Mrs. Maria Arostgei | Artificial Intelligence | Best Researcher Award

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Mrs. Maria Arostgei | Artificial Intelligence | Best Researcher Award

PhD Candidate at Artificial Intelligence, Tecnalia Research Innovation, Spain

👨‍🎓She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Maria Arostegi 🎓 earned her mathematics degree (Number Theory) in 1995 from EHU-UPV (Basque Country University), completing her final year of studies at L’Università degli Studi di Milano in Milano, Italy 🇮🇹. In 1996, she completed the Course on Pedagogical Aptitude. Over the next two years, she received grants to work in the mechanics department of LABEIN, focusing on Virtual Reality. She then obtained another grant from the “Bizkaiko Foru Aldundia” to further her training on Virtual Reality tools at VRAC (Virtual Reality Applications Center, Ames-IA), where she worked with the Carolina Cruz-Neira research team. During this period, she focused on geometric modeling, software navigation, and photo-realistic treatment.

Experience:

From then until 2017, Maria worked on various projects related to 3D modeling tools, graphic interaction, computation, and simulation in different scenarios. She specialized in developing software predictive tools for rolling mills, continuous casting, and reheating furnaces. Specifically, she developed the heating module in 1D, 2D, and 3D, as well as software interfaces for these steel processes. This involved mathematical development of the three-dimensional equations of heat transfer in steel processes and the (2D and 3D) View factor related to the geometrical shapes in the reheating furnace process for calculating radiation heat transfer.

Other Activity:

In 2017, Maria shifted her focus to studying mathematical algorithms for data analytics, machine learning, and big data technologies (such as Hadoop, Spark, etc.), receiving training in “Big data, Business Intelligence, and Data Science” through an online Master’s degree issued by INESEM. Since then, she has participated in several AI projects using techniques such as Artificial Intelligence, Machine Learning, clustering schemes, dimensional reduction, unbalanced strategies, regressive schemes, linear, lasso, elastic-net, SVMs, CART, RF, and assembly methods (bagging and boosting).

Currently, Maria is working on her thesis titled “Explainable continual learning over data streams” as part of the PhD program at UPV/EHV in the field of Information and Communication Technologies in Mobile Networks, while also working part-time.

 

Mr. Wang Xiaofeng | Artificial Intelligence | Best Researcher Award

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Mr. Wang Xiaofeng | Artificial Intelligence | Best Researcher Award

PhD Student at Artificial Intelligence, INTI International University, Malaysia

👨‍🎓He remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 He successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

👨‍🎓 Xiaofeng Wang (1980) is a PhD candidate in the Faculty of Data Science and Information Technology at INTI International University, Nilai, Malaysia. Originally from Shanxi, China, he graduated from Xinzhou Normal University with a major in Computer Science and Technology. He furthered his education at Shanxi University, specializing in Computer Systems Engineering.

Other Activity:

👨‍🏫 Currently, Xiaofeng Wang is a lecturer in the Department of Computer Science at Xinzhou Normal University in Shanxi. His primary research interests revolve around the Internet of Things, cyberspace security, artificial intelligence, and deep learning. Over the past few years, he has made significant contributions to his field, with 3 SCI papers, 1 EI paper, 2 Scopus papers, 1 book, and involvement in several research projects.

Publications:

  1. Wang, X., Othman, M., Dewi, D.A., Wang, Y. (2024). WSLC: Weighted semi-local centrality to identify influential nodes in complex networks. Journal of King Saud University – Computer and Information Sciences, 36(1), 101906.
  2. Wang, X., Wang, Y., Javaheri, Z., Moghadamnejad, N., Younes, O.S. (2023). Federated deep learning for anomaly detection in the internet of things. Computers and Electrical Engineering, 108, 108651.
  3. Wang, Y., Wang, X., Ariffin, M.M., Alqhatani, A., Almutairi, L. (2023). Attack detection analysis in software-defined networks using various machine learning methods. Computers and Electrical Engineering, 108, 108655.
  4. Wang, X. (2013). The research of digital recognition technology based on bp neural network. BioTechnology: An Indian Journal, 8(2), 180–185.

 

 

Ms. Brittany Ho | Machine Learning | Best Researcher Award

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Ms. Brittany Ho | Machine Learning | Best Researcher Award

Ph.D. Scholar at Climate Change , Beijing Normal University, China

👨‍🎓She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Brittany Ho is currently pursuing a Bachelor of Science in Computer Science at the University of the Pacific, with an anticipated graduation date in Fall 2024. She has consistently achieved high academic performance, earning a place on the Dean’s Honor Roll with a GPA of 3.88 out of 4.00. Brittany’s coursework has focused on areas relevant to her field, including Artificial Intelligence, Computer Game Technologies, Computer Systems & Networks, and Analytics Computing Data Science. Her dedication to her studies and her coursework selection demonstrate her commitment to gaining a well-rounded understanding of computer science 🎓.

