Computer Science graduate student @DePaul University, specializing in AI/ML and Systems & Software Development | 2+ years in Backend & Data Science | Involved heavily in my Professional Research on LLMOps & Code Refactoring currently | AWS Certified Cloud Practitioner | Seeking CPT opportunities in AI/ML & SDE roles in the US
- Production-grade MLOps/LLMOps framework for LLM-based code refactoring (with GNNs, robustness distillation, RAG, MLflow monitoring) - research with Prof. Vahid Alizadeh @ DePaul University
- Hybrid Prophet + LSTM energy consumption forecasting with real-time weather API & NLP features
- Advanced LLMOps, Graph Neural Networks for code understanding, efficient distillation techniques
- Kubernetes for scalable ML deployments, more AWS services (Solutions Architect in progress)
Feel free to explore my repos below or reach out on LinkedIn! 🚀
class Kalyan:
def __init__(self):
self.name = "Kalyan Venkatesh"
self.role = "AI/ML Graduate Student & Software Engineer"
self.location = "Chicago, Illinois, USA"
self.education = "MS Computer Science @ DePaul University (Sep 2024 – Jun 2026) | BTech @ NIT Nagpur (2017–2021)"
self.gpa = "3.80/4.0"
self.experience = "3+ years (Backend Developer & Data Scientist @ sensen.ai | Engineer @ AECOM/Siri)"
self.passions = [
"Production-grade MLOps / LLMOps pipelines",
"Robust LLM agents for code refactoring (GNNs, distillation, RAG)",
"Time-series forecasting with real-world deployment & impact",
"Scalable cloud-integrated ML systems (AWS, Docker, Kubernetes)"
]
self.personality = "Driven • Curious • Results-oriented • Team player"
def get_expertise(self):
return {
"languages": ["Python", "Java (with Data Structures & Algorithms)", "C", "JavaScript", "SQL"],
"ai_ml": ["PyTorch", "TensorFlow", "Scikit-learn", "Prophet", "LSTM", "Hugging Face", "NetworkX", "GNNs", "RAG", "MLflow", "SHAP"],
"tools": ["Streamlit", "GridSearchCV", "OpenWeather API"],
"cloud_devops": ["AWS (Cloud Practitioner certified, Solutions Architect in progress)", "Docker", "Kubernetes", "MLOps/LLMOps", "ETL pipelines"],
"databases": ["PostgreSQL", "Oracle SQL", "MySQL"]
}
def career_highlights(self):
return [
"🔬 Research: Production-grade LLMOps for code refactoring — robustness distillation + GNNs + MLflow monitoring (targeting ICML/KDD 2026)",
"⚡ Energy Predictor: Hybrid Prophet + LSTM (6% MAPE, +12% precision via NLP/weather, 15% projected CO₂ savings)",
"🏭 sensen.ai: 40% latency reduction, 20% downtime cut, 2× ETL efficiency; led drone pollution detection R&D (30–35% impact potential)",
"🎓 AWS Certified Cloud Practitioner | Mentored interns | Owned analytics pipelines"
]
me = Kalyan()- 🔭 Currently Working On: MLOps/LLMOps pipeline for LLM-based code refactoring (robustness distillation + GNNs + RAG + monitoring) with Prof. Vahid Alizadeh @ DePaul
- 🎓 Education: MS CS @ DePaul (AI/ML & Systems specialization, expected Jun 2026) | BTech @ NIT Nagpur
- 💼 Experience: Software Engineer (Backend & Data Science) @ sensen.ai (2022–2024) – APIs, ETL, analytics, ANPR pipelines | Engineer @ AECOM/Siri (2021–2022) – infrastructure data integration
- 🤖 Focus: End-to-end ML deployment, scalable systems, production AI reliability
- ☁️ Also Skilled In: Cloud-native ML (AWS/Docker/K8s), time-series + NLP integration, DSA in Java/Python
- 📫 Reach Me: adavivenkatesh@gmail.com | LinkedIn
- ⚡ Fun Fact: I turn complex data problems into clean, deployable solutions—usually fueled by green tea and early morning sessions!
Python • Java (with Data Structures & Algorithms) • SQL • C • JavaScript
PyTorch • TensorFlow • Scikit-learn • Hugging Face • Prophet • LSTM • NetworkX (GNNs) • RAG • MLflow • SHAP
AWS • Docker • Kubernetes • MLOps/LLMOps • Streamlit • GridSearchCV • OpenWeather API
PostgreSQL • Oracle SQL • MySQL