class MLScientist:
def __init__(self):
self.name = "Ashutosh Mishra"
self.role = "Machine Learning Scientist & AI Systems Engineer"
self.expertise = [
"Scalable ML Systems", "Adversarial Robustness",
"LLM Engineering", "MLOps Architecture"
]
self.current_focus = "Next-gen AI Security & Intelligent Automation"
self.seeking = "Full-time opportunities in ML Research + Engineering"
def get_passion(self):
return "Building robust AI systems that solve real-world problems"🔬 Research-Driven • 🛠️ Engineering-Focused • 🚀 Innovation-Minded
|
|
|
Primary Languages: Python • JavaScript • C++ • Jupyter Notebook • TypeScript • CSS
Breakthrough Architecture: FF-MB-APUF design for enhanced entropy & ML attack resistance
| 🎯 Impact | ⚡ Performance | 🔧 Tech Stack |
| 8% ↓ Attack Accuracy 50M CRPs Dataset |
24h → 2h Training JAX/CuPy Optimization |
Python • JAX • CuPy NumPy • CUDA |
🏆 DEI Award Winner | Purdue Research Symposium
graph TD
A[User Query] --> B[GPT-4o Processing]
B --> C[RAG Vector Search]
C --> D[3D Navigation Engine]
D --> E[MappedIn API Integration]
E --> F[Interactive Response]
style A fill:#00D4FF,stroke:#ffffff,color:#000000
style F fill:#FF6B35,stroke:#ffffff,color:#000000
Tech Stack: GPT-4o • Gemini • LangChain • Vector Search • Embeddings • 3D WebGL
| Metric | Improvement | Baseline |
|---|---|---|
| BLEU Score | +20% | T5/BART |
| Inference Latency | -10% | Standard Transformers |
| Memory Efficiency | +15% | Parallel Processing |
Innovation: Adaptive attention layers with parallel encoder paths for optimized performance.
# Architecture Highlights
recommendation_engine = {
"collaborative_filtering": "Matrix Factorization + Deep Learning",
"content_based": "Audio Feature Extraction + Embeddings",
"real_time_processing": "Flask + GraphQL + WebSocket",
"performance_gain": "40% latency reduction"
}🧰 Detailed Tech Stack
Programming:
- Python: Advanced (TensorFlow, PyTorch, Scikit-Learn)
- C++: Systems Programming & Performance Optimization
- JavaScript: Full-Stack Development & API Integration
- SQL: Complex Queries & Database Design
- MATLAB: Mathematical Modeling & Simulation
ML/AI Frameworks:
- Deep Learning: TensorFlow, PyTorch, JAX
- NLP: HuggingFace Transformers, LangChain, OpenAI API
- Computer Vision: OpenCV, PIL, Detectron2
- MLOps: MLflow, Weights & Biases, Azure ML Studio
Cloud & DevOps:
- Platforms: Azure, GCP, AWS
- Containers: Docker, Kubernetes
- Orchestration: Apache Airflow, Prefect
- Monitoring: Grafana, Prometheus, ELK Stack
Specializations:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Adversarial Machine Learning
- Real-Time Analytics & Streaming
- Security-First ML Design
Donna AI Assistant |
Leadership Excellence |
100+ Bot Migration |
Security Specialist |
ML Security Research |
JAX/CuPy Implementation |
mindmap
root((ML Innovation))
LLM Engineering
RAG Systems
Fine-tuning
Prompt Engineering
Security Research
Adversarial ML
Robust Training
Attack Mitigation
MLOps Architecture
Scalable Pipelines
Real-time Inference
Model Monitoring
AI Systems
Intelligent Automation
Multi-modal AI
Edge Deployment
🚀 Ready to tackle challenging ML problems and build impactful AI systems
⚡ "Innovation distinguishes between a leader and a follower" - Steve Jobs