CV

Education

• Master’s in Data Science, Analytics, and Engineering
  Arizona State University, Tempe, Arizona, USA (Aug 2023 - Jun 2025)
  • Achievements: GPA: 3.22
  • Coursework: Artificial Intelligence, Data Mining, Convex Optimization, Statistical Machine Learning
• Bachelor’s in Computer Science
  Institute of Technology, Nirma University, Ahmedabad, Gujarat, India (Jul 2019 - Jun 2023)
  • Achievements: GPA: 8
  • Coursework: Deep Learning, Machine Learning, Natural Language Processing

Work experience

• AI Research Intern
  GIOSTAR.AI, San Francisco, CA, USA (Nov 2023 - May 2024)
  • Engineered Vision Transformer Model and U-Net for medical imaging, focusing on anomaly detection and cell classification.
  • Achieved high accuracy in epilepsy detection using Temporal Fusion Transformers (TFT) and RCNN.
  • Contributed to Brain-Computer Interface (BCI) systems for thought-controlled smartphone usage.
• Deep Learning Engineering Intern
  Talin Labs Inc, Los Angeles, CA, USA (May 2024 - Sep 2024)
  • Developed an AI chatbot for supply-chain optimization using LangChain and Transformer models.
  • Achieved sub-second latencies with Retrieval-Augmented Generation (RAG).
  • Led cross-cloud deployment on AWS and Azure using Docker and Kubernetes.
• Summer Research Intern
  Nirma University, Ahmedabad, Gujarat, India (May 2022 - Aug 2022)
  • Developed Edge AI solutions for traffic violation detection using YOLOv5.
  • Engineered OCR and ensemble learning models for license plate recognition.

Projects

• Deep Ensemble Mammogram Classification Using One-Shot Segmentation (Aug 2022 - Nov 2022)
  • Utilized ResNet, U-Net, EfficientNet, and MobileNet for mammogram classification.
  • Achieved over 81% accuracy using ensemble models and one-shot segmentation techniques.
• Quantum Horizons: Predicting Asteroid Hazards with Supervised QML (Jan 2023 - May 2023)
  • Achieved 98.11% accuracy using Quantum Machine Learning frameworks and IBM 32-qubit quantum simulators.
  • Integrated Fidelity Quantum Kernels to process NASA JPL datasets effectively.
• MetaHate: AI-Driven Blockchain for Safer Metaverse Gaming (Aug 2022 - Dec 2022)
  • Designed a hate speech detection system achieving 95% precision using BERT and RoBERTa models.
  • Built a blockchain-powered moderation system for secure and transparent decisions.

Skills

• Programming Languages: Python, MATLAB, SQL
• Libraries/Frameworks: NumPy, Pandas, TensorFlow, PyTorch, Keras, Scikit-learn, qiskit
• Domains: Machine Learning, Deep Learning, Quantum Machine Learning, Cloud Computing, Statistical Modeling, Data Mining
• Tools: Docker, Kubernetes, OpenCV, NLTK
• Cloud Platforms: AWS, Azure

Publications

MetaHate: AI-based Hate Speech Detection for Secured Online Gaming in the Metaverse Using Blockchain

Sanghvi, H., Bhavsar, R., Hundlani, V., Gohil, L., Vyas, T., Nair, A., Desai, S., Jadav, N.K., Tanwar, S., Sharma, R., & Yamsani, N. (2024). "MetaHate: AI-based Hate Speech Detection for Secured Online Gaming in the Metaverse Using Blockchain." Security and Privacy. 7(2): e343.

Classification of Potentially Hazardous Asteroids Using Supervised Quantum Machine Learning

Bhavsar, R., Jadav, N.K., Bodkhe, U., Gupta, R., Tanwar, S., Sharma, G., Bokoro, P.N., & Sharma, R. (2023). "Classification of Potentially Hazardous Asteroids Using Supervised Quantum Machine Learning." IEEE Access.

Service and leadership

• Proven experience in optimizing scalability and efficiency through cross-cloud deployments and real-time data processing.
• Actively collaborating with research teams and contributing to academic papers.