Naga Nithin Katta | Image Processing | Best Researcher Award

Mr. Naga Nithin Katta | Image Processing | Best Researcher Award

Employee at Oppo | India

Naga Nithin Katta is a highly motivated computer science and engineering professional with a strong focus on innovation, research, and problem-solving. His expertise spans artificial intelligence, machine learning, computer vision, and full stack development, areas in which he has applied his skills to impactful projects. He has gained industrial exposure as a software engineer at OPPO, where he contributed to projects involving video stream analysis, automation of testing frameworks, and mobile AI deployment. Alongside his industry experience, he has been an active mentor in data structures and algorithms, helping students strengthen their problem-solving abilities. His leadership has been recognized through international competitions, including selection among the Top 100 teams globally in the Google Solution Challenge and multiple hackathon victories. With a balance of technical knowledge, practical implementation, and a passion for community contribution, he is steadily building a strong foundation as an emerging researcher with promising leadership potential.

Professional Profile

Scopus Profile

Education

Naga Nithin Katta is pursuing a Bachelor of Technology in Computer Science and Engineering at VNR Vignana Jyothi Institute of Engineering and Technology, where he has been developing a strong academic background in computing principles, software engineering, and applied technologies. Prior to this, he successfully completed a diploma in computer science from the Government Institute of Electronics, which provided him with a solid technical base in programming, database management, and system design. His educational journey has been complemented by active participation in research-oriented projects, hackathons, and collaborative learning platforms that encouraged innovation and problem-solving. He has consistently demonstrated academic excellence by integrating classroom knowledge with practical applications, which is evident in his project work and international recognition through competitive platforms. This strong educational foundation has equipped him with both theoretical and applied perspectives, allowing him to bridge the gap between academia and industry while nurturing his passion for research and development.

Professional Experience

Naga Nithin Katta has gained valuable professional experience as a software engineer at OPPO, where he contributed to significant projects aimed at improving efficiency and automation in mobile technologies. His work involved developing web applications using Vue.js and MySQL for managing project statuses, implementing video stream analysis through OpenCV and Python, and deploying AI models on mobile devices using ONNX and Beeware. He played a key role in creating a UI automation system powered by large language models, reducing manual testing efforts and enhancing accuracy. Additionally, he contributed to building a network operator testing automation tool, streamlining processes and reducing workforce requirements. Alongside his industry work, he served as a student mentor at SmartInterviews, guiding learners in data structures and algorithms and preparing them for technical challenges. This blend of industrial expertise and teaching experience reflects his versatility, ability to collaborate across teams, and passion for applying research in practical contexts.

Research Interest

Naga Nithin Katta’s research interests lie primarily in the fields of artificial intelligence, computer vision, natural language processing, and software engineering, with a particular focus on developing innovative solutions that bridge academic research and real-world applications. He has worked on projects such as sign language converters that integrate computer vision with generative AI and cloud technologies, reflecting his interest in human-computer interaction and accessibility-focused applications. His engagement with large language models and UI automation tools demonstrates his curiosity in advancing human-machine interaction and automated testing frameworks. Additionally, his focus on video stream analysis and frame detection highlights his inclination towards multimedia research and visual computing. He is also keen on exploring areas such as deep learning optimization, mobile AI deployment, and cloud-integrated intelligent systems. His vision is to contribute to impactful solutions that enhance everyday technologies while simultaneously pursuing scholarly outputs that advance scientific knowledge.

Research Skill

Naga Nithin Katta has developed strong research skills that enable him to design, implement, and evaluate innovative solutions across different domains of computer science. He is proficient in programming languages such as C, C++, Python, and Java, and demonstrates advanced knowledge in full stack development with tools like ReactJs, Vue.js, and MySQL. His expertise in AI and machine learning is reflected in projects involving computer vision, natural language processing, and model deployment on mobile devices. He has practical experience in research-driven software development, having implemented algorithms for video frame detection, gesture recognition, and UI automation powered by large language models. His familiarity with tools like OpenCV, ONNX, Flask, and cloud-based APIs allows him to conduct applied research efficiently. He also possesses strong problem-solving abilities, demonstrated by his role as a mentor in data structures and algorithms. His skills in bridging theoretical concepts with industrial applications showcase his potential as a future research leader.

