Cristina Marcu | Environmental Science | Best Researcher Award

Posted on 28/06/202428/06/2024 by ScienceFather

Cristina Marcu | Environmental Science | Best Researcher Award

Dr Cristina Marcu, National Institute for Research and Development of Isotopic and Molecular Technologies, Romania

Cristina Marcu, a dedicated chemist 🧪, specializes in adsorption studies using anion exchange resins. Her research, conducted at PIM Cluj-Napoca 🏛️, Romania, focuses on kinetics and thermodynamics of U(VI), Fe(III), and Cr(VI) adsorption. She has contributed significantly to understanding chemical exchange reactions and catalytic processes, presenting her findings at national and international conferences 🌍. Marcu’s work underscores her expertise in environmental chemistry and sustainable technologies, notably in uranium isotope enrichment and pollutant removal from aqueous solutions. Her collaborations with Damian Axente and Ancuţa Balla highlight her impactful contributions to the field. 📊

Publication profile

Scopus

Research focus

Based on the published papers, Cristina Marcu’s research focus revolves around environmental chemistry and chemical engineering, with a specialization in adsorption processes and oxidation reactions. Her work includes investigating adsorption isotherms and kinetics for various contaminants like chromium (VI) and uranium (VI), using materials such as anion exchange resins and Dowex-Marathon resin. Additionally, she explores the catalytic oxidation of carbon monoxide and processes related to isotope production and nitrogen separation. 🌿🔬 Her studies contribute to environmental management and industrial processes involving chemical reactions and materials science.

Publication top notes

Compensation Effect in Catalytic Oxidation of Carbon Monoxide

INVESTIGATION OF CARBON MONOXIDE (CO) OXIDATION PROCESS FOR CONVERTING 13CO TO 13CO2

Adsorption Isotherms and Thermodynamics for Chromium (VI) Using an Anion Exchange Resin

Adsorption Kinetics of Chromium (VI) from Aqueous Solution Using an Anion Exchange Resin

Determination of nitrogen losses in the sulfuric acid solution, waste of the ¹⁵N separation plant

The production of the isotope ¹⁵N by isotopic exchange in nitrox system at pressure

The calculus of the operation parameters at pressure of the primary separation column of the 15n production plant

The energy consumptions for thermo-catalytic conversion of sulphuric acid into sulfphur dioxide for its recycling in the ¹⁵N production plant

Study of Fe(III) adsorption onto Dowex-Marathon resin, as a rate determining step of the U(IV) oxidation in ²³⁵U enrichment column

Kinetic and thermodynamic studies of U(VI) adsorption using Dowex-Marathon resin

Minseok Ryu | Energy and Sustainability | Best Researcher Award

Posted on 26/06/202426/06/2024 by ScienceFather

Minseok Ryu | Energy and Sustainability | Best Researcher Award

Assist Prof Dr Minseok Ryu, Arizona State University, United States

Dr. Minseok Ryu is an Assistant Professor at Arizona State University’s School of Computing and Augmented Intelligence since August 2023 👨‍🏫. He earned his Ph.D. in Industrial and Operations Engineering from the University of Michigan in 2020 🎓. His research focuses on optimization and machine learning applications in power systems and privacy-preserving federated learning 🔍⚡. Dr. Ryu has held positions at Argonne National Laboratory and Los Alamos National Laboratory 🏢. He has received numerous awards, including the 2024 Alliance Fellowship at Mayo Clinic and ASU and multiple research highlights from the DOE-ASCR 🌟.

Publication profile

google scholar

Education

Minseok Ryu holds a Ph.D. in Industrial and Operations Engineering from the University of Michigan, Ann Arbor, which he completed in May 2020 🎓. Before that, he earned an M.S. in Aerospace Engineering from KAIST, Daejeon, Korea, in February 2014 🚀. His academic journey began with a B.S. in Aerospace Engineering from KAIST, which he obtained in February 2012 ✈️.

Employment

Minseok Ryu is currently an Assistant Professor at the School of Computing and Augmented Intelligence at Arizona State University in Tempe, AZ (Aug 2023–present) 📚. Previously, he was a Postdoctoral Appointee at the Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL (Aug 2020–Jul 2023) 🔬. He also worked as a Research Assistant with the Applied Mathematics and Plasma Physics Group, Los Alamos National Laboratory, Los Alamos, NM (May 2019–Aug 2019) 🧪. Additionally, he served as a Post Baccalaureate Research Fellow at the Kellogg School of Management, Northwestern University, Evanston, IL (Nov 2014–Apr 2015) 🎓.

