Hello, my name is
Kiran Dhana
AI Enthusiast
- dkiran100@gmail.com
- 917-293-3313
I build cool AI bots
I’m Kiran Dhanasekaran, an AI enthusiast and Computer Science graduate student at NYU with a strong foundation in machine learning, computer vision, and deep learning. With hands-on experience from institutions like MIT and IIT, and a solid track record in developing robust AI models, I specialize in building intelligent, secure systems that solve real-world problems—from financial forecasting to robotic manipulation. This portfolio showcases my passion for AI, innovative projects, and commitment to advancing human-centered technology.
Beyond technical proficiency, I bring a multidisciplinary approach to AI development—blending statistical insight, creative problem-solving, and full-stack engineering skills. Whether designing secure LLM frameworks or building real-time fintech applications, I prioritize performance, safety, and scalability. My work is driven by curiosity and a deep desire to push the boundaries of what AI can achieve, especially in domains like mental health, education, and human-robot interaction.
What I do
AI DEVELOPMENT
I design and optimize machine learning models with real-world applications—from adversarial LLM safety systems to vision-language robotics. My solutions focus on performance, robustness, and responsible AI deployment.
DATA SCIENCE & ANALYTICS
I leverage advanced statistical tools and predictive modeling to uncover insights and drive smarter decisions. My experience includes time series forecasting, classification systems, and real-time data analysis using Python, R, and modern BI tools.
CLOUD & FULL-STACK ENGINEERING
Whether building scalable fintech platforms or mental health apps, I deliver full-stack solutions using React, Spring Boot, and cloud platforms like AWS and GCP. My work integrates secure architecture, fast deployment, and seamless user experiences.
Skills
My Experience
2022–2023
Massachusetts Institute of Technology
STATISTICS INTERN
I developed and optimized CPI forecasting models using ARIMA and Seasonal ARIMA in R, achieving a 10% boost in predictive accuracy. Co-authored a published research paper with Dr. Peter J. Kempthorne, enhancing model reliability through robust statistical evaluation.
2022
Illinois Institute of Technology
DATA ANALYST
Led data extraction, transformation, and analysis using Pandas, Power BI, and Tableau to refine advertising strategy. Identified costly campaigns and cut expenses by 20%, resulting in more efficient ad spend and higher campaign ROI.
2022
Wipro – Velocity Cognitive Data Science Program
DATA SCIENCE INTERN
Built and deployed classification models using SVM, decision trees, and CNNs. Achieved 96% accuracy on the Iris dataset and 95% precision on credit card default predictions. Earned top performance recognition with an A grade and 84.4% overall score.