Publications Top Notes

Title: Optical Motion Detection Language Generator: A Survey

Year: 2025

Conclusion

Naga Nithin Katta is a deserving candidate for the Best Researcher Award as he has consistently demonstrated innovation, technical expertise, and leadership in both academic and industrial settings. His impactful projects, including advancements in computer vision, automation, and AI-driven solutions, showcase contributions that address real-world challenges and benefit society. With proven recognition in global competitions, mentorship roles, and industry research experience, he has already made meaningful strides as an emerging researcher. With a continued focus on publishing in reputed venues and building stronger international collaborations, he holds significant potential to become a future leader in the research and technology community.

Dr. Abdelaziz Daoudi | Image Processing | Best Researcher Award

Dr. Abdelaziz Daoudi | Image Processing | Best Researcher Award

Doctorate at Tahri Mohammed university, Algeria

👨‍🎓 Profiles

Scopus

Google Scholar

Publications

Enhancing Brain Segmentation in MRI through Integration of Hidden Markov Random Field Model and Whale Optimization Algorithm

  • Authors: Abdelaziz Daoudi, Saïd Mahmoudi
    Journal: Computers
    Year: 2024

Benchmark for algorithms segmenting the left atrium from 3D CT and MRI datasets

  • Authors: Catalina Tobon-Gomez, Arjan J Geers, Jochen Peters, Jürgen Weese, Karen Pinto, Rashed Karim, Mohammed Ammar, Abdelaziz Daoudi, Jan Margeta, Zulma Sandoval, Birgit Stender, Yefeng Zheng, Maria A Zuluaga, Julian Betancur, Nicholas Ayache, Mohammed Amine Chikh, Jean-Louis Dillenseger, B Michael Kelm, Saïd Mahmoudi, Sébastien Ourselin, Alexander Schlaefer, Tobias Schaeffter, Reza Razavi, Kawal S Rhode
    Journal: IEEE transactions on medical imaging
    Year: 2015

Prof Dr. Oliver Steinbock | Image Processing and Enhancement | Best Researcher Award

Publications

Understanding the Salt Crystallizations from Droplets under Various Gravity and Pressure Environments: Display of the Marangoni Effect?

  • Authors: Hadidi, R.; Pinckney, V.D.; Shaw, S.A.; Steinbock, O.; Dangi, B.B.
    Journal: Journal of Physical Chemistry B
    Year: 2025

High-throughput robotic collection, imaging, and machine learning analysis of salt patterns: composition and concentration from dried droplet photos

  • Authors: Batista, B.C.; Amrutha, S.V.; Yan, J.; Dangi, B.B.; Steinbock, O.
    Journal: Digital Discovery
    Year: 2025

Wavebreakers in excitable systems and possible applications for corrosion mitigation

  • Authors: Batista, B.C.; Romanovskaia, E.V.; Romanovski, V.I.; Kiss, I.Z.; Steinbock, O.
    Journal: Chaos
    Year: 2025

Morphogenic Modeling of Corrosion Reveals Complex Effects of Intermetallic Particles

  • Authors: Batista, B.C.; Romanovskaia, E.V.; Romanovski, V.I.; Scully, J.R.; Steinbock, O.
    Journal: Advanced Science
    Year: 2024

Chemical composition from photos: Dried solution drops reveal a morphogenetic tree

  • Authors: Batista, B.C.; Tekle, S.D.; Yan, J.; Dangi, B.B.; Steinbock, O.
    Journal: Proceedings of the National Academy of Sciences of the United States of America (PNAS)
    Year: 2024

Assoc Prof Dr. Burcu Tunga | Image Processing | Best Researcher Award

Assoc Prof Dr. Burcu Tunga | Image Processing | Best Researcher Award

Burcu Tunga at Istanbul Technical University, Turkey

👨‍🎓 Profiles

Scopus

Orcid

Google Scholar

Publications

Contrast and Content Preserving HDMR-Based Color-to-Gray Conversion

  • Authors: Ayça Ceylan, Evrim Korkmaz Özay, Burcu Tunga
  • Journal: Computers & Graphics
  • Year: 2024

