SHAUNAK
MISHRA
ML Researcher
Computer Vision Engineer and ML Researcher. Specialized in medical imaging segmentation, deep learning model benchmarking, and building production fullstack systems.
8.72
SOA CGPA
250+
DSA SOLUTIONS
19
MS AI BADGES
Shaunak Mishra
Computer Science & Engineering Scholar • SOA University
BACKGROUND & NARRATIVE
Shaunak Mishra
SOA University (ITER), Bhubaneswar (CGPA: 8.72)
Pioneering adaptive algorithms in Deep Learning, Computer Vision, and modular web structures that deliver impactful diagnostics.
As a Computer Science Scholar closely tracking the rapid transition of AI from research to real-world deployment, I enjoy building at the boundary of machine learning theory and highly polished, scalable systems engineering.
My research interests focus on convolutional segmentation architectures designed for clinical brain tumor diagnosis from raw MRI. Along with theoretical exploration, I develop end-to-end web frameworks mapping agent actions, node graph operations, and audio diagnostics.
Tech Stack Focus
Key Statistics
DSA Solutions
LeetCode & GFG algorithmic keys
ML Architectures
Implemented CV & deep networks
Software Projects
Fullstack platforms & products
MS Learn Badges
Academic cloud credentials
Education & Research Timeline
B.Tech Student (CSE)
2022 – 2027SOA University (ITER), Bhubaneswar
CGPA: 8.72 / 10.0
In-depth specialization in Computer Vision, Advanced Data Structures, Operating Systems, and Relational Databases.
Frontend Developer
Jun 2025 – Aug 2025CN Nexus — Coding Ninjas Club, SOA University
Improved problem discovery speed by 30% by building topic-wise categorization and memoized search filters for a DSA platform aggregating LeetCode, GFG, and Codeforces
Founding Engineer
Dec 2025 – Mar 2026Mentomania
Designed and built complete frontend UI/UX for a government exam mentorship platform, delivering full product from design to deployment
COMPUTER VISION IN MEDICAL IMAGING
Benchmarking 14 classification and 10 segmentation architectures on the BRISC2025 dataset (6,000 T1-weighted MRI slices, 4 classes). Published pipeline combines MambaOut classification with SwinSeg segmentation and GradCAM++ explainability.
MambaOut + SwinSeg Pipeline
Raw MRI Intake
Ingest high-res DICOM scans spanning T1-CE, T2, and FLAIR profiles.
Preprocessing
Apply pixel normalization, non-local means filtering, and spatial resizing.
MambaOut Classifier
State-space model classifies tumor type from preprocessed MRI slices.
SwinSeg Segmentation
Swin Transformer-based decoder extracts precise tumor boundaries.
GradCAM++ Map
Generate activation heatmaps revealing backprop weights on diagnostic regions.
MRI Diagnostic Sandbox Waiting
Pick a patient MRI scan from the left stack and click "Examine MRI" to boot model pipeline.
PAPER IN PREPARATION
Comprehensive Benchmarking of Deep Learning Architectures for Brain Tumor Classification and Segmentation on BRISC2025
Systematic evaluation of 14 classification models and 10 segmentation architectures on 6,000 T1-weighted MRI slices. The proposed MambaOut + SwinSeg pipeline with GradCAM++ explainability achieves state-of-the-art results under faculty supervision at SOA University.
ADVANCED ENGINEERING WORK
Active Projects
OS Contributions
Featured Projects
WorkflowOS
FastAPI
AI agent swarm that converts meeting transcripts into execution plans. Microsoft Build AI Hackathon 2026.
Brain Tumor Detection
Python
Medical image classification & segmentation research. 14 classification + 10 segmentation architectures benchmarked on BRISC dataset (6,000 MRI scans).
MentorHub / MentoMania
Next.js
Mentorship platform connecting students with exam toppers (IIT-JEE, NEET, CAT, UPSC).
AI Vehicle Health Diagnostics
Next.js
AI/ML-based vehicle health diagnostics, predictive maintenance, and driving simulation.
