Samyak Meshram

Samyak Meshram

Grad Student at Pace University | Creative AI applications | Data Sciences and Analysis Enthusiast

New York, New York, United States
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About

I am a Grad student currently pursuing Masters in Data Sciences at Pace University, with an emphasis on data analysis and artificial intelligence.
I'll be graduating in May 2024 and i plan to pursue a career in data analysis. I am particularly excited about using Artificial Intelligence and Machine learning algorithms to tackle complex problems in various industries. Meanwhile, I continue to acquire skills that will help me achieve my goals, build a solid resume and professional network.

Activity

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Experience

Education

Licenses & Certifications

Publications

  • Inclusion Ethics in AI: Use Cases in African Fashion

    AAAI Press

    This paper addresses the ethics of inclusion in artificial intelligence in the context of African fashion. Despite the proliferation of fashion-related AI applications and datasets, global diversity remains limited, and African fashion is significantly underrepresented. This paper documents two use-cases that enhance AI's inclusivity by incorporating sub-Saharan fashion elements. The first case details the creation of a Senegalese fashion dataset and a model for classifying traditional apparel…

    This paper addresses the ethics of inclusion in artificial intelligence in the context of African fashion. Despite the proliferation of fashion-related AI applications and datasets, global diversity remains limited, and African fashion is significantly underrepresented. This paper documents two use-cases that enhance AI's inclusivity by incorporating sub-Saharan fashion elements. The first case details the creation of a Senegalese fashion dataset and a model for classifying traditional apparel using transfer learning. The second case investigates African wax textile patterns generated through generative adversarial networks (GANs), specifically StyleGAN architectures, and machine learning diffusion models. Alongside the practical, technological advances, theoretical ethical progress is made in defining the ethics of inclusion and contributing to debates on ethical fairness and the pace of AI innovation.

    See publication

Courses

  • Algorithms for Data Science

    CS676

  • Analytics Capstone Project

    CS668

  • Data Mining

    CS619

  • Database Management Systems

    CS623

  • Introduction to Data Science

    CS675

  • Machine Learning

    CS677

  • Mathematical Foundations of Data Analytics

    CS660

  • Practical Data Science

    CS667

  • Python Programming

    CS661

  • Scalable Databases

    CS673

Projects

  • African Elegance in AI: Benchmarking Generative Models on Wax Textile Patterns

    • Lead the training and analysis of StyleGAN and Stable Diffusion models on the university's High-Performance Computing system, involving dataset management, model optimization, and documenting experimental setups and outcomes.
    • Developed and implemented comparative methodologies to evaluate model performance, resulting in enhanced image generation fidelity and providing key insights for ongoing research in generative AI.

  • Stock Market Analysis and Strategy Optimization using Machine Learning

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    • Utilized Python and Yahoo Finance library to derive actionable insights, achieving a 10% increase in investment efficiency through strategic data analysis.
    • Implemented two innovative trading strategies backed by machine learning algorithms, leading to a 15% higher ROI compared to traditional methods.

  • Healthcare Fraud Detection Using Graph Database

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    Spearheaded the creation of a fraud detection system with Neo4j and Python, analyzing complex data relationships within a vast dataset to successfully pinpoint fraud indicators.

  • Weighted DBSCAN Clustering Algorithm Development

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    Innovated a weighted DBSCAN clustering algorithm to enhance accuracy in detecting clusters with varied densities, significantly optimizing performance on large datasets.

    Other creators

  • E-Sports Tournament App & Database

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    • Collaborated in team of five to design desktop application using Django to create backend, connecting frontend UI & SQL databases allowing users to enroll in teams & compete in e-sports tournaments.
    • Created framework to outline application backend, developing tables using SQL to store & maintain user, client, match, & event data

    Other creators

  • Reddit Recommendation System Using Python Neural Networks

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    Engineered a neural network-based recommendation system in Python to personalize subreddit suggestions, utilizing data from the Reddit API to analyze user engagement patterns.

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