Shreyansh Agarwal
Solution Architect at DosePacker Inc.
Ahmedabad, Gujarat, India
Summary
👤
Senior🎓
Top SchoolShreyansh Agarwal is a Solution Architect with nine years of experience designing pragmatic systems for healthcare tech at DosePacker Inc., combining strategic architecture with hands-on implementation. Based in Ahmedabad, he blends data science grounding from internships and early ML projects—customer acquisition, student success prediction, and socioeconomic feature modeling—with production-focused solution design. His background coordinating robotics and embedded-systems education at IITRAM signals a practical, systems-oriented mindset and an ability to translate complex technical ideas into teachable, deployable outcomes. Comfortable with analytics tools and experimentation methodologies, he applies techniques like propensity score matching and stratified CV to inform product decisions. Known as a systemic problem solver, he bridges research-style rigor and startup velocity to deliver measurable outcomes in regulated domains. Colleagues value his knack for turning exploratory models into robust, operational features that move healthcare workflows forward.
9 years of coding experience
High School, High School at Mahaveer Public School, JaipurBachelor's Degree, Bachelor's Degree at Institute of Infrastructure Technology Research and Management (IITRAM)Associate's Degree, Associate's Degree at Cambridge court high school, Jaipur
English, Hindi
Stackoverflow
456reputation
29kreached
18answers
0questions
Github Skills (43)
database-project9
sqlalchemy9
q-learning9
cookiecutter8
semantic-html8
multi-agent-reinforcement-learning7
fastapi7
semantic-web7
python7
deep-reinforcement-learning7
android6
gradle6
css6
java6
print-js6
Programming languages (6)
Github contributions (5)
shreyansh96/dynamic-programming
Dec 2020 - May 2022
Contributions:31 commits, 25 pushes, 1 branch in 1 year 5 months
DosepackAIR/MARL-DPP
Nov 2019 - Oct 2021
Multi Agent Reinforcement Learning for Dense Path Planning
Contributions:4 commits, 2 PRs, 3 pushes in 1 year 11 months
multi-agent-reinforcement-learningreinforcement-learningagentspath-planningq-learning
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