Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

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Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

Ms. Xinlu Bai, Changchun university, China

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, following an Engineering Degree from Zhengzhou University of Finance and Economics (2018-2022). Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His research includes the development of the GR-YOLO algorithm, which improves detection performance over existing methods like YOLOv8, with notable advancements in accuracy across various datasets. Xinlu’s work has been published in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. He has been recognized for his excellence in competitions, winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

Professional Profile:

Orcid

Suitability Summary for Best Researcher Award

Researcher: Xinlu Bai

Summary:

Xinlu Bai is a highly qualified candidate for the Best Researcher Award, distinguished by his innovative research and significant contributions to the field of computer science, particularly in pedestrian detection technology. Bai’s work demonstrates a clear commitment to advancing technology through rigorous research and practical applications.

🎓Education:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, which he has been enrolled in since 2023. He previously completed his Engineering Degree at Zhengzhou University of Finance and Economics, where he studied from 2018 to 2022. Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His development of the GR-YOLO algorithm, which enhances detection performance compared to YOLOv8, has been recognized through publications in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. His excellence has been acknowledged in various competitions, including winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

🏆Awards:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, having previously completed his Engineering Degree at Zhengzhou University of Finance and Economics. His contributions to computer vision, particularly through the development of the GR-YOLO algorithm, have been published in Sensors and guided by Professors Deyou Chen and Nianfeng Li. Xinlu’s excellence in the field has been recognized with several prestigious awards: he won the First Prize in the Jilin Province Virtual Reality Competition, the Second Prize in the China Virtual Reality Competition (Data Visualization Track), and the Third Prize in the Jilin Province Ruikang Robot Competition.

Publication Top Notes:

Title: Dense Pedestrian Detection Based on GR-YOLO

 

 

 

Dr. Srinivas Balivada | Hidden Sensors Award | Best Researcher Award

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Dr. Srinivas Balivada | Hidden Sensors Award | Best Researcher Award

Dr. Srinivas Balivada, University of Chicago Trust, India

Dr. Srinivasa Balivada is a consultant with the University of Chicago Trust in Delhi, India, and a guest scientist at the University of Chicago. He holds a Ph.D. in Chemistry from Andhra University, where his research focused on trace elements in diabetes mellitus and hypertension. Dr. Balivada’s expertise lies in developing innovative cyber-physical systems for real-time monitoring of soil and water quality, leveraging AI to promote sustainable environmental management.

Professional Profile:

Summary of Suitability for Best Researcher Award: Srinivasa Balivada, Ph.D.

Research Contributions: Srinivasa Balivada has made significant advancements in the field of cyber-physical systems and environmental monitoring. His research has been pivotal in developing innovative technologies for real-time soil and water quality monitoring, leveraging machine learning and advanced sensor networks. Some notable contributions include:

Education

  • Ph.D. in Chemistry, October 2018
    Andhra University, India
  • M.Sc. in Bio-Inorganic Chemistry, May 2007
    Andhra University, India
  • B.Sc. in Chemistry, Botany, and Zoology, May 2005
    Andhra University, India

Work Experience

  • Guest Scientist & Consultant, May 2024 – Present
    University of Chicago & University of Chicago Trust, Delhi, India
    Focus: Designing a web-based platform integrating water quality data with contextual information to identify pollution sources and enhance monitoring.
  • Staff Scientist & Resident Associate, May 2023 – May 2024
    University of Chicago & Material Science Division, Argonne National Laboratory
    Focus: Developed a novel machine learning algorithm for spatially mapping soil moisture using topographic parameters.
  • Postdoctoral Scholar & Resident Associate, May 2019 – May 2023
    University of Chicago & Material Science Division, Argonne National Laboratory
    Advisor: Prof. Supratik Guha; Co-advisor: Dr. Roser Matamala
    Focus: Developed low-power, wireless underground sensor networks for soil property collection; created a deep learning algorithm for soil moisture estimation.
  • Senior Research Lead, May 2017 – April 2019
    University of Chicago Centre, Delhi, India
    Focus: Developed a cyber-physical sensing system for high-resolution surface water quality mapping; created a soft measurement technique for water quality assessment.
  • Research Scholar, 2010 – 2017
    School of Chemistry, Andhra University, India
    Advisor: Prof. M S Prasada Rao
    Focus: Developed a method for simultaneous trace element determination in blood samples; investigated trace element associations with diabetes and hypertension.
  • Research Fellow, 2010 – 2017
    Centre for Studies on Bay of Bengal, Andhra University, India
    Focus: Developed algorithms for quantifying chlorophyll, chromophoric organic matter, and suspended solids in coastal waters; monitored algal blooms using satellite remote sensing.
  • Teaching Assistant, 2011 – 2017
    Department of Inorganic and Analytical Chemistry, Andhra University, India
    Taught and graded laboratory sessions for Bio-Inorganic Chemistry and Environmental Chemistry.
  • Chemist in Quality Control Department, 2007 – 2009
    Auctus Pharma Ltd., India
    Responsibilities: Conducted routine and non-routine analyses of raw materials and finished products, compiled data, and calibrated analytical instruments including HPLC, GC, IR, and UV-Vis spectrometers.

