Curriculum Vitae
| 📄 Resume |
Professional Experience
National Renewable Energy Laboratory (NREL)
| Machine Learning Engineer (Intern) | May 2024 — Jan 2025 |
- Developed novel machine learning models for automated network topology inference and resilient control policy optimization for complex distributed systems under extreme scenarios
- Designed and developed semi‑supervised learning approaches to tackle the challenge of limited labeled data in networks, achieving 98% improvement in model accuracy with varying labeled data.
- Paper ”Advanced Semi‑Supervised Learning with Uncertainty Estimation for Phase Identification in Distribution Systems” accepted at IEEE Power & Energy Society General Meeting (PES GM) 2025.
Comcast
| Software Engineer | Jul 2019 — Feb 2020 |
- Designed and implemented real‑time data processing pipelines using Amazon Kinesis and RabbitMQ, processing 1TB+ daily data for fraud detection and system monitoring.
- Developed machine learning models for anomaly detection and user behavior analysis, reducing fraudulent activities by 70% through predictive analytics.
- Created interactive dashboards using Presto DB and Python visualization tools, enabling real‑time monitoring of network performance metrics and fraud patterns.
IBM
| Software Engineer | Jan 2019 — Jun 2019 |
- Led cloud infrastructure optimization using OpenShift, implementing auto‑scaling solutions that reduced operational costs by 30%.
- Developed a comprehensive monitoring system using Grafana and Flask, providing real‑time visibility into 100+ cloud servers.
- Implemented automated performance monitoring and alerting system, reducing incident response time by 60%.
Hewlett Packard Enterprise (HPE)
| Software Engineer | Apr 2017 — Dec 2018 |
- Spearheaded migration of critical applications from HPI to HPE domain, ensuring zero downtime during transition.
- Implemented OAuth 2.0 authentication system and RESTful services using Spring Boot, securing applications serving 50K+ users.
- Designed and deployed microservices architecture on Apache/WebLogic servers, improving system response time by 40%.
Tata Consultancy Services (TCS)
| System Engineer | Jul 2012 — Dec 2015 |
- Engineered high‑performance ETL pipelines for data warehouse integration, processing 100GB+ daily data volumes.
- Optimized database performance through advanced SQL tuning and indexing strategies, reducing query execution time by 70%.
- Received excellence award for achieving $100K cost savings through database optimization initiatives.
Education
Iowa State University
| Ph.D. in Computer Science (Minor: Statistics) | 2020 — 2025 (Expected) |
- Research: Deep RL, Physics-Informed AI, Uncertainty Quantification, LLM Agents
- Courses: Deep Learning, NLP, Statistical Theory, Empirical Methods, Algorithm, Databases
Teaching Experience
Iowa State University
| Teaching Assistant | 2020 — 2025 |
Department of Computer Science
- Supported undergraduate/graduate courses including Software Development Practices, Database Systems, and Spreadsheets.
- Led weekly lab sessions, assisted students with debugging and conceptual challenges, and held office hours.
- Designed assignments and quizzes aligned with real-world workflows and agile development practices.
- Mentored students on semester-long capstone projects simulating software engineering team experiences.
Research Experience
Iowa State University
| Research Assistant | Aug 2022 — Jul 2025 |
- Research on Physics‑Informed Deep Reinforcement Learning for Critical Infrastructure Systems, focusing on Intelligent Resource Management and Security in Large‑Scale Distributed Networks.
- Applied computational deep reinforcement learning algorithms in a Smart Energy System to analyze power simulation data, minimizing voltage violations, power loss, and control errors.
- Developed physics‑informed DRL algorithms incorporating domain‑specific physical constraints, achieving 30% improvement in resource allocation efficiency and reducing system violations in complex distributed networks.
- Designed and implemented adversarial attack detection and mitigation frameworks for AI models in critical systems, enhancing robustness against security threats through systematic testing and defensive techniques.
- Created novel transfer learning methodologies enabling DRL models to adapt across varying network sizes and topologies, reducing training time by 40% for new configurations.
- Developed Python‑based simulation and control framework integrating real‑time hardware (OPAL‑RT and OpenDSS) with distributed systems.
- Leveraged LLM‑driven reasoning and contextual understanding within simulation environments to support real‑time adaptive control, human‑AI collaboration, and predictive system optimization.
| Research Assistant | Aug 2020 — Jul 2022 |
- Research on Deep Reinforcement Learning (DRL) and Safety‑Critical Learning for Autonomous Systems, with focus on perception, control, and decision‑making in high‑stakes environments.
- Utilized CARLA simulator for vision‑based autonomous driving tasks, including perception, object detection, trajectory planning, and policy learning in complex traffic scenarios.
- Applied deep computer vision models for object recognition, semantic segmentation, and sensor fusion, enabling robust situational awareness in autonomous driving and robotics.
Skills
Programming
Python, R, Java, C++, SAS, MATLAB, SQL, HTML/CSS, JavaScript (Node.js, React)
Machine/Deep Learning
scikit-learn, TensorFlow, PyTorch, pandas, Matplotlib, Seaborn, Gym, RLlib
LLMs & NLP
OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, RAG (retrievers, chunking, reranking), vector DBs (FAISS, Chroma, Pinecone), prompt engineering & structured outputs, evaluation (Ragas, Promptfoo)
Agentic Systems & Orchestration
LangGraph (stateful workflows), LangChain Agents (ReAct/MRKL/tools), function/tool calling, multi-agent design, planning & memory, tool-use (search/code/execution), guards & grounding
HPC & Big Data
Hadoop, Hive, Spark, Kafka, Kinesis, SLURM, MPI, OpenMP
Simulation & Modeling
OPAL-RT, OpenDSS (Power), CARLA (Autonomous Driving)
Optimization
Gurobi, Pyomo, BoTorch, Optuna, Hyperopt
Visualization & GIS
Tableau, ArcGIS, Leaflet
Cloud & DevOps
AWS (EC2, S3, Lambda), GCP, Docker, Kubernetes, Git, Terraform, Jenkins, CircleCI
Honors & Awards
- Selected, Seventh Workshop on Autonomous Energy Systems @ NREL (2024)
- Selected, ByteBoost Workshop on Accelerating HPC Research Skills (2024)
- Selected, Oxford Machine Learning Summer School (OxML) (2022)
- Excellence Award, Database Optimization @ TCS
- 2nd Place, BAJA SAE India (Safest Terrain Vehicle Category, National Level)
Service
Reviewer:
- IEEE Transactions on Industrial Informatics (2025)
- Conference on Neural Information Processing Systems (Ethics)(2025)
- IEEE Transactions on Neural Networks and Learning Systems (2024)
- IEEE PES GM, Grid Edge & ISGT (2023, 2024)
Mock Interviewer: Supporting underrepresented minorities in tech.
Volunteer, Prayaas India (BIT): NGO providing quality education to underprivileged children in slums and villages.