A Novel Image Denoising Technique with Caputo Type Space–Time Fractional Operators

  • Authors: Evren Tanriover, Ahmet Kiris, Burcu Tunga, M. Alper Tunga
  • Journal: Nonlinear Dynamics
  • Year: 2024

High Dimensional Model Representation Median Filter for Removing Salt and Pepper Noise

  • Authors: Sena Kacar, Burcu Tunga
  • Journal: Signal, Image and Video Processing
  • Year: 2024

Machine Learning Based Tomographic Image Reconstruction Technique to Detect Hollows in Wood

  • Authors: E. N. Yıldızcan, M. E. Arı, Burcu Tunga, N. As, T. Dündar
  • Journal: Wood Science and Technology
  • Year: 2024

DeepEMPR: Coffee Leaf Disease Detection with Deep Learning and Enhanced Multivariance Product Representation

  • Authors: A. Topal, Burcu Tunga, E. B. Tirkolaee
  • Journal: PeerJ Computer Science
  • Year: 2024

Mr. Jiatai Wang | Image Processing | Best Researcher Award

Mr. Jiatai Wang | Image Processing | Best Researcher Award

Jiatai Wang at Shandong University of Finance and Economics, China

Profile

Orcid

Summary:

Mr. Jiatai Wang is a postgraduate student specializing in edge computing and hyperspectral image analysis at Shandong University of Finance and Economics. With a strong academic background and a focus on developing advanced algorithms for image processing, Jiatai has published in both international conferences and SCI-indexed journals, earning recognition for innovative contributions in computer vision and data analytics.

Education

Mr. Jiatai Wang holds a Master’s degree in Computer Science and Technology, with a specialization in edge computing and hyperspectral image analysis.

💼 Professional Experience

As a Master’s graduate, Jiatai has conducted significant research in image processing, leading to the publication of one paper in an EI International Conference and another in an SCI-indexed journal. His work has been acknowledged through various academic awards.

🔬 Research Interests

Mr. Jiatai’s research interests include edge computing, hyperspectral image analysis, and the development of efficient algorithms for image processing. His work aims to enhance computer vision and data analytics capabilities.

 

Publication

Elastic Reweighted Sparsity Regularized Sparse Unmixing for Hyperspectral Image Analysis

  • Authors: Jiatai Wang, Qiuyue Zhang, Yunfeng Zhang
  • Journal: Digital Signal Processing
  • Year: 2024

Dr. Yue Cao | Image Processing | Best Researcher Award

Dr. Yue Cao | Image Processing | Best Researcher Award

Doctorate at Harbin Institute of Technology, China

Profile

Google Scholar

📋 Summary

Yue Cao is a Ph.D. candidate at Harbin Institute of Technology, specializing in computational imaging. His work focuses on noise modeling and image enhancement in extreme low-light conditions, making significant strides in sensor technology and image processing.

Education

  • Ph.D., Computer Application Technology (Sep. 2020 – Present), Harbin Institute of Technology
  • M.S., Computer Software and Theory (Sep. 2017 – Aug. 2020), Shaanxi Normal University
  • B.S., Software Engineering (Sep. 2010 – Aug. 2014), Inner Mongolia University

💼 Internship Experience

  • Industry-Academia-Research Project Intern
    OPPO Research Institute, Shenzhen
    Feb. 2023 – Feb. 2024 (estimated)
    Engaged in noise modeling and parameter calibration of mobile phone sensors, as well as joint denoising, demosaicking, and super-resolution tasks in extremely low-light conditions related to smartphone sensor technology.

🏆 Selected Awards

  • 2020: Winner Award, NTIRE Real Image Denoising Challenge – rawRGB Track
  • 2020: 3rd Place Award, NTIRE Real Image Denoising Challenge – sRGB Track
  • 2014: Outstanding Graduate of Inner Mongolia Autonomous Region, P.R. China
  • 2012: Excellent Three Merit Student Award of Inner Mongolia Autonomous Region, P.R. China

🔬 Research Interests

Dr. Yue’s research interests include noise modeling, image denoising, demosaicking, super-resolution, and sensor technology, with a particular focus on improving imaging performance in challenging environments.

