Data Science Researcher

I am a dedicated and innovative data science professional with a passion for bridging advanced machine learning techniques and real-world applications. Currently, I'm working as Data Science Researcher at the University of Southern California. My focus is on developing robust models that harness the power of multimodal data—including clinical images and natural language—to drive breakthroughs in disease detection and beyond.

• Statistical Analysis & Data Engineering: Expertise in transforming and cleaning complex datasets, applying rigorous statistical methodologies to derive actionable insights.
• Advanced Modeling Techniques: Proficient in classical machine learning and deep learning architectures. Skilled in feature engineering, model optimization, and performance evaluation.
• Experimental Design: Experience in designing experiments and conducting A/B tests to validate model efficacy and business impact.

• Transformer Architectures: Deep understanding of state-of-the-art transformer-based models and their fine-tuning for natural language processing tasks.
• Prompt Engineering: Proficient in developing effective prompts and leveraging pre-trained large language models to generate insightful outcomes.
• Multimodal Integration: Innovating on merging text, image, and structured data to create comprehensive predictive systems, particularly in healthcare applications.

Additional tools and libraries include SQL, MongoDB, Flask, LangChain, and cloud platforms like GCP and AWS.

• Multimodal Disease Detection: Developed a comprehensive deep learning pipeline combining breast cancer mammography images and ultrasound scans to improve diagnostic accuracy.
• LLM-Based Analytics: Engineered and fine-tuned transformer models for natural language understanding and generation, addressing complex tasks such as medical report summarization and real-time query answering.
• Data-Driven Decision Systems: Architected scalable data pipelines that integrate structured and unstructured data to empower insightful analytics and strategic decisions.

For more details, check out my GitHub repositories or visit my Google Scholar profile.

I regularly publish articles and research findings on advanced data science methods and LLM innovations.

• From Raw Data to Informed Decisions: Exploring statistical methodologies in real-world data problems.
• Navigating the Complexities of Linear Regression: A deep dive into techniques and applications in data science.

For more, follow my posts on Medium.

I am always open to collaborating on projects that push the limits of data science and machine learning. Whether you're interested in cutting-edge research or building robust solutions, feel free to reach out.

• 💬 LinkedIn: Ketki Kinkar

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