New York University
- Database Systems, Operating Systems, Social Networks
- Data Analytics and Visualization in Healthcare, DevOps and Agile Methodologies
- Cloud and Machine Learning, Data Science for Business, Responsible Data Science
Welcome
I'm Aditya Dixit
Healthcare data science, AI & scalable computing
Machine learning, clinical analytics, cloud-based AI systems, and observability frameworks for high-performance, real-time healthcare applications.
Summary
Passionate about the intersection of healthcare data science, artificial intelligence, and scalable computing, I bring a strong foundation in machine learning, clinical analytics, cloud-based AI systems, predictive models, and observability frameworks that support high-performance, real-time healthcare applications. My academic and professional work spans clinical outcome modeling, geospatial health analytics, and medical data visualization, where I apply rigorous statistical and computational methods to translate complex patient data into actionable insights.
Education
University of San Francisco
- Python, Java, C, Software Development, Computer Architecture
- Blockchain, Tableau, Data Visualization, Machine Learning, Artificial Intelligence
Certifications
Professional Experience
Data Science Analyst
Icahn School of Medicine, Mt Sinai New York, NY, USA January 2026 – Present- Building machine-learning driven clinical data pipelines integrating patient records, imaging, biopsy, and surgical data to generate real-time insights for diagnosis, risk assessment, and treatment planning.
- Developing AI-powered analytics workflows that translate complex patient and surgical data into actionable clinical intelligence, supporting personalized care, improved surgical decision-making, and better patient outcomes.
Senior Software Engineer
HCL Tech Frisco, TX, USA May 2025 – January 2026- Integrated React/TypeScript front-end applications with Python-based backends (FastAPI) to deliver key features across a custom agentic AI framework.
- Designed and implemented modern, responsive UI components supporting complex user flows, including intelligent parsing interfaces and real-time insights for an optimal experience.
Software Engineer
Modern Management Hotels Columbus, OH, USA December 2024 – May 2025- Developed scalable workflows to automate routine hotel maintenance tasks using a custom ticketing system built with a Flask-based API, React, and PostgreSQL, ensuring seamless task assignment and resolution.
- Designed AI-driven tools for hotel management and investor portfolio dashboards with predictive analytics.
Site Reliability Engineer
NIKSUN Princeton, NJ, USA August 2023 – October 2024- Monitored Kubernetes clusters with Prometheus and Grafana, ensuring high reliability and uptime across environments.
- Implemented NVIDIA GPU nodes into Kubernetes clusters for machine learning workload optimization.
- Managed Jenkins pipelines to deploy applications and services for overall cluster maintenance.
- Developed Python scripts for observability, generating real-time insights into hardware and software metrics.
Data Science Intern
Glocol Networks Sacramento, CA, USA September 2022 – December 2022- Deployed IoT solutions using AWS Greengrass and Raspberry Pi, capturing real-time data for transit systems.
- Collaborated with urban planners to enhance analytics for mobility infrastructure and passenger data accuracy.
- Designed dashboards to visualize mobility insights, supporting smarter city initiatives.
Junior Solution Designer Intern
OneReach.ai Denver, CO, USA June 2022 – August 2022- Created conversational AI chatbots with integrations for Slack, SMS, and web-based platforms.
- Enhanced user experiences by implementing streamlined workflows and applying key UX principles.
iOS Tech Fellow (volunteer)
CodePath.org San Francisco, CA, USA October 2020 – May 2022- Taught and mentored students in iOS app development during weekend sessions, guiding them through technical concepts, coding exercises, and best practices in CodePath's Connected Classroom program.
- Facilitated group projects, encouraging collaboration and teamwork while providing support to ensure successful completion of app development assignments.
Course Assistant
New York University New York, NY, USA September 2021 – December 2021- Advising students regarding solutions and techniques for data algorithms courses.
- Created guides for students to be able to revise their knowledge.
Data Science Intern
Axians Remote July 2021 – August 2021- Collaborated remotely with Axians Location Intelligence Team to create machine learning algorithms using satellite images to determine whether vegetation growth will interfere with power line construction.
- Devised a Google Colab & Earth app engine using geospatial data to do image classification with Sentinel 2 images for vegetation management with random forests with categorized pixels using a color cart and analyze data to predict over 95% accuracy to overlay the geographical data.
