Ishaan Saxena
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with less than a year in AI/ML & Full-stack Development
Highly motivated and results-driven individual pursuing a B.Tech in Mathematics and Computing with a strong focus on Financial Engineering. With practical experience as an AI/ML Intern and Business Analyst, I have developed a robust skill set in AI-powered backend development, data analysis, and machine learning. My expertise includes building fintech backends, developing LLM-based chatbots, and leveraging data for process improvement, complemented by a strong foundation in Python, SQL, React.js, and various AI/ML frameworks. I am eager to apply my technical and analytical capabilities to innovative engineering challenges.
Rajiv Gandhi Institute of Petroleum Technology
B.Tech. · Mathematics and Computing with Elective in Financial Engineering
August 1, 2023 – June 30, 2027
Sanfort World School
Senior Secondary · CBSE Board
June 1, 2022 – May 31, 2022
Coding House
AI/ML Intern
May 1, 2026 – June 1, 2026
India
ScholarsBoost
Business Analyst
January 1, 2025 – July 1, 2025
India
Carbon-Aware Digital Twin Microgrid Optimization System
June 1, 2026 – Present
-Engineered a carbon-first microgrid optimization system leveraging IoT sensing, MQTT streaming, and Digital Twin modeling to intelligently shift loads between renewable and grid sources. -Implemented a hybrid ML pipeline using LSTM (time-series forecasting), XGBoost (carbon intensity prediction), and quantile regression for risk-aware control, enabling real-time decision automation. -Deployed an end-to-end system with ESP32 hardware control, FastAPI backend, and Streamlit dashboard, demonstrating AI-driven energy optimization and measurable carbon footprint reduction.
View ProjectProject Saaransh: AI Powered E-Consultation Analysis Platform
June 1, 2026 – Present
-Developed an enterprise-grade AI framework for the Ministry of Corporate Affairs (MCA) to automate sentiment analysis of legal submission consultations using DistilBert, IndicBert, and Legal-BERT. -Designed quality metric confidence scoring system using Naive Bayes and Gaussian distribution and redistribution for neutral categories, converting 0-1 probabilities to interpretable 1-5 confidence ratings. -Developed section/clause-wise AI summarization with multi-language translation (LibreTranslate API) and text-to-speech audio generation supporting Hindi TTS, implementing fallback mechanisms. -Created admin dashboard and user panel with React.js, featuring real-time analytics, stakeholder ecosystem mapping, cross-consultation trend analysis predicting regulatory hotspots, exploratory data analysis, Performed data cleaning and interactive stance visualizations using Chart.js.
View ProjectAuraCast: Climatological Weather Risk Assessment Platform
June 1, 2026 – Present
-Climatological probability engine analyzing 30+ years of NASA MERRA-2 data and with real-time API integration to predict adverse weather conditions for long-term planning using Random Forest classifier. -Implemented activity-specific risk weighting algorithms applying to different outdoor planning, reducing event cancellation by enabling data-driven planning 6+ months ahead. Developed ci/cd pipeline. -Architected full-stack solution with Fast API and React TypeScript frontend with serverless deployment.
View ProjectIntegrating Quantitative Finance with Traditional Equity Research
June 1, 2026 – Present
-Integrating statistical risk assessment, and quantitative analysis methods using BSE Ltd. as case study with real market data achieving 88% confidence interval predictions for stock price movement. -Implemented Monte Carlo simulation using Geometric Brownian Motion with market parameters (mue=0.12, sigma=0.45) resulting in mean price projection of 2,686.52 -Applied Black-Scholes option pricing model and analyzed derivatives market with implied volatility analysis (45-47%) and option chain open interest patterns.
Predicting Indian IPO Subscription Rates via Vernacular Social Media Signals & Deep Learning
International Journal of Forecasting
June 1, 2026 – Present
AQE-FinLLM: Adaptive Quantile Ensemble with FinLLM Sentiment for Tail-Risk Estimation
IEEE Computational Intelligence in Financial Engineering and Economics (CIFEr) 2026
June 1, 2026 – Present
Whose Voice Counts? Bridging the Digital Consultation Gap with NLP & Synthetic Citizen Population
ICSC 2026, Springer CCIS (Oxford University)
June 1, 2026 – Present
DIRA: A Deep Indel Refinement Framework for Genomic Variant Calling
17th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from AI-powered e-consultation platforms to carbon-aware microgrid optimization and quantitative finance, demonstrates a broad interest in applying AI to various real-world problems. Their involvement in multiple hackathons and leadership positions (Student Relations Executive, Operations Team Executive) suggests a proactive, innovative, and collaborative spirit. The blend of technical depth and business acumen aligns well with a dynamic, results-oriented culture often found in AI engineering teams.
Soft Skills & Operational Fit
The candidate's project descriptions highlight collaboration with teammates, cross-functional teams, and stakeholder engagement, suggesting good teamwork and communication skills. Experience in business analytics and product strategy indicates an understanding of business impact and data-driven decision-making. The remote work experience also points to self-discipline and adaptability.