.

Full-stack by foundation, AI by conviction. I was building machine learning systems back when it required more math than marketing - 17+ years in software development, 5+ years as a hands-on AI engineer and AI developer.🇺🇦 I'm a CTO-level AI engineer, machine learning architect, and software architect with a perfectionist's attention to detail. My team of AI engineer, AI developer, data scientist, and web developer delivers full-cycle AI App Development and Web Development - from early MVPs to enterprise platforms. Need an AI chatbot developer, an AI integration specialist, a software engineer, a Python developer for ML pipelines, or a data scientist with real machine learning depth? We've done it - properly. 𝗪𝗵𝗮𝘁 𝘄𝗲 𝗯𝘂𝗶𝗹𝗱 𝗮𝘀 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀: ✅ AI App Development - LLM-powered apps, RAG pipelines, AI bot and AI chatbot solutions ✅ AI Agent Automation, autonomous ai agent builder, ai agent creator and agentic workflows (LangChain, CrewAI) ✅ AI Integration - AI model integration and API integration into your existing systems ✅ AI Chatbot Developer services - intelligent bots, NLP systems, multilingual AI chatbot products ✅ AI Automation n8n - ai agent n8n workflow orchestration, data scraping, pipeline automation with n8n ✅ Computer Vision - OpenCV, CNN architectures, image recognition and processing systems ✅ Machine Learning & Data Science - model design, training, optimization, production deployment ✅ Web & Back-End Development - React, Node.js, Python, PHP, Java; RESTful & GraphQL API integration ✅ MVP / PoC - custom, low-code, no-code; discovery, UI/UX, QA, project management 𝗪𝗵𝘆 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝗰𝗵𝗼𝗼𝘀𝗲 𝘂𝘀: As AI developer and AI engineer, we don't just integrate tools - we architect solutions. Whether it's a custom AI chatbot developer engagement, a complex AI integration project, or a full AI App Development cycle, our AI engineering team brings senior-level ownership to every project. Every AI app developer on our team treats your product like their own. From AI integration strategy to deployment - we own it end to end. 🧬 𝗖𝗼𝗿𝗲 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: - Machine learning, deep learning (PyTorch, TensorFlow), Python machine learning systems - Natural Language Processing, computer vision (OpenCV, CNN), RAG pipelines - AI Agent Development, AI App Development, and AI chatbot development for production - Data scientist and data analyst workflows; quant machine learning for FinTech - AI Integration and API integration - robust RESTful / GraphQL API development - n8n automation, cloud infrastructure (AWS, Docker, Kubernetes) Our team includes senior AI engineer and specialists with machine learning PhD backgrounds. 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸: Python · PyTorch · TensorFlow · Scikit-Learn · LangChain · open ai developer · React · Vue · Angular · Node.js · Java · PHP (Laravel) · ASP.NET · PostgreSQL · MongoDB · ElasticSearch · AWS · Docker · Kubernetes · n8n 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗲𝘀: FinTech & quant ML · e-Learning · Fantasy sports & gaming · e-Commerce · Media & Entertainment · EcoTech · PropTech · Cybersecurity 𝗧𝗵𝗶𝘀 𝗽𝗿𝗼𝗳𝗶𝗹𝗲 𝗳𝗶𝘁𝘀 𝗶𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿: AI engineer · AI developer · AI chatbot developer · AI integration specialist · API integration specialist · machine learning engineer · data scientist · computer vision engineer · Python developer · web developer · AI agent developer · n8n automation expert · LangChain developer · AI bot developer · OpenAI developer · prompt engineer · agentic AI developer · AI Automation make · AI Prompt Engineer · AI Model · ML · LLM · ai machine learning trading · machine learning time series · airtable integration · ai api integration · software engineer · ai Lead Generation · social media marketing automation · etsy marketing · business development · pinterest marketing · sales agent · ai automationai developer · ai data engineer · ai engineer rag nlp · ai prompt engineering · ai saas developer · airtable automation · app developer with ai · bolt ai developer · computer vision machine learning · airtable integration 👉 Check the portfolio and selected projects below.