Mr. Adamu Abubakar Sani | Machine Learning | Best Researcher Award

Mr. Adamu Abubakar Sani | Machine Learning | Best Researcher Award

Adamu Abubakar Sani at Universiti Teknologi PETRONAS, Malaysia

👨‍🎓 Profiles

Google Scholar

Publications

A Multi-level Classification Model for Corrosion defects in Oil and Gas Pipelines Using Meta-Learner Ensemble (MLE) Techniques

  • Authors: Adamu Sani Abubakar, Mohamed Mubarak Abdul Wahab, Nasir Shafiq, Kamaludden Usman, Nasir Khan, Adamu Tafida, Arsalan Khan
  • Journal: Journal of Pipeline Science and Engineering
  • Year: 2024

A Review of Eco-Friendly Road Infrastructure Innovations for Sustainable Transportation

  • Authors: Adamu Tafida, Wesam Salah Alaloul, Noor Amila Bt Wan Zawawi, Muhammad Ali Musarat, Adamu Sani Abubakar
  • Journal: Infrastructures
  • Year: 2024

Design and modeling the compressive strength of high-performance concrete with silica fume: a soft computing approach

  • Authors: Abiola Usman Adebanjo, Nasir Shafiq, Siti Nooriza Abd Razak, Vicky Kumar, Syed Ahmad Farhan, Priyanka Singh, Adamu Sanni Abubakar
  • Journal: Soft Computing
  • Year: 2024

Systematic Literature Review and Scientometric Analysis on the Advancements in Electrically Conductive Asphalt Technology for Smart and Sustainable Pavements

  • Authors: Arsalaan Khan Yousafzai, Muslich Hartadi Sutanto, Muhammad Imran Khan, Nura Shehu Aliyu Yaro, Abdullah O Baarimah, Nasir Khan, Abdul Muhaimin Memon, Adamu Sani Abubakar
  • Journal: Transportation Research Record
  • Year: 2024

Integrating Life Cycle Cost Analysis into Pipeline Asset Integrity Management: A Comprehensive Approach in Decision Support Systems

  • Authors: Adamu Sani Abubakar, Mohamed Mubarak Bin Abdul Wahab, Nasir Shafiq, Kamaluddeen U Danyaro, Abiola Usman Adebanjo
  • Journal: Journal of Hunan University Natural Sciences
  • Year: 2024

Dr. Na Yi | Deep Metric Learning | Best Researcher Award

Dr. Na Yi | Deep Metric Learning | Best Researcher Award

Doctorate at Heilongjiang University of Science and Technology, China

Profiles

Scopus

Orcid

Academic Background

Dr. Na Yi, born in June 1997 in Acheng, Harbin, is an Associate Professor and a committed member of the Communist Party of China. With a strong academic foundation in Electrical Engineering and Automation, she has quickly risen as a prominent figure in the field of Petroleum and Natural Gas Engineering.

Education

Dr. Na Yi graduated with a degree in Electrical Engineering and Automation from Northeast Petroleum University in 2019. She was subsequently recommended for a doctoral program in Petroleum and Natural Gas Engineering, during which she also studied at Southeast University, earning her doctorate in 2024.

Professional Experience

Throughout her career, Dr. Na Yi has published over 20 research papers in esteemed journals, with 10 SCI-indexed and 5 EI-indexed papers, including highly cited and hot papers. She holds 6 national patents and has participated in 5 significant scientific research projects. Her achievements have earned her more than 10 national and provincial awards.

Research Interests

Dr. Na Yi’s research interests lie in Petroleum Engineering, with a focus on sustainable energy, power systems, and technological innovation. She is an active reviewer for multiple international and Chinese academic journals and has been invited to present her research at several international and domestic conferences.

