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Sapna Rawat

@sapnarawat

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PhD researcher in recommendation systems, combining ML development and teaching to build scalable intelligence.

India

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What I'm looking for

I’m looking to apply my PhD-level expertise in recommendation systems to drive innovation in Amazon’s Seller Fulfillment Services. I want to build scalable ML models that improve prediction accuracy and measurable performance using real-world data.

I’m a PhD researcher specializing in recommendation systems, with 3+ years of combined experience in software development and teaching. I enjoy turning large-scale user behavior data into high-impact models, grounded in solid statistical modeling and experimentation.

In my current PhD at Central University of Rajasthan, I design advanced recommendation algorithms using collaborative filtering and hybrid approaches. I also implement deep learning techniques, build prototypes with real-world datasets, and evaluate performance using metrics like RMSE, MAE, Precision, Recall, and NDCG.

I’ve published/presented 2 research papers in international conferences in ML and recommendation systems, and I collaborate closely with research supervisors while writing technical papers. My work is focused on optimization and scalability—so my models don’t just work in theory, they perform reliably on large datasets.

Before research, I gained industry experience as a Junior Java Developer at Enjay IT Solutions, building Java-based enterprise applications with Oracle and SQL in an agile environment. I’ve also taught advanced computer science topics, developing curricula and mentoring students—skills that reflect how I communicate complex ideas clearly and build practical solutions.

Experience

Work history, roles, and key accomplishments

Current

PhD Research Scholar

Current

Central University of Rajasthan

Dec 2023 - Present (2 years 6 months)

Designed and developed machine learning recommendation models using collaborative filtering, matrix factorization, and deep learning, and evaluated performance with RMSE, MAE, Precision, Recall, and NDCG. Published and/or presented 2 international conference papers in ML and recommendation systems.

Recommendation Systems Collaborative Filtering Deep Learning TensorFlow Precision And Recall Feature Engineering

PGT Computer Science

Kendriya Vidyalaya Gachibowli

Jul 2022 - Sep 2022 (2 months)

Taught advanced computer science topics including data structures, algorithms, and programming. Developed lesson materials and delivered practical Python/Java and database sessions while mentoring students for competitive problem-solving.

Computer Science Data Structures Algorithms Python Java Curriculum Development Practical Lab Delivery Student Mentoring Competitive Programming

Computer Instructor

Kendriya Vidyalaya Gachibowli

Jul 2021 - Nov 2021 (4 months)

Delivered comprehensive computer science instruction and programming fundamentals to students. Organized coding workshops and technical competitions to reinforce practical programming skills.

Computer Science Fundamentals Computer Science Instruction Technical Competitions Lesson planning Student Support Java Python Classroom Training

Computer Instructor

Sophia Senior Secondary School

Apr 2014 - Oct 2015 (1 year 6 months)

Taught C, C++, and Java and led practical lab sessions. Created teaching materials and assessment tools and provided project guidance to students.

C++ Programming Java Teaching Tools Assessment Design Student Mentoring Classroom Training

Junior Java Developer

Enjay IT Solutions

Aug 2011 - Dec 2011 (4 months)

Developed Java-based enterprise applications using object-oriented programming principles and implemented database-integrated features with Oracle and SQL. Collaborated in an Agile environment across the full SDLC, debugging and optimizing code to improve performance and reliability.

Java Object Oriented Programming Oracle SQL Agile Development SDLC Debugging Performance Optimization Data Integration Git

Education

Degrees, certifications, and relevant coursework

Central University of Rajasthan

PhD, Computer Science (Recommendation Systems, ML, Deep Learning)

2023 -

Activities and societies: Research area: recommendation systems, machine learning, deep learning. Designing collaborative and hybrid approaches; publishing/presenting 2 papers in international conferences; working on optimization techniques for scalable ML models.

PhD research at Central University of Rajasthan in Computer Science, focusing on recommendation systems, machine learning, and deep learning. Developed and evaluated scalable recommendation models using large-scale datasets and metrics such as RMSE, MAE, Precision, Recall, and NDCG.