Mike MrMike24

🧠 About Me

Software Engineer specializing in Artificial Intelligence, Machine Learning, and Natural Language Processing for data-intensive applications. I design end-to-end AI systems, predictive analytics pipelines, and Generative AI solutions using Python, PyTorch, scikit-learn, FastAPI, and LLM APIs.

I built and co-authored an IEEE-published, IEEE Xplore–indexed AI-powered financial analysis platform integrating machine learning, NLP, sentiment analysis, and real-time data processing, and completed Data Science and Data Analytics internships delivering predictive models and business intelligence solutions.

Currently pursuing an M.Sc. in Computational Linguistics (AI & NLP) at Heidelberg University, with a strong focus on scalable AI systems, intelligent software engineering, and applied machine learning.


🎓 Current Study	M.Sc. Computational Linguistics (AI & NLP), Heidelberg University
📍 Location	Heidelberg, Germany
🔬 Research Focus	AI · ML · NLP · Generative AI
📰 Publication	IEEE ICETEG 2025 · IEEE Xplore
🗣️ Languages	English (C1) · German (A2, learning)
✉️ Email	pramukesh872@gmail.com

🎯 Current Mission

┌─ 2025 ───────────────────────────────────────────────────────────┐
│  ✔  Published "WealthWise" at IEEE ICETEG 2025 (IEEE Xplore)      │
│  ✔  Data Analytics Internship — Quantium                          │
│  ✔  Data Science Internship — British Airways                     │
├─ 2026 ───────────────────────────────────────────────────────────┤
│  ▶  M.Sc. Computational Linguistics (AI & NLP) — Heidelberg Uni    │
│  ▶  Contributing to QuantLib (C++ quantitative finance library)   │
│  ▶  Learning German → targeting B1 fluency                        │
│  ▶  Deepening focus on scalable, systems-level AI engineering     │
└─────────────────────────────────────────────────────────────────┘

💼 Experience

🩶 Data Science Intern

British Airways · Sept 2025 – Oct 2025

Built predictive models via data preprocessing, feature engineering, and ML to analyze lounge eligibility for passengers at Heathrow Terminal 3
Ran EDA and feature selection to identify key drivers of customer eligibility
Applied data visualization and statistical analysis for targeted marketing and customer segmentation
Partnered with cross-functional stakeholders to translate analytical results into business decisions

📊 Data Analytics Intern

Quantium · Jul 2025 – Sept 2025

Analyzed large-scale retail transaction data in Python to surface purchasing behavior, financial patterns, and revenue trends
Performed customer segmentation and A/B testing to evaluate strategies and optimize ROI
Cleaned, transformed, and validated datasets for high-quality analysis and reporting
Built dashboards and visual reports to support strategic decision-making

🎓 Education

Period	Institution	Program	Result
2026 – Present	Heidelberg University, Germany	M.Sc. Computational Linguistics (AI & NLP)	In progress
2021 – 2025	SIES Graduate School of Technology (Autonomous), Mumbai University, India	B.E. Electronics & Computer Science Engineering — Honors in Cybersecurity	CGPA 8.07 / 10
2019 – 2021	SS High School and Jr. College, Mumbai University, India	Higher Secondary Certificate	80.17 / 100

🌱 Open Source Contributions

QuantLib (C++) — May 2026

Diagnosed a cross-platform build failure in blackvolatilitysurface code where std::vector was used without a proper include, relying on an implicit forward declaration that failed on stricter toolchains. Fix was merged into mainline by the library author — demonstrating the ability to navigate a large, production-grade C++ financial library and resolve non-obvious portability issues.

🚀 Featured Projects

💹 WealthWise — AI-Based Stock Analysis Chatbot

_{IEEE ICETEG 2025 · IEEE Xplore Indexed}

An AI-powered stock analysis platform integrating Machine Learning, NLP, technical indicators, and Generative AI to support intelligent investment decisions.

