Built a CBIR system using 6-bit color code histograms and texture features to retrieve visually similar images from a dataset. Implemented custom feature extraction, distance metrics, and query-by-example search.
Abhishek Vajragattepalya Seetharamaiah
M.S. Computer Science · Virginia Commonwealth University
I'm a graduate student in Computer Science at Virginia Commonwealth University with a focus on Artificial Intelligence, Machine Learning, and Data Science.
I enjoy building end-to-end AI systems: from data preprocessing and feature engineering to model training, evaluation, and deployment. Recent work includes a content-based image retrieval system in MATLAB, a hotel-review exploration app powered by LangGraph and Streamlit, and quantum optimization experiments with QAOA.
Education
- Virginia Commonwealth University – M.S. in Computer Science (AI/ML focus), expected Dec 2025
- Presidency University – B.Tech. in Information Science and Engineering
Learn more about my:
Skills
Below are some of my key skills across programming, data, cloud, and tooling.
(Grouped by category; see my resume for more context.)
Programming & Machine Learning
Strong foundation in software engineering and core ML frameworks.
- Python, Java, C/C++, MATLAB, SQL
- TensorFlow, PyTorch, scikit-learn
- NumPy, Pandas
Data Science & Analytics
Hands-on experience analyzing real-world datasets and building models.
- Exploratory Data Analysis (EDA), Feature Engineering
- NLP, Neural Networks, Classical ML
- Classification, Regression, Clustering
- Recommender Systems, Image Processing
Databases & Data Management
Comfortable working across relational and NoSQL data stores.
- MySQL, PostgreSQL, MongoDB, Oracle
- Advanced Database Systems
- SQL querying & optimization
Cloud, DevOps & MLOps
Industry experience deploying and operating ML and data workloads in the cloud.
- Google Cloud Platform (GCP), AWS (EC2, Lambda, DynamoDB)
- Docker, Kubernetes, Cloud deployment
- Git, GitHub, basic CI/CD practices
Tools, Frameworks & Domains
Ecosystem of libraries and tools I use for experimentation and visualization.
- Jupyter, Tableau
- Matplotlib, Seaborn
- Streamlit, LangChain, LangGraph
- OpenCV for computer vision
Additional Topics
Broader foundation supporting my AI/ML work.
- Advanced Algorithms & Data Structures
- Knowledge Discovery & Data Mining
- Quantum Computing fundamentals & QAOA basics
Projects
Some of the projects I've worked on recently.
Human-in-the-loop tool that summarizes hotel reviews and supports interactive exploration using multi-agent workflows, style-guided responses, and review history logging.
Implemented QAOA for vertex cover on small graphs, experimenting with depth, penalty parameters, and optimizer settings. Compared quantum solutions against classical baselines and analyzed trade-offs.
Papers & Reports
Course projects and research-style reports.
Prototype: “Image-Based Classification for Skin Lesion Data”
Prototype: “Quantum-Inspired Optimization with QAOA for Small Graphs”
Certifications
Selected online courses and certifications.
Timeline
A short summary of my academic and professional journey.
2024 – Present
Graduate Student, VCU – Richmond, VA
Pursuing M.S. in Computer Science with focus on AI/ML, NLP, and data mining. Working on projects in image analysis, quantum optimization, and ML systems.
Jan 2023 – Jul 2024
Cloud Architect – Quadra Systems .NET India Pvt Ltd, Bengaluru
Supported clients on GCP and AWS by resolving issues, optimizing deployments, and improving overall system reliability, cost-efficiency, and security.
Jul 2020 – Jan 2023
Machine Learning Engineer – Capgemini Technology Services, Bengaluru
Built and maintained end-to-end ML pipelines using Python, TensorFlow, and scikit-learn, deploying models for classification, prediction, and recommendation use cases in production environments.