- Evaluating LLMs responds and providing feedback to improve them through RLHF - Assessing the factuality and relevance of text produced by AI models - Writing and rewriting prompts and responses, which may involve research and fact-checking

- Teching STEAM curriculum including AI, coding, robotics and other programs to students from all ages.- Consulting on AI curriculum design for kids.- Giving parents direct feedback on their child’s learning progress.

- Conducting research on applications of Data Mining, Machine Learning and Reinforcement learning in software engineering. - Investigating the prompt interpretability of Large Language Models (LLMs) by defining saliency and attention scores. - Supervising 4th year undergraduate students through their projects/research. - Analyzing real-world tracing data to derive meaningful insights through data mining methods like clustering, associate rule mining and etc..- Published… Show more - Conducting research on applications of Data Mining, Machine Learning and Reinforcement learning in software engineering. - Investigating the prompt interpretability of Large Language Models (LLMs) by defining saliency and attention scores. - Supervising 4th year undergraduate students through their projects/research. - Analyzing real-world tracing data to derive meaningful insights through data mining methods like clustering, associate rule mining and etc..- Published research in top international conferences in the field. Show less

- Demonstrating labs.- Marking/grading assignments and exams.- Running help desk sessions to answer their questions regarding.

- Mentoring and teaching kids from 5 to 14 years onld how to code.- Providing feedback to parents.- Code debugging and teaching kids how to prevent them.

- Defining/Implementing Reinforcement Learning model for log-placement to capture performance bugs.- Utilized static source code metrics and RL (Reinforcement Learning) to investigate and resolve performance issues on resource-constrained devices.- Data collection and feature extraction from source code of 17 different repositories by web scraping.- Evaluating and testing different RL algorithms (DQN, A2C and PPO) to find the most suitable method for our approach.

- Developed machine learning models for a remote sensing project to classify and recognize different croplands.- Optimized the model's performance by 12% and reaching 93% accuracy by tuning dataset features and utilizing SVM instead of Random Forest.- Data collection and time series analysis by investigating satellite images using Google Earth Engine.

- Developing and maintaining company's website.- Conducting search engine optimization.