Sayam Palrecha

AI Researcher

Washington, District of Columbia, United States0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in quantitative finance and machine learning.
Experience in developing regulatory data dashboards.
Strong background in healthcare data visualization.

Stackforce AI infers this person is a Data Scientist with a focus on Healthcare and Regulatory Compliance.

Contact

Skills

Core Skills

Data VisualizationMachine Learning

Other Skills

Artificial Intelligence (AI)CanvaCommunicationComputer VisionDeep LearningEngineeringFinancial AnalysisGenerative Adversarial Networks (GANs)Hyperparameter tuningImage ProcessingMicrosoft PlannerObject-Oriented Programming (OOP)Public SpeakingPythonQuantitative Finance

About

I am Sayam, data science major (email - sayam.palrecha@gwu.edu) My research and professional interests lie at the intersection of quantitative finance and machine learning, with a focus on pricing securities Previously worked at Carnegie Mellon University and IIT-Roorkee on complex ideas like 3D cell mapping and Unsupervised Domain Adaptation My research experience and current learnings makes me well round candidate with ability to adapt to high pressure environments to deliver tangible outcomes

Experience

The george washington university- milken institute school of public health

Teaching Assistant

May 2025 – Jul 2025 · 2 mos · Washington, District of Columbia, United States · On-site

Course PUBH 6199: Visualizing Data with R
Grading assignments, conducting office hours, creating course contents

RData Visualization

The george washington university regulatory studies center

Research Specialist (Data Science)

Apr 2025 – Present · 11 mos · Washington, District of Columbia, United States · On-site

Making dashboards using using R and Shiny for regulatory data

RShinyData Visualization

Carnegie mellon university

Research Intern

Jul 2023 – Sep 2023 · 2 mos · Pittsburgh, Pennsylvania, United States · Remote

Worked with optimization techniques like Stochastic Gradient Descent (SGD), batch size and loss functions
Reduced space and time requirements for 3D cell mapping projects through hyper parameter tuning

Stochastic Gradient DescentHyperparameter tuningMachine Learning

Indian institute of technology, roorkee

Research Intern

Jan 2023 – Jun 2023 · 5 mos · Roorkee, Uttarakhand, India · Remote

Contributed to development of a Unsupervised Source-free Domain adaptation model for MRI and CT -scans of lungs for early detection of pneumonia.
Visualized healthcare variables and vitals using python

Unsupervised LearningPythonMachine Learning