Stabak Nandi

I am a Lead Data Scientist with 11 years of experience in Healthcare AI, specializing in Clinical Diagnostics, Medical Coding and Real-World Evidence. My expertise spans Surgical Robotics, Clinical Trials, Drug Engineering, Medical Data Governance, Pharmacovigilance, Medical Devices and Computational Biology. I have led and architected Machine Learning and NLP projects, developed scalable Data Solutions, and implemented Deep Learning applications in various Healthcare contexts. Proficient in Python, R, Neural Networks, Computer Vision, Natural Language Processing, and MLOps, I excel at driving projects from conception to deployment, ensuring impactful outcomes and continuous improvement in Healthcare AI initiatives. As a collaborative team player with strong leadership and interpersonal skills, I am committed to advancing innovation and excellence in the healthcare sector.

PROJECTS

Developed an ensemble Machine Learning model to automate Medical Coding for hospital billing, improving accuracy and efficiency by utilizing NLP and Deep Learning techniques on Clinical Notes and Patient Records.
Detected vaccination adverse events using Transformers (Clinical BERT) and integrated MedDRA and UMLS Metathesaurus. Mined adverse events from Covid vaccination drives using social media data and NLP techniques.
Discovered optimal treatment effect subgroups for Multiple Myeloma and Lung Cancer. Conducted Survival Analysis, including DFS, RFS, and Kaplan-Meier, for Isatuximab versus Daratumumab.
Implemented dynamic treatment regimes in sequential multiple assignment randomized trials (SMART) to improve patient outcomes through adaptive and personalized treatment plans.
Worked on motion and path planning of robotic arms, developed intelligent diagnostic Computer Vision applications for endoscopic cameras, and created a 2D overlay-based GUI for the surgeon command center.
Developed algorithms to enhance the quality and accuracy of Medical Imaging for diagnostic purposes and classified tumors from MRI using Deep Learning and Neural Networks.
Developed Computer Vision-based tool tip tracking systems for automated endoscopic applications.
Analyzed handwritten prescription data to predict Medical Diagnostics and detect anomalies in doctor referral patterns using Natural Language Processing techniques.
Worked on Computer Vision-based real-time robotic surgical cart position registration systems.
Researched and developed supervised Edge Detection Algorithms and 2D images to 3D Point Cloud Reconstructions and Photogrammetry for expert Medical Imaging and Endoscopic Applications.
Developed solutions for Smart Dairy Monitoring using beacons, Raspberry Pi, and advanced Computer Vision techniques.
Developed an asset management system for monitoring Airtel Telecom assets using advanced IoT solutions.
Designed a system for deriving statistical summary insights from internal travel portal data, led a team to develop the Auto ML platform 'DataProbe' for banking institutions, and managed the Guided Resolution project.
Managed and led the team for building a predictive decision support system for Dell Support Assist 2.0, involving Machine Translation, alert monitoring, and decision support.
Worked in Deep Reinforcement Learning for optimizing bidding strategies in Group Procurements project.
Developed a spelling correction model for dyslexic children using Neural Networks.
Worked on speech recognition-driven motion systems for endoscopic surgical single arms.
Built a recommender system and customer segmentation models for PayUMoney using credit card transaction data.
Researched and developed Bayesian Clustering for engineering an NLP based recruitment job recommender system.
A hybrid genetic algorithm to learn the Directed Acyclic Graph structure of Bayesian Networks built from Severe Ventilator-Associated Pneumonia NHS survey datasets and an analysis of the scoring functions for the Directed Acyclic Graphs. [Academic Project]
Contributed to the development of Charlie, an anthropomorphic robotic head at the University of Southampton. The project focused on biologically inspired Robotics, integrating sensors and actuators for human-like facial expressions and interactions using Arduino, capacitive, and piezoelectric sensors. [Academic Project]
Participated in the worldwide Trading Agent Competition and represented the team as an Individual Research Project for extra credits in Intelligent Agents. [Academic Project]
Developed intelligent systems for the University of Essex's iDorm project, integrating AI for automation and smart control. Worked on sensor data integration, real-time monitoring, and predictive analytics to enhance the functionality and efficiency of smart home environments. [Academic Project]

• Coursera - Machine Learning
• Coursera - Introduction to Data Science
• Coursera - Neural Networks and Deep Learning
• Coursera - Getting Started with AWS Machine Learning
• John Hopkins University - Essential Epidemiologic Tools for Public Health Practice
• John Hopkins University - Data and Health Indicators in Public Health Practice
• Leiden University - Population Health: Study Design
• Sanofi - RD-WW-MEDICAL-CERT: RWE Generation Lead
• Sanofi - GCL_Pharmacovigilance Reporting Journey
• Udemy - Agile Fundamentals: Including Scrum and Kanban 2020
• Udemy - Scrum Certification Prep + Scrum Master + Agile Scrum Training
• Udemy - Agile Crash Course:
• Udemy - Agile Crash Course: Agile Project Management; Agile Delivery