Architecture

End-to-end pipeline for real-time financial data acquisition, preprocessing, feature engineering, and predictive analytics via Yahoo Finance APIs
Technical indicator engine: RSI, MACD, EMA, ADX, ATR, Bollinger Bands, OBV
Google Gemini AI integrated with financial news sentiment analysis (VADER + TextBlob) for context-aware Buy / Sell / Hold recommendations
Interactive Streamlit + Plotly web app for real-time visualization of trends, indicators, and AI insights

Results: 90.22% accuracy · 91.23% precision · 92.86% recall · 92.04% F1-score

📄 IEEE Publication

WealthWise: An AI-Based Stock Analysis Tool

_{📚 IEEE International Conference on Emerging Technologies in Electronics and Green Energy (ICETEG 2025) · Indexed in IEEE Xplore}

Co-authored research on an AI-powered financial analysis platform combining Machine Learning, NLP, Generative AI, sentiment analysis, and technical indicators for stock market prediction. Proposed a hybrid framework integrating real-time financial data, technical analysis, Google Gemini AI, and market sentiment to generate intelligent investment recommendations — evaluated using industry-standard metrics (90.22% accuracy, 91.23% precision, 92.86% recall, 92.04% F1-score).

⚡ AI Arsenal

Domain	Proficiency
Machine Learning (PyTorch, Scikit-learn)	`█████████░` 90%
Natural Language Processing (spaCy, NLTK, Transformers, Stanza)	`████████░░` 85%
Generative AI & LLM APIs	`████████░░` 80%
Systems / Low-Level C++ (SIMD, lock-free structures)	`█████████░` 90%
Python (Data & ML systems)	`█████████░` 95%
Distributed Infra (Kafka, Redis, AWS, Docker)	`███████░░░` 75%
Quantitative Research & Time-Series	`███████░░░` 75%

🧰 Tech Stack

Languages

AI / ML / NLP

Frameworks & Web

Cloud / Data / DevOps

📊 GitHub Dashboard

🏆 Achievements

◆ Technical Coordinator — IEEE Student Branch
   Organized AI, cybersecurity, and software engineering seminars; coordinated
   hackathons, technical competitions, student volunteers, and event logistics.

◆ Workshop Organizer — AI & NLP Community
   Conducted technical workshops on Machine Learning, LLMs, Generative AI,
   and Python for students and developers.

◆ Student Ambassador — Mumbai University
   Represented the university at academic events, mentored prospective
   students, and promoted research, innovation, and student engagement.

◆ BCG X — Generative AI Virtual Experience Program
   Developed AI-powered business solutions using Prompt Engineering, LLMs,
   Generative AI, and AI workflow design.

◆ J.P. Morgan — Software Engineering Virtual Experience Program
   Applied software development, system design, debugging, version control,
   backend development, and problem-solving principles.

🔬 Research Interests

🤖 Generative AI
LLM-driven applications & prompt engineering

🗣️ NLP
Sentiment analysis, text pipelines, linguistic modeling

📈 Quantitative Research
Time-series analysis, portfolio optimisation, backtesting

🕸️ Graph Neural Networks
Structured & relational learning

⚙️ Systems for AI
SIMD, lock-free structures, scalable ML infra

🗺️ Current Learning Roadmap

IEEE-published research in AI-driven financial analysis
Production-grade C++ open-source contribution (QuantLib)
M.Sc. coursework in Computational Linguistics (AI & NLP) — in progress
German language proficiency: A2 → B1
Deeper specialization in scalable, systems-level AI engineering

🧭 Career Goals

Milestone	Focus
🎓 Complete M.Sc. in Computational Linguistics	AI & NLP specialization at Heidelberg University
🧪 Continue applied AI/NLP research	Building on IEEE-published work
🏗️ Grow as a Software Architect	Scalable AI systems & intelligent software engineering
🌍 Reach German B1 fluency	Supporting long-term work in Germany

✨ Fun Facts

🧩 Bug Hunter
Fixed a portability bug in QuantLib, a production-grade C++ financial library — merged by the library author

🗣️ Language Learner
English (C1) and currently building German (A2 → B1)

🎤 Community Builder
Organized hackathons & AI/NLP workshops as IEEE Technical Coordinator

📡 Connect With Me

_{📍 Heidelberg, Germany}

_{Thanks for stopping by — always happy to talk AI, NLP, and systems engineering. 🚀}

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