 Publications

A multi-stage low-cost false data injection attack method for power CPS

  • Authors: Yi, N., Xu, J., Chen, Y., Pan, F.
  • Journal: Zhejiang Electric Power
  • Year: 2023
A New Distributed Power Supply for Distribution Network Considering SOP Access
  • Authors: Peng, C., Xu, J., Zhao, S., Yi, N.
  • Year: 2023
Multi-stage coordinated cyber-physical topology attack method based on deep reinforcement learning
  • Authors: Yi, N., Xu, J., Chen, Y., Sun, D.
  • Journal: Electric Power Engineering Technology
  • Year: 2023
A multi-stage game model for the false data injection attack from attacker’s perspective
  • Authors: Yi, N., Wang, Q., Yan, L., Tang, Y., Xu, J.
  • Journal: Sustainable Energy, Grids and Networks
  • Year: 2021
Insulator Self-Explosion Defect Detection Based on Hierarchical Multi-Task Deep Learning
  • Authors: Xu, J., Huang, L., Yan, L., Yi, N.
  • Journal: Diangong Jishu Xuebao/Transactions of China Electrotechnical Society
  • Year: 2021

Ms. Mina Gachloo | Machine Learning | Best Researcher Award

Ms. Mina Gachloo | Machine Learning | Best Researcher Award

Mina Gachloo at university of North Carolina Wilmington, United States

Profiles

Scopus

Orcid

Google Scholar

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

Mr. Nikolaos Argirusis | Machine Learning | Industry Impact Award

Mr. Nikolaos Argirusis, Machine Learning, Industry Impact Award

Nikolaos Argirusis at mat4nrg GmbH, Germany

Profiles

Scopus

Orcid

🎓Education:

Mr. Nikolaos Argirusis pursued his education at Ostfalia University of Applied Sciences, specializing in Energy Systems and Environmental Engineering, achieving a “Very Good” rating in his Master’s degree. Previously, he completed his Bachelor’s in Electrical and Information Technology at Ostfalia University, with a focus on Electromobility and Energy Technology. He also holds a Bachelor’s degree in Electrical Engineering from Technische Universität Braunschweig, specializing in Energy Technology.

💼 Work Experience:

Currently, Nikolaos serves as a Student Assistant at CZM – TU Clausthal, where he contributes to electronics development and plasma technology experiments. He also engages in a research project for mat4nrg GmbH, focusing on prototype development and project organization. As the Co-founder and Managing Director of mat4nrg GmbH, he oversees the management, supervision, and development of research and customer projects. Additionally, Nikolaos supports his family’s business, aeras GmbH, focusing on power electronics assembly.

🌐 Skills and Languages:

He possesses advanced skills in Microsoft Office, PSpice, and LTspice, with foundational knowledge in C++ and Java programming languages. Fluent in German and Greek, Nikolaos also communicates proficiently in English.

🎯 Interests:

Outside of academics and professional endeavors, Nikolaos enjoys swimming, team sports, and engaging in DIY projects, reflecting his diverse interests and active lifestyle.

📖 Publications:

Evaluation of the effectiveness and performance of environmental impact assessment studies in Greece
  • Authors:Papamichael, I., Tsiolaki, F., Stylianou, M., Argirusis, C., Zorpas, A.A.
  • Journal:Comptes Rendus Chimie
  • Year: 2023
End-of-Life Management and Recycling on PV Solar Energy Production
  • Authors:Papamichael, I., Voukkali, I., Jeguirim, M., Argirusis, C., Zorpas, A.A.
  • Journal: Energies
  • Year: 2022
Research Progress in Metal-Organic Framework Based Nanomaterials Applied in Battery Cathodes
  • Authors: Mechili, M., Vaitsis, C., Argirusis, N., Zorpas, A.A., Argirusis, C.
  • Journal: Energies
  • Year: 2022
Research progress in transition metal oxide based bifunctional electrocatalysts for aqueous electrically rechargeable zinc-air batteries
  • Authors: Mechili, M., Vaitsis, C., Argirusis, N., Sourkouni, G., Argirusis, C.
  • Journal: Renewable and Sustainable Energy Reviews
  • Year: 2022
MOF nanomaterials for battery cathodes
  • Authors: Vaitsis, C., Mechili, M., Pandis, P.K., Argirusis, N., Sourkouni, G.
  • Year: 2022