Moein Shahiki Tash

CIC-IPN - NLP Researcher

2022-08 - Present

• Large Language Models (LLMs): My research involves working with LLMs to develop and refine natural language processing applications. I developed a novel dataset for online social support, utilizing advanced machine learning techniques including transformers and zero-shot learning with GPT-3 and GPT-4 models, which led to significant improvements in classification performance.

• Advanced Machine Learning: In another area of research, I used advanced machine learning techniques, such as deep neural networks and transformers, to enhance model accuracy, performance, and the ability to capture complex patterns in data. Different models have been applied to tasks such as hate speech detection, hope speech recognition, sentiment analysis, and the identification of enhancers and super-enhancers.

• Traditional Machine Learning: I used traditional machine learning algorithms, such as decision trees and support vector machines, in a research project focused on Identification language.

• Azure Machine Learning: I have experience utilizing Azure Machine Learning to streamline and manage the deployment and training of machine learning models in my research projects. I used Azure Machine Learning to enhance performance in various NLP tasks, including hope speech detection and classification challenges.

• Natural language processing techniques: I used NLP techniques, including emotion recognition with SenticNet, to analyze emotional trends derived from X platform data in relation to cryptocurrency market dynamics. Additionally, I employed advanced NLP techniques such as psycholinguistic analysis and co-mention detection to analyze and compare the linguistic characteristics of social media content across different cryptocurrency communities.

Lidoma — Machine learning engineer

2019-04 - 2022-07

• Developed and deployed machine learning models for natural language processing tasks, such as sentiment analysis and text classification, using frameworks like TensorFlow and Scikit-learn

• Conducted exploratory data analysis to uncover insights and trends, guiding the development of predictive models.

• Collaborated with stakeholders to translate business requirements into machine learning solutions, delivering actionable insights and recommendations for decision-making

Hi-Web — python Developer

2017.12 - 2018.12

• Implemented data processing pipelines and performed data analysis tasks using Python libraries such as Pandas and NumPy.

• Developed scripts to automate data retrieval and cleaning processes, optimizing workflow efficiency.

Programming Languages and Librari

• Proficient in Python and related libraries, including NumPy, Pandas, andscikit-learn.

• Experienced with machine learning and deep learning frameworks such as TensorFlow, PyTorch, and Keras.

Natural Language Processing (NLP)

• Familiarity with a wide range of NLP tasks, including part-of-speech tagging, named entity recognition, hate speech detection, hope speech detection, fake news identification, emotion analysis, low-resource languages, and code-mixed texts.

• Knowledge of advanced algorithms and techniques for text data processing and analysis, including word embeddings, language models, and feature engineering.

Data Handling and Management

• Proficiency in working with large, complex datasets, ensuring efficient data manipulation and storage.

• Excellent communication and writing skills, both oral and written, to clearlyconvey research findings and collaborate with others.
• Strong time management and organizational skills to effectively plan and execute research projects
• Ability to work independently and in a team environment, as well as to collaborate with researchers from a variety of backgrounds and disciplines
• Creativity and problem-solving skills to approach NLP challenges in innovative ways and develop novel solutions.
• Strong presentation skills to effectively communicate research findings to both technical and non-technical audiences.
• Ability to stay up-to-date on the latest research and developments in thefield of NLP and related areas