Publications

Physics-guided iso-dependent sensor noise modeling for extreme low-light photography

  • Authors: Yue Cao, Ming Liu, Shuai Liu, Xiaotao Wang, Lei Lei, Wangmeng Zuo
  • Year: 2023

Incorporating Semi-Supervised and Positive-Unlabeled Learning for Boosting Full Reference Image Quality Assessment

  • Authors: Yue Cao, Zhaolin Wan, Dongwei Ren, Zifei Yan, Wangmeng Zuo
  • Year: 2022

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser

  • Authors: Yue Cao, Xiaohe Wu, Shuran Qi, Xiao Liu, Zhongqin Wu, Wangmeng Zuo
  • Year: 2021

Unpaired learning of deep image denoising

  • Authors: Xiaohe Wu, Ming Liu, Yue Cao, Dongwei Ren, Wangmeng Zuo
  • Year: 2020

Ntire 2020 challenge on real image denoising: Dataset, methods and results

  • Authors: Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte, Michael S Brown
  • Year: 2020

Dr. Tirumala Vasu | Image Processing | Excellence In Research

Dr. Tirumala Vasu | Image Processing | Excellence In Research

Doctorate at Presidency University, India

Profiles

Scopus

Orcid

Google Scholar

Academic Background:

Dr. G. Tirumala Vasu is an accomplished Assistant Professor in the E.C.E Department at Presidency University, Bangalore, Karnataka, with over 14 years of extensive experience in academia. He is known for his dedication to teaching, research, and development in the field of Electronics and Communication Engineering. Dr. Vasu has made significant contributions to the academic community, publishing numerous research papers, presenting at national and international conferences, and securing patents. He has a strong background in Digital Image Processing, Deep Learning, and Digital Signal Processing, among other areas. He has also been recognized for his outstanding teaching and research efforts with various awards and honors.

Education:

Dr. Vasu earned his Ph.D. from the National Institute of Technology (NIT), Tiruchirappalli in February 2024, with a thesis titled “Multi Focus, Multi Exposure and Multi Sensor Image Fusion Using Edge Preserving Filters”. He holds an M.Tech in Digital Electronics and Communication Systems from JNTU Anantapur, completed in 2009 with first-class distinction, and a B.Tech in Electronics and Communication Engineering from Sri Venkateswara University, Tirupati, completed in 2007. Additionally, he has distinguished himself academically since his early education, consistently achieving first-class distinction throughout his studies.

Professional Experience:

Dr. Vasu has been serving as an Assistant Professor at Presidency University, Bangalore since July 2018. Previously, he held the same position at Siddharth Institute of Engineering and Technology, Puttur, Andhra Pradesh from June 2012 to May 2018, and at Regency Institute of Technology, Yanam, UT of Puducherry from December 2010 to June 2012. He began his academic career at KSRM College of Engineering, Kadapa, Andhra Pradesh, where he worked from August 2009 to December 2010. Throughout his career, Dr. Vasu has taught a wide range of subjects including Computational Intelligence, Machine Learning, Digital Signal Processing, and more. He has also been actively involved in various academic and research coordination roles.

Research Interests:

Dr. Vasu’s research interests are diverse and include Digital Image and Video Processing, Deep Learning and Machine Learning, Digital Signal Processing, 5G OTFS, Electromagnetic Waves and Transmission Lines, and Antennas and Wave Propagation. He has published 28 papers in international journals, presented at numerous conferences, and published 11 patents. His work has earned him accolades such as Best Paper awards and recognition for his innovative contributions to the field of Electronics and Communication Engineering.