Honors & Awards

Minseok Ryu has achieved numerous accolades throughout his career. In 2024, he was honored as an Alliance Fellow by the Mayo Clinic and ASU Alliance for Health Care and participated in the Faculty Summer Residency program. His research was highlighted by the Department of Energy’s Advanced Scientific Computing Research (DOE-ASCR) in both 2023 and 2022. Ryu received the Rackham Graduate Student Research Grant in 2016 and multiple fellowships from the University of Michigan in 2015. Additionally, he earned the National Science Foundation Student Award from INFORMS Computing Society. Earlier, he received the National Scholarship from the Korean government (2010-2013) and accolades from KAIST, including the Department Honor and Best Technical Poster Award in 2010. 🎓🔬📊

Presentations

Minseok Ryu has made significant contributions to various fields, presenting his research at numerous esteemed conferences. His work includes heuristic algorithms for geomagnetically induced current blocking devices (Paris, June 2024) 🌍⚡, generating columns (Phoenix, Oct 2023) 📝, and differentially private algorithms for constrained federated learning (Seattle and Amsterdam, 2023) 🔒🤖. He has also focused on privacy-preserving federated learning frameworks (Arlington, Aug 2022; Virtual, June 2022) 🛡️📡. Additionally, he has explored optimal power flow control, transmission expansion planning, and robust optimization in healthcare staffing across various platforms including INFORMS, SIAM, and international symposiums 🌐🧑‍⚕️

Research focus

Minseok Ryu’s research primarily focuses on data-driven optimization and privacy-preserving techniques, particularly in federated learning and power systems. His work spans several areas, including robust optimization under uncertainty, privacy-preserving distributed control, and federated learning frameworks. Key applications include improving nurse staffing models, optimizing electric grids against geomagnetic disturbances, and developing secure frameworks for federated learning in biomedical research. Ryu’s contributions are significant in ensuring privacy and robustness in distributed systems and optimization problems. 🧠🔒💡🔋👩‍⚕️

Publication top notes

Data-Driven Distributionally Robust Appointment Scheduling over Wasserstein Balls

APPFL: Open-Source Software Framework for Privacy-Preserving Federated Learning

A Privacy-Preserving Distributed Control of Optimal Power Flow

An extended formulation of the convex recoloring problem on a tree

Nurse Staffing under Absenteeism: A Distributionally Robust Optimization Approach

Differentially private federated learning via inexact ADMM with multiple local updates

Mitigating the Impacts of Uncertain Geomagnetic Disturbances on Electric Grids: A Distributionally Robust Optimization Approach

Algorithms for Mitigating the Effect of Uncertain Geomagnetic Disturbances in Electric Grids

Development of an Engineering Education Framework for Aerodynamic Shape Optimization

Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx

Environmental Impact Award

Posted on 22/02/202422/02/2024 by ScienceFather

Environmental Impact Award

Introduction:

Welcome to the Environmental Impact Award, recognizing exceptional contributions to environmental conservation and sustainability. This award celebrates individuals or organizations making significant strides towards protecting our planet and promoting a more sustainable future.

About the Award:

The Environmental Impact Award honors those who have demonstrated exemplary leadership and innovation in addressing environmental challenges. From conservation efforts to sustainable practices, this award celebrates initiatives that make a positive impact on our planet.

Eligibility:

Open to individuals, organizations, and initiatives worldwide
No age limits
Candidates must have implemented or contributed to projects with measurable environmental impact
Publications, if any, should demonstrate a commitment to environmental stewardship

Recurrence:

Annual

Evaluation Criteria:

Demonstrated environmental impact
Innovation and creativity in approach
Sustainability and scalability of the initiative
Engagement and collaboration with stakeholders

Submission Guidelines:

Submit a detailed description of the environmental initiative or project
Provide evidence of measurable impact, such as data or case studies
Include any relevant publications or documentation supporting the initiative's effectiveness
Follow the specified format and submission deadlines

Recognition:

Recipients of the Environmental Impact Award receive a prestigious certificate, public recognition through various channels, and opportunities for further collaboration and support.

Community Impact:

The Environmental Impact Award aims to inspire and mobilize communities to take action in safeguarding our planet. By recognizing and promoting environmental stewardship, this award fosters a sense of collective responsibility and encourages widespread engagement in conservation efforts.

Biography:

Applicants are invited to provide a brief biography highlighting their involvement in environmental initiatives, relevant experience, and notable achievements.

Abstract and Supporting Files:

Include a comprehensive abstract summarizing the environmental initiative's objectives, strategies, and outcomes. Supporting files such as project reports, testimonials, and multimedia materials can enhance the submission and demonstrate the initiative's impact.