Ms. Mina Gachloo | Machine Learning | Best Researcher Award
Mina Gachloo at university of North Carolina Wilmington, United States
Profiles
Education:
Ms. Mina Gachloo is set to graduate with a Master's degree in Computer Science and Information Systems from the University of North Carolina Wilmington in December 2024, boasting a GPA of 3.8. Her research at UNCW, under the guidance of Dr. Yang Song, focuses on "Temporal Prediction of Coastal Water Quality Based on Environmental Factors with Deep Learning." Mina also holds a Bioinformatics Engineering degree from Huazhong Agricultural University in Wuhan, China, where she researched "Embedding of Cancer-Centric Entities and Knowledge Discovery." Additionally, she earned a B.Sc. in Information Technology from the University of Applied Science and Technology in Tehran, and an Associate’s degree in Information and Communication Technology from the University of Culture and Art in Tehran.
Professional Experience:
Ms. Mina has a diverse range of professional experiences. In 2023, she interned as a Data Analyst and Researcher at the UNCW Institutional Research Office, focusing on predicting the time-to-graduate for undergraduate students. As a Teaching and Research Assistant at UNCW, she conducted data cleaning, feature engineering, and implemented machine learning and deep learning models for predictive analysis. Prior to this, she worked as a Commercial Expert at Bam Khodro Company in Tehran, using SQL, Excel, and Python for data extraction, analysis, and report automation. Mina also served as a Financial Expert at Mellat Leasing Bank, facilitating loans and generating customer reports. Her career began in IT at KICCC in Tehran, specializing in Point of Sale devices and Business Intelligence.
Research Interest:
Ms. Mina's research interests include machine learning, deep learning, structure learning, data analysis, natural language processing, and computer vision. She has actively contributed to several projects, such as the construction of the Active Gene Annotation Corpus (AGAC) and the prediction of dissolved oxygen and salinity levels in the Neuse River Estuary using deep learning techniques.
Honors and Awards:
Ms. Mina's academic excellence has been recognized with multiple awards, including the Summer Research Stipend, Support for Undergraduate Research and Creativity Awards (SURCA), and CMS summer stipend at UNCW. She also received scholarships for her M.Sc. in Computer Science and Bioinformatics at Huazhong Agricultural University.
Skills:
Ms. Mina is proficient in data preprocessing, machine learning, deep learning, natural language processing, and programming in Python and Java. She is skilled in using tools like Jupyter Notebook, Google Colab, Pycharm, IDLE, Microsoft Office, Pegasus, SQL, and Oracle.
 Publications:
Using Machine Learning Models for Short-Term Prediction of Dissolved Oxygen in a Microtidal Estuary
-
Authors: Mina Gachloo, Qianqian Liu, Yang Song, Guozhi Wang, Shuhao Zhang, Nathan Hall
- Year: 2024
An overview of the active gene annotation corpus and the BioNLP OST 2019 AGAC track tasks
- Authors: Yuxing Wang, Kaiyin Zhou, Mina Gachloo, Jingbo Xia
- Year: 2019
A review of drug knowledge discovery using BioNLP and tensor or matrix decomposition
- Authors: Mina Gachloo, Yuxing Wang, Jingbo Xia
- Year: 2019
GOF/LOF knowledge inference with tensor decomposition in support of high order link discovery for gene, mutation and disease
- Authors: Kai Yin Zhou, Yu Xing Wang, Sheng Zhang, Mina Gachloo, Jin Dong Kim, Qi Luo, Kevin Bretonnel Cohen, Jing Bo Xia
- Year: 2019
An active gene annotation corpus and its application on anti-epilepsy drug discovery
- Authors: Yuxing Wang, Kaiyin Zhou, Jin-Dong Kim, Kevin B Cohen, Mina Gachloo, Yuxin Ren, Shanghui Nie, Xuan Qin, Panzhong Lu, Jingbo Xia
- Year: 2019