Hi there, I am Adelina! π
Welcome to My Page! π
Hello! Iβm Adelina Duman, a recent graduate from Columbia University, specializing in the Intelligent Systems track. My academic journey has equipped me with a robust foundation in Artificial Intelligence, Applied Machine Learning, and Natural Language Processing. I also interned at Duolingo as a Software Engineer and worked as a AI Researcher in EPFL University, working on the intersection between AI and neuoscience
π Education
- Columbia University (Graduation Date: May 2024)
- Courses: Artificial Intelligence, Applied Machine Learning, Natural Language Processing, and more.
πΌ Internship and Work Experience
EPFL University AI Research Intern π§
- Acceptance Rate: 1.5%
- Contributed to state-of-the-art deep learning research in animal behavior analytics.
- Implemented and optimized algorithms including decision trees, SVMs, and neural networks.
- Enhanced predictive modeling accuracy through advanced data preprocessing.
- Tech Stack: Python, TensorFlow, Keras, Scikit-Learn, Pandas
- Skills: Deep Learning, Neural Networks, Data Preprocessing, Model Optimization
Duolingo Software Engineering Intern π¦π’
- Developed an Android mobile app βConcentration Gameβ with a team of engineers, where users can practice words in their learning language.
- Frontend: Coded in Kotlin using reactive programming and MVVM architecture.
- Backend: Coded in Python with Flask and SQL. Integrated Terraform and DynamoDB for data storage.
- Conducted A/B testing and optimized app performance, significantly improving user retention.
- Tech Stack: Kotlin, Flask, DynamoDB, Python, Docker, SQL, Terraform, AWS
- Skills: Full-Stack Development, A/B Testing, Performance Optimization
NLP Research Assistant with John R. Kender at Columbia University π
- Worked on an NSF-funded project focusing on sentiment analysis using big data from online forums.
- Built predictive models and data visualizations to translate sentiment trends.
- Researched state-of-the-art deep learning papers on arXiv.
- Tech Stack: Python, PyTorch, NLTK, Matplotlib, Seaborn
- Skills: Sentiment Analysis, Data Visualization, Deep Learning
- Link
π Leadership Experience
- Teaching Assistant for COMS ENGI1600 at Columbia University β 300 students, holding recitations π
- Events Lead for Google Developer Student Club π₯³
- Organized events focused on emerging technologies and AI development, significantly increasing club engagement.
π» Technical Skills
- Languages: Python, R, SQL, Kotlin, Java
- Frameworks and Tools: LangChain, Docker, Vertex AI, AWS Sagemaker, Hugging Face, Bedrock, TensorFlow, Praat β Data Engineering: Data Structures, ETL, Vector Databases (Pinecone, Chroma), Neo4j (Cypher), Knowledge Graphs
- Machine Learning and AI: Model Training, Neural Networks, Supervised Learning, Feature Engineering, Hyperparameter Tuning,RAG (Retrieval-Augmented Generation),, Fine-tuning LLMs, MLOps, VADER, NLTK, Prompt Engineering, Model Deployment
- Libraries: PyTorch, NumPy, opencv,Pandas, Scikit-Learn, Matplotlib, Seaborn, Tableau, Keras
π Certifications
- Machine Learning by Stanford University
- Currently taking Machine Learning Specialization by Andrew Ng
- AI for Product Management by Duke University
- Introduction to Generative AI Learning Path by Google Cloud