βββββββββββββββββββββββββββββββββββββββββββββββ
π Google BigCode Program Β β’Β πΌ 4+ Internships Β β’Β π SparkTank Finalist Β β’Β π¬ Research Intern @ IIT Ropar Β β’Β π Aspire Leaders Finalist Β β’Β π Summer Projects '26 @ IIT Guwahati
I'm a pre-final-year B.Tech in AI & ML student at Vishnu Institute of Technology (CGPA 8.78/10), currently a Research Intern at the VLED Lab, IIT Ropar, contributing to open-source AI/ML projects β alongside a graph-based ML project for large-scale relational data at IIT Guwahati. I like problems that involve a graph, a deadline, and a model that refuses to converge on the first try.
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π΅ Β Building β deep learning & computer vision systems that ship, not just notebooks that run π’ Β Learning β MLOps, system design, scalable model deployment π£ Β Researching β graph-based ML for relational data @ IIT Guwahati π‘ Β Open to β open-source AI/ML & data science collaborations |
π΅ Β Need help with β scaling ML models for production π’ Β Ask me about β Computer Vision, Deep Learning, Graph Analytics, Python for ML π£ Β Currently β Pre-final-year B.Tech, AI & ML β CGPA π‘ Β Fun fact β I'll happily burn an hour of compute for one extra point of accuracy |
| Role | AI / ML Engineer |
| Institution | Vishnu Institute of Technology |
| Year | Pre-Final Year (3rd Year) |
| CGPA | 8.78 / 10 |
| Current Focus | Summer Research Intern @ VLED Lab, IIT Ropar |
| Strength | Squeezing one more % of accuracy out of any model |
| Recognition | Google BigCode Program β selected for DSA & algorithmic problem-solving |
Core Skills
| Skill | Proficiency | Level |
|---|---|---|
| Python for ML | ββββββββββββββββββββ 95% |
Expert |
| Data Analysis / EDA | ββββββββββββββββββββ 95% |
Expert |
| Computer Vision | ββββββββββββββββββββ 85% |
Advanced |
| Deep Learning | ββββββββββββββββββββ 80% |
Advanced |
| DSA & Software Dev | ββββββββββββββββββββ 80% |
Proficient |
Unlocked skills feed into the next tier β the frontier node is where I'm actively grinding XP right now.
flowchart TD
A[["Foundations<br/>Python Β· Math Β· DSA"]] --> B[["Core ML<br/>NumPy Β· Pandas Β· scikit-learn"]]
B --> C[["Deep Learning<br/>TensorFlow"]]
C --> D[["Computer Vision<br/>OpenCV Β· YOLOv8 Β· MediaPipe"]]
C --> E[["Applied Systems<br/>FastAPI Β· Streamlit Β· Power BI"]]
D --> F(("Open-Source Contributions<br/>VLED Lab, IIT Ropar"))
D --> I(("Graph-Based ML<br/>IIT Guwahati"))
E --> G(("MLOps & System Design<br/>in progress"))
F --> H{{"Production-Grade AI"}}
I --> H
G -.-> H
classDef unlocked fill:#4F8EF7,stroke:#0D1117,color:#0D1117,stroke-width:2px;
classDef mastered fill:#2EC4B6,stroke:#0D1117,color:#0D1117,stroke-width:2px;
classDef inprogress fill:#0D1117,stroke:#F4B740,color:#F4B740,stroke-width:2px,stroke-dasharray:4 3;
classDef frontier fill:#141B2D,stroke:#A78BFA,color:#A78BFA,stroke-width:3px;
class A,B unlocked;
class C,D,F mastered;
class E,G,I inprogress;
class H frontier;
How the CGPA, the internships, and the research fellowship actually line up.
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