Skills:

Ms. Brittany Ho is proficient in several programming languages, including Java (advanced), C++ (advanced), Python (intermediate), Swift (beginner), and R (beginner). Her technical skills extend to working with relational databases, the MQTT protocol, the Linux operating system, GPT 3.5 Turbo, Logic Pro, and Unity. Additionally, she holds certifications and has completed training in various areas such as IP Addressing (LinkedIn), Cloud Computing (Coursera), Arduino Foundation (LinkedIn), MacOS System Administrators (LinkedIn), Unity Essentials (Unity), C# with Unity (LinkedIn), Social and Behavioral Research (CITI), and Learning Deep Learning (NVIDIA). 🖥️📊🔧

Projects and Research:

Ms. Brittany Ho has been making significant contributions in her roles. As a Performance Engineer Intern at NVIDIA Corporation, she is involved in comprehensive GPU performance benchmarking for High-Performance Computing (HPC) and Deep Learning (DL) frameworks and applications. Her responsibilities include developing Python scripts for automating testing and collaborating with the engineering team to troubleshoot and resolve performance issues, gaining valuable hands-on experience in problem-solving. Additionally, at the University of the Pacific, as a Research Assistant, she has played a pivotal role in developing an advanced NLP and Generative AI tool using Python and GPT 3.5 Turbo, contributing to a book chapter on “Machine Learning in Educational Sciences,” and leading a journal publication on ChatGPT integration in an NLP framework for targeted user review analysis. 🚀🔬👩‍💻

 

 

Mr.Syamasudha Veeragandham | Deep learning | Best Researcher Award

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Mr.Syamasudha Veeragandham| Deep learning | Best Researcher Award

Research Scholar, Vellore Institute of technology, Vellore

👨‍🎓She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

EDUCATION:

The user is currently pursuing a full-time Ph.D. in the School of Computer Science and Engineering at Vellore Institute of Technology-Vellore, starting from July 2019. They have previously completed an M.Tech in Computer Science and Engineering from PBR Visvodaya Institute of Technology, Kavali, affiliated with J.N.T.U.A, A.P, with an aggregate of 74.07% in 2011. Their undergraduate degree is a B.Tech in Computer Science and Engineering from Chadalawada Ramanamma Engineering College, Tirupati, with an aggregate of 60.78% in 2009. They completed their Intermediate education in M.P.C from Sri Sai Junior College, Kavali, with a percentage of 87.1% in 2005, and their SSC from Z.P.H. School, Gudlur, with a percentage of 61.00% in 2003.

EXPERIENCE:

The user has accumulated 8 years of teaching experience as an Assistant Professor in the CSE department at various institutions, including Annamacharya Institute of Technology & Sciences-Tirupati, Sree Rama Engineering College-Tirupati, and Ramireddy Subbaramireddy Engineering College-Kavali. They have been ratified as an assistant professor from JNTU-Anathapuramu. Their teaching portfolio includes a wide range of subjects at both undergraduate and postgraduate levels, such as Artificial Intelligence, Machine Learning, Deep Learning, Computer Organization, Microprocessors and interfacing, Computer Graphics, Data Mining, Data Warehousing, Discrete Mathematics (MFCS), C-Programming, Data Structures, Advanced Computer Network, and Java and Web Technologies. Additionally, they have guided numerous B.Tech and M.Tech projects, with 12 and 5 projects guided, respectively. In addition to teaching, they have taken on various administrative responsibilities, including acting as an in-charge for CO’S, PO’S, PSO’S, PEO’S in NBA and NAAC, as well as serving as a time-table in-charge, class in-charge, and project coordinator.

Syamasudha Veeragandham ‘s citation metrics and indices from Google Scholar are as follows:

  • Cited by: All: 33, Since 2018: 31
  • Citations: 33 (All), 31 (Since 2018)
  • h-index: 4 (All), 4 (Since 2018)
  • i10-index: 1 (All), 1 (Since 2018)

These metrics showcase the impact of Veeragandham ‘s work within the academic community, demonstrating the number of citations his publications have received and the influence of his research output.

WORKSHOPS ATTENDED:

The user has actively participated in a wide array of workshops and training sessions covering diverse topics. These include sessions on Virtualization and Cloud Computing, Implementation of ICT in Engineering Education, Design of Experiments-Research Orientation, Industrial IoT training using LoRaWAN Technology, Deep drive into Machine Learning Algorithms for Natural Language Processing, Machine Learning for IOT Data Analysis using Raspberry pi and Tensor flow, Deep Learning Concepts with Convolutional Neural Network, Deep Drive in Cloud computing and hands-on Kubernetes, Effective Tools and Methodologies for NLP and Computational Linguistics, Emerging Trends and Research Directions in Cryptography and Information Security, Laughter yoga-The Hilarious Stress Buster, IoT in Cybersecurity, Accreditation: Its Benefits –Multidisciplinary approach, Mathematica for Education & Research, Developing Blockchain-based Smart Contracts on Ethereum using Solidity Language, Web 3.0 and Semantic Web, Statistical tools for effective research, Addressing challenges in medical image processing using Deep learning techniques, an Online user awareness session to demonstrate Springer Nature platforms, Fitness is your wealth, FOP-HR Policies, Avoiding Common Errors in English, Assessment of Python programming using MoodleCoderunner/VPL, Recent trends in Machine/Deep Learning for Computer Vision and Biomedical Applications, AI Tools for Scientific writing, Machine Learning and Deep Learning techniques in applied research, and A practical approach to real-world problems using AI and Deep Learning.

