Sohrab Pirhadi- Master of Computer Science
- Research Assistant at Institute for Advanced Studies in Basic Sciences
Sohrab Pirhadi
- Master of Computer Science
- Research Assistant at Institute for Advanced Studies in Basic Sciences
Machine Learning Engineer, Research Scientist in Analytical Chemistry
About
7
Publications
314
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1
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Introduction
I am a Data Scientist and Machine Learning Developer specializing in Natural Language Processing and high-dimensional data analysis. My research focuses on optimizing machine learning models for tasks like relation extraction and analyzing sparse data such as LC-TOF-MS samples.
I am passionate about advancing data science through interpretable, scalable solutions and look forward to collaborating with the scientific community to tackle real-world challenges.
Current institution
Additional affiliations
October 2023 - March 2024
Position
- Research Assistant
Description
- Natural Language Processing research with a focus on extracting information from text. My work involves developing techniques to automatically identify and extract key facts, entities, relationships, and insights from unstructured text data.
December 2021 - March 2022
Position
- Teaching Assistant
Description
- Computational Data Mininig Teacher assistant.
Education
September 2019 - February 2023
September 2013 - May 2018
Publications
Publications (7)
Relation extraction (RE) is a crucial task in natural language processing that identifies relationships between entities within text. Although increasing the size of annotated datasets typically enhances model performance, the cost and effort associated with human annotation can be prohibitive. This study examines the impact of dataset size on RE p...
This study evaluates ensemble learning methods, including Bagging, Boosting, Random Forest, and Stacking, for classification tasks on diverse benchmark datasets. By evaluating these techniques, the research assesses their performance using standard metrics such as accuracy, F1-score, ROC, and AUC. The results reveal that Random Forest consistently...
The COVID-19 outbreak has had a significant influence on several critical industries, including agriculture, education, and the economy. This essay investigates these processes, with a focus on agriculture, where the repercussions have been particularly harsh for poor groups dealing with unpredictable food supplies and food safety. Along with a cri...
Article Type: Review In recent years, consumers have become increasingly concerned about the safety and authenticity of their food, as it directly affects their health. Food adulteration is a global issue that poses safety risks and is difficult to detect. Economically motivated adulteration (EMA) frequently results from the diversion of ingredient...
Article Type: Review Ensuring accurate meat species identification and animal authentication in meat products is crucial for promoting fair trade and empowering consumers to make informed decisions. Concerns about food fraud have grown due to significant financial and trust-related consequences. Chromatographic techniques combined with chemometrics...
Information Extraction (IE) refers to the process of automatically extracting structured data from unstructured sources to enable the utilization of such data by other applications. Extracting relations from textual sources, which seeks to detect the semantic relation represented between entities ref-erenced in the texts, is a common sub-problem. T...
Sentence-level relation extraction using deep neural networks (DNNs) has emerged as a powerful approach in the field of natural language processing. This technique aims to identify and classify relationships between entities within individual sentences, leveraging the capabilities of DNNs to understand complex linguistic patterns and contextual nua...
