Yiliang He

ORCID: 0000-0001-7672-5727
Publications
Citations
Views
---
Saved
---
About
Contact & Profiles
Research Areas
  • Pharmaceutical and Antibiotic Environmental Impacts
  • Membrane Separation Technologies
  • Aquatic Ecosystems and Phytoplankton Dynamics
  • Microbial Community Ecology and Physiology
  • Anaerobic Digestion and Biogas Production
  • Wastewater Treatment and Nitrogen Removal
  • Microbial Fuel Cells and Bioremediation
  • Marine and coastal ecosystems
  • Microplastics and Plastic Pollution
  • Water Treatment and Disinfection
  • Advanced Photocatalysis Techniques
  • Nanoparticles: synthesis and applications
  • Advanced oxidation water treatment
  • Graphene and Nanomaterials Applications
  • Antibiotic Resistance in Bacteria
  • Toxic Organic Pollutants Impact
  • Fullerene Chemistry and Applications
  • Environmental DNA in Biodiversity Studies
  • Environmental Chemistry and Analysis
  • Effects and risks of endocrine disrupting chemicals
  • Electrospun Nanofibers in Biomedical Applications
  • Membrane-based Ion Separation Techniques
  • Antibiotic Use and Resistance
  • Recycling and Waste Management Techniques
  • Advanced Sensor and Energy Harvesting Materials

Shanghai Jiao Tong University
2016-2025

National University of Singapore
2021-2025

Singapore-HUJ Alliance for Research and Enterprise
2021-2024

Jiangsu University of Technology
2023-2024

Chinese Academy of Tropical Agricultural Sciences
2024

Nanjing Hydraulic Research Institute
2023

Yancheng Teachers University
2023

Shanghai Institute of Pollution Control and Ecological Security
2018-2022

Hengshui University
2020

National Institute of Clean and Low-Carbon Energy
2020

Abstract The utilization of biochar derived from biomass residue to enhance anaerobic digestion (AD) for bioenergy recovery offers a sustainable approach advance energy and mitigate climate change. However, conducting comprehensive research on the optimal conditions AD experiments with addition poses challenge due diverse experimental objectives. Machine learning (ML) has demonstrated its effectiveness in addressing this issue. Therefore, it is essential provide an overview current...

10.1007/s43979-023-00078-0 article EN cc-by Carbon Neutrality 2024-01-08
Coming Soon ...