Publication top Notes:

 

Distribution of trace metals in surface seawater and zooplankton of the Bay of Bengal, off Rushikulya estuary, East Coast of India

CITED:76

A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation

CITED:14

Contrasting bio-optical characteristics of coastal water prior to and in the aftermath of a tropical super cyclone

CITED:8

Particle backscattering variability in the coastal waters of Bay of Bengal: a case study along off Kakinada and Yanam regions

CITED:8

Retrieval and validation of chlorophyll-a concentrations in the coastal waters Off Yanam and Kakinada (Godavari) basin along East coast of India

CITED:7

 

Dr. Hebat-Allah S. Tohamy | Chemical sensors | Best Researcher Award

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Dr. Hebat-Allah S. Tohamy | Chemical sensors | Best Researcher Award 

Dr. Hebat-Allah S. Tohamy, National Research Centre, Egypt

Dr. Hebat-Allah Sarhan Abd-Allah Tohamy, born on November 17, 1989, in Egypt, is an accomplished chemist with a strong academic and professional background. She earned her B.Sc. in Chemistry and Biochemistry with honors in 2011 and her M.Sc. in Organic Chemistry in 2017 from Helwan University. She completed her Ph.D. in Organic Chemistry in 2020 at the same institution, focusing on the preparation, characterization, and applications of carbon allotropes derived from agricultural wastes. Since 2012, Dr. Tohamy has been affiliated with the National Research Center’s Cellulose and Paper Department, where she has gained extensive experience in cellulose chemistry, nanomaterials, sustainability, and drug delivery systems. She has conducted scientific missions in Prague and has been involved in numerous research projects and international collaborations. Her work has earned her recognition, including the best M.Sc. thesis award at the National Research Centre in 2017. Dr. Tohamy is also a member of professional organizations such as the Egyptian Society of Polymer Science and Technology and the Organization for Women in Science for the Developing World (OWSD).

Professional Profile:

ORCID 

 

SCOPUS

 

Education:

  • Ph.D. in Organic Chemistry
    Faculty of Science, Helwan University, 2020
    Thesis Title: Preparation, characterization, and applications of carbon allotropes derived from agricultural wastes
  • M.Sc. in Organic Chemistry
    Faculty of Science, Helwan University, 2017
    Thesis Title: Preparation, characterization, and applications of cellulose-based amphiphilic materials
  • B.Sc. in Chemistry and Biochemistry
    Faculty of Science, Helwan University, 2011
    Graduated with Very Good with honors (among the top ten students)

Work Experience:

  • Teaching Assistant with Ph.D.
    Chair of Erosion and Torrent Control, Department of Ecological Engineering for Soil and Water Resources Protection, University of Belgrade – Faculty of Forestry, June 2022 – Present
    Responsible for teaching and research activities related to erosion control and soil and water conservation.
  • Teaching Assistant
    Chair of Erosion and Torrent Control, Department of Ecological Engineering for Soil and Water Resources Protection, University of Belgrade – Faculty of Forestry, April 2016 – June 2022
    Assisted in teaching and research, focusing on erosion control and ecological engineering.
  • Volunteer and Demonstrator
    University of Belgrade – Faculty of Forestry, November 2015 – April 2016
    Gained practical experience in teaching and laboratory work, contributing to various projects in ecological engineering.
  • Researcher
    National Research Center (NRC), Cellulose and Paper Department, since 2012
    Conducted extensive research in cellulose chemistry, recycling agricultural wastes, sustainability, kinetics, thermal analysis, hydrogels, nanomaterials, and amphiphilic polymers. Specialized in carbon-based materials, graphene oxide, carbon nanotubes, carbon quantum dots, drug delivery, water treatment, adsorption, and sensors.

Publication top Notes:

Biodegradable carboxymethyl cellulose based material for sustainable/active food packaging application

Fluorescence ‘Turn-on’ Probe for Chromium Reduction, Adsorption and Detection Based on Cellulosic Nitrogen-Doped Carbon Quantum Dots Hydrogels

Antibacterial activity and dielectric properties of the PVA/cellulose nanocrystal composite using the synergistic effect of rGO@CuNPs

Potential application of hydroxypropyl methylcellulose/shellac embedded with graphene oxide/TiO2-Nps as natural packaging film

Applications of propolis-based materials in wound healing

Oil dispersing and adsorption by carboxymethyl cellulose–oxalate nanofibrils/nanocrystals and their kinetics

 

Sensors for high energy physics applications

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Introduction of Sensors for high energy physics applications

Sensors for high energy physics applications are at the forefront of scientific discovery, enabling the detection and measurement of subatomic particles and phenomena in particle accelerators and detectors.

Particle Detectors:

Investigating the development of particle Detectors including silicon strip detectors calorimeters and time-of-flight detectors used to identify and track particles produced in high-energy collisions.

Radiation-Hard Sensors:

Focusing on sensors and materials that can withstand the intense radiation Environments found in particle Physics experiments ensuring long-term reliability and accuracy.

Fast Timing Detectors:

Addressing the need for sensors with high temporal Resolution for time-of-flight Measurements particle identification, and the study of short-lived particles.

Gas and Liquid Detectors:

Analyzing gas and liquid detectors. such as drift chambers and time projection Chambers, used for precise particle tracking and momentum measurement.

Trigger and Data Acquisition Systems:

Investigating sensor technologies integrated into Trigger and data Acquisition systems to efficiently select and record relevant collision events in real-time from the vast data generated in high-energy physics experiments.