Carlos Junqueira Junior | High Performance Computing | Research Excellence Award

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Dr. Carlos Junqueira Junior | High Performance Computing | Research Excellence Award

École Nationale d’Arts et Métiers | France

Dr. Carlos Junqueira Junior is an accomplished computational fluid dynamics (CFD) researcher and HPC specialist with extensive experience in numerical modeling for fluids and solids. He earned his Ph.D. in Aerospace Engineering from Instituto Tecnológico de Aeronáutica (ITA), Brazil, focusing on the development of parallel solvers for large eddy simulation of supersonic jet flows, following an MSc on upwind parallel solvers for turbulent flow applications. He also holds a Diplôme d’Ingénieur from Grenoble INP, France, where he conducted research on numerical modeling during an internship at CEA, and a Mechanical Engineering degree from UNESP, Brazil. Professionally, he has contributed significantly as an HPC Research Engineer at Arts et Métiers ParisTech, France, and held research and teaching positions at ITA, IAE, and CTMSP, Brazil, where he developed parallel CFD solvers for RANS and LES simulations and taught numerical methods to engineering students. His research interests include high-performance computing, turbulence modeling, supersonic flows, and numerical methods for fluid dynamics. Dr. Junqueira’s work has been recognized internationally for advancing simulation techniques in aerospace and turbo machinery applications. His contributions continue to impact computational engineering, bridging fundamental research and practical applications in CFD.

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Dr. Abhijeet Das | Environmental Pollution | Environmental Chemistry Commitment Award

Published on by Research Chemistry Awards

Dr. Abhijeet Das | Environmental Pollution | Environmental Chemistry Commitment Award

C.V. Raman Global University (CGU), Bhubaneswar | India

Dr. Abhijeet Das is a dedicated researcher and academic in the field of Water Resource Engineering, with a strong background in civil and environmental studies. He holds a Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar (2024), an M.Tech in Water Resource Engineering from Biju Patnaik University of Technology, Rourkela (2017), and a B.Tech in Civil Engineering from the same university (2015). With over ten years of cumulative professional experience, he has contributed as a Project Consultant at Madhu Smita Design & Engineers Studio, Bhubaneswar, and served as a faculty member at IGIT Sarang and CET Bhubaneswar, shaping the academic and professional growth of students. His research interests span watershed hydrology, hydrological modeling, hydrologic extremes such as floods and droughts, climate change impact assessment, food-energy-water nexus, machine learning, GIS and remote sensing, simulation-optimization, water quality, and environmental impact assessment. He has been widely recognized for his scholarly contributions, securing numerous Best Paper Awards at prestigious national and international conferences for his innovative approaches in surface water quality assessment and hydrological studies. Driven by a passion for sustainable water management and advanced geospatial techniques, Dr. Das continues to make impactful contributions to the field of water resources engineering.

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Featured Publications

An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance

Reimagining biofiltration for sustainable industrial wastewater treatment

A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in Mahanadi River Basin, Odisha, India

Evaluation and prediction of surface water quality status for drinking purposes using an integrated water quality indices, GIS approaches, and machine learning techniques

Bioplastics: a sustainable alternative or a hidden microplastic threat?

Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning analysis

Geographical Information System–driven intelligent surface water quality assessment for enhanced drinking and irrigation purposes in Brahmani River, Odisha (India)