Metal Defect Detector
Python
Surface defect detection on metal surfaces using deep learning.
AI Resume Analyzer
React Router
AI-powered resume parsing and scoring with Docker deployment.
Civic Issue System
React
Platform for civic issue reporting and tracking.
openfoodfacts-nodejs
TypeScript
PR #646 merged into v2.0.0-alpha.8. Added getProductImageFolder() to production SDK.
leetsync-organizer
Python
Python tool that auto-categorizes LeetCode solutions into difficulty folders via GitHub Actions.
DSA-Solve
C++
250+ DSA problems solved in C++ covering Arrays, DP, Graphs, Trees, Binary Search.
Nexus-E1
TypeScript
DSA platform aggregating LeetCode, GFG, and Codeforces problems.
COMPETENCY CONSTELLATION
Active Learn Domain
Multi-Modal Vision Transformers & Mamba Architectures
Studying self-attention maps in transformers under spatial limits to identify multi-task medical annotations.
CONSTELLATION READOUT: MACHINE LEARNING & CV
Advanced Deep learning networks, image segmentation pipelines, object detection models, diagnostic heatmapping.
Applied: Researched BRISC architectures on glioma patient MRI brain scans.
Applied: Isolate tumor contours on raw glioma patient MRI brain scans.
Applied: Implemented residual and transformer pipelines within video diagnostics.
Applied: Map backpropagated dense weights to display activation heatmaps.
Applied: Trained spectrogram diagnostic classifications for sound models.
DATA STRUCTURES & COMPETITIVE CODE
/**
* @file dijkstra.cpp
* @brief Verified sub-15ms Dijkstra Shortest Path Solution
*/
#include <vector>
#include <queue>
using namespace std;
class ShortestPathSolver {
public:
vector<int> matchPath(int N, vector<vector<pair<int, int>>>& adj, int src) {
vector<int> dist(N, 1e9);
priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq;
dist[src] = 0;
pq.push({0, src});
while(!pq.empty()) {
int d = pq.top().first;
int u = pq.top().second;
pq.pop();
if(d > dist[u]) continue;
for(auto& edge : adj[u]) {
int v = edge.first;
int weight = edge.second;
if(dist[u] + weight < dist[v]) {
dist[v] = dist[u] + weight;
pq.push({dist[v], v});
}
}
}
return dist; // Time: O(E log V) matched
}
};DSA-Solve Hub Repository
Holds production implementations of graph traversal, dynamic programming structures, trees maps. Underpinned by speed analysis test units.
JOURNEY & CREDENTIALS
Chronological Journey Timeline
Introduction to Software Engineering
IBM via Coursera
Runner-Up, SOA University Chess Tournament
SOA University
Secured runner-up position in university-level chess tournaments two consecutive years.
Mastering AI and Data Science — Design and Build Intelligent Solutions
IIT (ISM) Dhanbad & TCS iON
Completed intensive course organized by IIT Dhanbad in collaboration with TCS iON. Sep–Nov 2025. Certificate ID: 25231210471.
Smart India Hackathon 2025
Ministry of Education, India
Problem Statement #95 — Participated in SIH 2025 at university level (SOA University).
Microsoft Build AI Hackathon 2026
Microsoft
Built WorkflowOS — AI agent swarm converting meeting transcripts to execution plans. Track: Agent Swarms.
Verified Microsoft Learn credentials spanning AI, security, compliance, and infrastructure.
Design a dream destination with AI
Introduction to Microsoft security solutions
Introduction to security, compliance, and identity concepts
Describe the concepts of cybersecurity
Search and investigate with Microsoft Purview Audit
Design a dream destination using Microsoft Copilot
Describe threat protection with Microsoft Defender XDR
Describe security management capabilities in Azure
SECURE AN APPOINTMENT
Authorized Channels
UTM ZONE: 45Q
LAT: 20.2961° N | LON: 85.8245° E
Bhubaneswar, Odisha, India
Siksha 'O' Anusandhan University Campus Area, Bhubaneswar.