Computer Science Tutor
University of San Francisco San Francisco, CA, USA August 2019 – May 2020- Provided office hours in the computer labs to help students with Java, Python, data structures, and C to debug their code and explain advanced concepts.
Teaching Assistant
University of San Francisco San Francisco, CA, USA August 2018 – December 2019- Supporting the teacher in daily classroom operations for CS 110 Python class and assisting pupils.
- Included grading of projects and labs and holding multiple weekly office hours to help students succeed in the course.
Projects
Metahuman
- Built an AI-powered conversational avatar platform that generates real-time human-like video responses from user text.
- Engineered a low-latency token streaming system with sentence detection and intelligent buffering, enabling sentence-by-sentence video generation, optimized for natural speech synthesis and smooth visual delivery.
Property Management System
- Built a scalable ticketing and service-request system for multi-property operations using Flask, React, and PostgreSQL, enabling real-time creation, tracking, and assignment of tickets, rooms, and maintenance tasks.
- Implemented role-based access control, live dashboards, and exportable reporting to provide secure user management, real-time operational visibility, and data-driven decision-making.
Observability Monitoring Tool
- Created a service running Python and Bash scripts at set intervals to collect key metrics like disk, memory, CPU usage, network activity, and the state of Kubernetes and Ceph.
- The JSON structure enabled efficient data processing, providing real-time insights and pattern recognition to maintain service health and performance and via telemetry observability logs to be sent to an analysis machine.
Technical Audit of Automated Decision-Making Systems for Early Alzheimer's Diagnosis
- Conducted technical audits on the top 2 Automated Decision-Making Systems (ADS) focusing on early Alzheimer's diagnosis with cross-sectional and longitudinal MRI data, respectively.
- Showcased the analysis that aimed to address biases and errors in these healthcare systems and improve their accuracy and efficiency to ensure the models were being used ethically.
Analyzing Restaurant Success in New York City
- Developed a system to analyze and predict the success of future restaurants in the New York City tri-state area based on attributes such as price, location, and category.
- Used a proxy for success that took into account both restaurant ratings and turnover to better capture the profitability of a given venture.
Comparative Study of Deep Learning Model Deployment
- Conducted a comparative study on deploying a deep learning model with MLFlow on Kubernetes clusters across public cloud platforms.
- Tracked model performance metrics, including training time, job execution time, test loss, and data loading time providing insights into factors influencing cloud platform selection for MLFlow deployment.
Customer Accounts Implementation
- Implemented a scalable RESTful API Flask microservice with CRUD functionality using CI/CD pipelines, Kubernetes deployment using Docker, and automated BDD testing with UI integration.
- Established a 4-stage DevOps pipeline with IBM Cloud, integrated with GitHub, to streamline microservice processes, ensuring seamless deployment with TDD unit and BDD integration tests.
Investigating Socio-Economic Factors and Their Impact on Covid-19 Fatality Rates
- Investigated COVID-19 fatality rate correlations with socio-economic factors like GDP, HDI, and hospital infrastructure, modeling trends in highly affected countries using machine learning.
- Visualized clinical data from the MIMIC-III Database, enabling accessible insights for healthcare researchers and administrators.
Fire Predictor
- Attempted to create a model that predicts the locations of optimally controlled wildfires in northern California.
- Included data gathering from multiple geographical data sources, cleaning and analysis, and the use of multiple machine learning models to provide insights based on where the next human-induced wildfire could occur.
Senior Team Project – Healthcare Dashboard
- Designed and implemented multiple dynamic, interactive charts using D3.js on the frontend, showcasing a wide variety of clinical data and enabling users to explore healthcare trends and correlations effectively.
- Developed a comprehensive healthcare dashboard leveraging MIMIC-III data, providing diverse visual insights tailored to researchers, hospital administrators, and data enthusiasts.
AdityaKiwi
Technology moves fast—learning doesn’t have to be overwhelming. At AdityaKiwi I’m building a space where you:
- Learn to code with the help of AI tools
- Understand how AI thinks so you can code smarter
- Stay curious, creative, and confident as tech evolves
What you’ll find
Whether you’re a student, self-taught developer, or curious about AI—this is your place to explore the future of coding.
Get in touch
Suggestions, collaborations, or just saying hi—I’d love to hear from you.