Hi There,
I'm Shivashish Prusty
i am into
About Me
I grew up obsessed with two things: how people behave, and how systems behave.
Somewhere between hacking together my first websites and training my first neural nets,
I realized I could bend both—if I designed them carefully enough.
Designing AI systems that change how teams,
cities, and customers actually behave. Right now I’m a B.Tech CSE (AIML) student
at LPU, but I operate like an R&D engineer: I’ve shipped n8n/LangChain automations
that shrink 6‑hour manual workflows into ~15‑minute, 97%‑accurate runs with 99%+
uptime for real clients, computer‑vision platforms that detect floods from satellite
imagery and score heart‑risk from clinical data with near‑clinic AUC‑ROC, and
diffusion‑based virtual try‑on that runs directly on e‑commerce sites to quietly reduce
returns and lift conversions.
My favourite problems sit where AI, product, and people intersect. I think
in pipelines and interfaces at the same time – from Python, FastAPI and model training,
to React/Next.js frontends and the tiny UX details that make non‑technical users say “ohhh,
now I get it.
If you’re looking for someone who can talk loss functions with your ML team, ship production code
with your engineers, and still explain it all to a founder or doctor in plain language – that’s
the kind of work I wake up excited to do.
email : shivashishprusty@gmail.com
place : Jalandhar, India - 144411
Architecting high-performance systems from deep neural representations to tactile user interfaces.
Education is not the learning of facts, but the training of the mind to think.
School Of Computer Science and Engineering | LPU
D.A.V Public School | CBSE
March 2024 - May 2024 · Hyderabad, Telangana
April 2024 - June 2024 · Remote
January 2024 - February 2024 · Bengaluru, Karnataka
December 2023 - Present · Punjab, India
Every credential below is battle-tested expertise — from Google's flagship AI/ML internship to cutting-edge Generative AI & Deep Neural Architectures.
Official government-backed program mastering supervised learning pipelines, MLOps foundations, and production-grade model deployment under Google's mentorship.
End-to-end LLM lifecycle mastery — pre-training, RLHF fine-tuning, RAG pipelines, and deploying enterprise GenAI systems on AWS cloud infrastructure.
Industrial neural network engineering — CNNs, RNNs, transfer learning, and hyperparameter optimization built on IBM's AI stack using Keras and TensorFlow.