Publications
8
Conferences
4
Ongoing Projects
2
News Highlights
Great news! My conference presentation on using machine learning techniques to discover novel battery electrolytes, developed during my internship with researchers at the University of Chicago, has been published in IEEE Explore.
My undergraduate thesis has been published in Bioresource Technology Reports. Cheers!
Read my research on using data science to predict Nigeria's future carbon emissions, and learn about the roadmap we created for integrating renewable energy into the power grid. Preprint
My collaborative research on optimizing enzyme recovery from a genetically modified microorganism, conducted alongside talented researchers from across Nigeria, has been published in Biocatalysis and Agricultural Biotechnology. Cheers!
Thrilled to take on a new role as a co-reviewer at the Bioresources Valorization Laboratory, University of Benin.
About Me
Stanley is a research assistant in the Bioresources Valorization Laboratory at the University of Benin, where he collaborates closely with Professor Andrew Amenaghawon. He previously interned at the University of Chicago's Pritzker School of Molecular Engineering in the Amanchukwu Lab, focusing on using machine learning to discover novel battery electrolytes. Stanley's academic journey has provided him with extensive experience across both industry and academia. He is passionate about leveraging machine learning and data science to address complex challenges, with a strong commitment to advancing knowledge and finding real-world solutions.
Research Experience
Amanchukuw Lab
University of Chicago Pritzker School of Molecular Engineering
Project Title: Machine Learning for Battery Electrolyte Discovery
Bioresources Valorization Laboratory
University of Benin
Project Title: Data-Driven Intelligent Modeling, Optimization, and Global Sensitivity Analysis of a Xanthan Gum Biosynthesis Process
Central Research Laboratory
University of Benin
Project Title: Optimization of Lipase Yield from Agricultural Waste Using Machine Learning
Work Experience
Egbin Power Plc
Operations and Chemistry Intern
Duration: 6 months
Publications
Stanley Aimhanesi Eshiemogie, Ritesh Kumar, Chibueze V. Amanchukwu, "Data Preprocessing and Machine Learning Modelling for Battery Electrolyte Discovery," 2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG), Omu-Aran, Nigeria, 2024. Link
Andrew Nosakhare Amenaghawon, Melissa Osagbemwenorhue Omede, Glory Odoekpen Ogbebor, Stanley Aimhanesi Eshiemogie. (2024). "Optimized biodiesel synthesis from an optimally formulated ternary feedstock blend via machine learning-informed methanolysis using a composite biobased catalyst." Bioresource Technology Reports, 25, 101805. Link
Andrew Nosakhare Amenaghawon, Shedrach Igemhokhai, Stanley Aimhanesi Eshiemogie, Favour Ugbodu, Nelson Iyore Evbarunegbe (2024). "Data-driven intelligent modeling, optimization, and global sensitivity analysis of a xanthan gum biosynthesis process." Heliyon, 10(3), e25432. Link
Steve Oshiokhai Eshiemogie, Joshua O. Ighalo, Michael Adekanbi, Titilope Banji, Stanley Aimhanesi Eshiemogie, Raymond Okoh, Chinenye Adaobi Igwegbe, Adewale George Adeniyi, Adedapo O. Adeola & Kanika Dulta (2023). "Current Effect and Projected Implications of Climate Change on Nigeria’s Sustainable Development Plan". Springer Climate, 1–17. Link