 Publications:

Medical image registration with object deviation estimation through motion vectors using octave and level sampling
  • Authors: Nagarathna, P., Jeelani, A., Fiza, S., Vasu, G.T., Seelam, K.
  • Journal: Automatica
  • Year: 2024
Multi-exposure image fusion using structural weights and visual saliency map
  • Authors: Tirumala Vasu, G., Palanisamy, P.
  • Journal: Multimedia Tools and Applications
  • Year: 2024
Visible and Infrared Image Fusion Using Distributed Anisotropic Guided Filter
  • Authors: Vasu, G.T., Palanisamy, P.
  • Journal: Sensing and Imaging
  • Year: 2023
Improved chimp optimization algorithm (ICOA) feature selection and deep neural network framework for internet of things (IOT) based android malware detection
  • Authors: G.T.V., Fiza, S., Kumar, A.K., Kumar, C.N., Kubra, A.
  • Journal: Measurement: Sensors
  • Year: 2023
CT and MRI multi-modal medical image fusion using weight-optimized anisotropic diffusion filtering
  • Authors: Vasu, G.T., Palanisamy, P.
  • Journal: Soft Computing
  • Year: 2023

Prof. Zhi Gao | Image Processing | Best Researcher Award

Prof. Zhi Gao, Image Processing, Best Researcher Award

Zhi Gao at Wuhan University, China

Professional Profile

Summary:

Zhi Gao is a highly accomplished Professor and Doctoral Supervisor at the School of Remote Sensing and Information Engineering, Wuhan University. He holds prestigious positions as the National Young Talent Program and Distinguished Professor of Hubei Province, China. With a solid background in engineering and extensive experience in academia and research, he has built strong collaborative networks with renowned universities and institutions worldwide.

👩‍🎓Education:

Zhi Gao received his Bachelor of Engineering (B.Eng.) and Doctor of Philosophy (Ph.D.) degrees from Wuhan University, China, in 2002 and 2007, respectively. His educational background provides him with a strong foundation in his field.

🧬 Work Experience:

Zhi Gao’s professional journey reflects a wealth of experience in both academia and industry. Highlights of his career include:

  • Research Fellow (A) and Project Manager at the Interactive and Digital Media Institute, National University of Singapore (NUS), Singapore, since 2008.
  • Research Scientist (A) at the Temasek Laboratories, NUS, contributing significantly to research endeavors.
  • Building strong collaborative relationships with prestigious institutions globally, including the Temasek Laboratory, National University of Singapore, Carnegie Mellon University Robotics Institute, Robert Gordon University, The Chinese University of Hong Kong, Beijing Normal University, and Beijing Institute of Technology.

Research Interests:

  • Computer Vision
  • Machine Learning
  • Remote Sensing
  • UAV-based Surveillance Research and Applications

Publications Top Noted:

Paper Title: Exploring the relationship between land use change patterns and variation in environmental factors within urban agglomeration
  • Authors: Xiao, R., Yin, H., Liu, R., Liu, L., Jia, T.
  • Journal: Sustainable Cities and Society
  • Volume: 108
  • Pages: 105447
  • Year: 2024
  • Citations: 0
Paper Title: Tracking by Detection: Robust Indoor RGB-D Odometry Leveraging Key Local Manhattan World
  • Authors: Zhou, Z., Gao, Z., Xu, J.
  • Journal: IEEE Robotics and Automation Letters
  • Volume: 9
  • Issue: 6
  • Pages: 4990–4997
  • Year: 2024
Paper Title: How Challenging is a Challenge? CEMS: a Challenge Evaluation Module for SLAM Visual Perception
  • Authors: Zhao, X., Gao, Z., Li, H., Fang, H., Chen, B.M.
  • Journal: Journal of Intelligent and Robotic Systems: Theory and Applications
  • Volume: 110
  • Issue: 1
  • Pages: 42
  • Year: 2024
  • Citations: 0
Paper Title: TJ-FlyingFish: An Unmanned Morphable Aerial–Aquatic Vehicle System
  • Authors: Liu, X., Dou, M., Yan, R., Chen, J., Chen, B.M.
  • Journal: Unmanned Systems
  • Volume: 12
  • Issue: 2
  • Pages: 409–428
  • Year: 2024
  • Citations: 1
Paper Title: WaterFormer: A Global-Local Transformer for Underwater Image Enhancement With Environment Adaptor
  • Authors: Wen, J., Cui, J., Yang, G., Dou, L., Chen, B.M.
  • Journal: IEEE Robotics and Automation Magazine
  • Volume: 31
  • Issue: 1
  • Pages: 29–40
  • Year: 2024
  • Citations: 1