Niveditha Kundapuram — Software Engineer
Aspiring data scientist with 2+ years of experience applying machine learning and deep learning techniques to extract insights from complex datasets. Developed predictive models and implemented novel approaches to problems across domains including network security, astrophysics, neuroscience, and computer vision. At IISc's MILE Lab, I utilized advanced machine learning including neural networks to uncover EEG biomarkers that discriminate meditative states. Achieved 96% accuracy in classifying meditation levels via feature engineering and ensemble modeling. Constructed functional brain networks revealing neural correlates of meditation through connectivity analysis. At Fidelity Investments, built an application in Angular and Flask to automate validation of financial records for over 1M customers. Designed and deployed REST APIs, optimized SQL queries, and indexed databases to improve performance. Reduced execution time from 2 hours to under 1 minute through workflow optimization. Presented application to senior stakeholders and contributed to documentation for production deployment. Strong foundation in data structures, algorithms, statistics, and machine learning with proficiency in Python, Java, C++, and related frameworks. Experienced working with TensorFlow, Keras, NumPy, Pandas, SciPy, scikit-learn, Matplotlib, and other libraries. Passionate about deriving impactful insights through rigorous analytical thinking. Actively expanding expertise in production ML system design and large-scale data engineering. Passionate about leveraging data to uncover impactful insights. Excited to apply analytical thinking and technical skills to data science roles in startups and innovative teams working on meaningful problems. Actively expanding expertise in ML engineering, optimization, and deploying solutions to production.
Stackforce AI infers this person is a Data Scientist with expertise in Fintech and Healthcare applications.
Location: Bengaluru, Karnataka, India
Experience: 1 yr 10 mos
Skills
- Api Development
- Machine Learning
Career Highlights
- Achieved 96% accuracy in EEG classification.
- Reduced execution time from 2 hours to under 1 minute.
- Developed applications for diverse domains including finance and neuroscience.
Work Experience
Apple
Software Engineer (1 yr 10 mos)
Machine Learning Intern (6 mos)
Fidelity Investments
Summer Intern (2 mos)
Indian Institute of Science (IISc)
Research Intern (3 mos)
Center for Data Sciences and Applied Machine Learning (CDSAML)
Summer Research Intern (2 mos)
Education
Computer Science and Engineering at PES University