RESOURCE PERSON:

The user has actively contributed as a resource person at several engineering colleges, where they conducted training sessions for faculty members on Outcome-Based Curriculum, Cooperative and Collaborative Learning, Designing Question Papers, and Outcome-Based Assessment. Their engagements included sessions at Annamacharya Institute of Technology and Sciences-Tirupati, Nalla Narasimha Reddy Education Society’s Group of Institutions-Hyderabad, and Sree Venkateswara College of Engineering-Nellore.

CERTIFICATIONS ON OUTCOME BASED EDUCATION:

The user has actively pursued professional development in the field of education and curriculum design. They completed the IUCEE International Engineering Educator Certification program in three phases through APSSDC from January 2018 to July 2018. Additionally, they attended a one-week workshop on Curriculum Design, Measurement, and Evaluation through NITTTR-Kolkata from November 22, 2016, to November 27, 2016. They also participated in a one-week workshop on Outcome-Based Education and accreditation through NITTTR-Kolkata from September 24, 2018, to September 28, 2018. Furthermore, they attended a one-week workshop on Evaluating Students’ Performance and Designing Question Papers through NITTTR-Kolkata from February 25, 2019, to March 1, 2019.

Publications:

A review on the role of machine learning in agriculture

  • Published in Energy in 2020 with 11 citations.

A detailed review on challenges and imperatives of various CNN algorithms in weed detection

  • Published in Energy in 2021 with 8 citations.

Role of IoT, image processing and machine learning techniques in weed detection: a review

  • Published in Energy in 2022 with 6 citations.

Effectiveness of convolutional layers in pre-trained models for classifying common weeds in groundnut and corn crops

  • Published in Energy in 2022 with 4 citations.

The Solutions of SQL Injection Vulnerability in Web Application Security

  • Published in Energy in 2019 with 2 citations.

Dr. Sita Rani | Machine Learning | Women Researcher Award

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Dr. Sita Rani : Leading Researcher in Machine Learning

Assistant Professor at Machine Learning, Guru Nanak Dev Engineering College, Ludhiana, Punjab, India

She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Dr. Sita Rani has a distinguished academic background, including a Ph.D. in Computer Science and Engineering (CSE) from Inder Kumar Gujral Punjab Technical University (IKG PTU), Kapurthala, India, where she focused on the performance characterization of parallel computation in bioinformatics applications. She also holds a Master’s degree in CSE from GNDEC, Ludhiana, where she achieved a remarkable 73.68%, securing the 2nd position in her class. Dr. Rani’s academic journey began with a Bachelor’s degree in CSE from the same institution, where she secured a 73.2%, again achieving the 2nd position in her class. She also holds a Diploma in CSE from GPW, Ludhiana, where she graduated with honors and a notable 75.2% with a first division. Her academic excellence extends to her high school education, where she graduated from Govt. Sen. Sec. School., Lambra (Hoshiarpur) with a remarkable 78.8%, earning a first division with distinction. Additionally, Dr. Rani has recently completed a Post Graduate Certification Program in Data Science and Machine Learning from IIT, Roorkee, with distinction, further enhancing her expertise in the field.

Professional Experience:

Dr. Sita Rani completed her Postdoctoral research at the Big Data and Machine Learning Lab at South Ural State University (National Research University) in Chelyabinsk, Russian Federation. Her research was conducted under the project titled “Federated Learning for IoMT Applications” during the period from May 2022 to August 2023. This project likely involved exploring the applications of Federated Learning, a machine learning technique, in the context of the Internet of Medical Things (IoMT), which focuses on the use of interconnected medical devices and systems for healthcare applications.

Sita Rani ‘s citation metrics and indices from Google Scholar are as follows:

  • Cited by: All: 1338, Since 2018: 1325
  • Citations: 1338 (All), 1325 (Since 2018)
  • h-index: 21 (All), 20 (Since 2018)
  • i10-index: 39 (All), 39 (Since 2018)

These metrics showcase the impact of Rani ‘s work within the academic community, demonstrating the number of citations his publications have received and the influence of his research output.

Conferences:

Dr. Sita Rani actively participated in several international conferences, contributing to the field of data science and smart systems. She served as the Sessions Chair for the special session on “Data Mining and Software Engineering” at the 1st International Conference on “Applied Data Science and Smart Systems (ADSSS)” held at Chitkara University, Punjab, INDIA on 4th -5th November, 2022. Additionally, she chaired the special session on “Data Science and Data Analytics” at the “International Conference on Innovations in Data Analytics (ICIDA-2022)” organized by the “International Knowledge Research Foundation” in collaboration with Eminent College of Management and Technology (ECMT), West Bengal, India on 29-30 November, 2022. Dr. Rani also contributed as a member of the Technical Program Committee during the “International Conference on Innovations in Data Analytics (ICIDA-2022).” Furthermore, she chaired the special session on “Networking and Security” at the International Conference on Data Analytics and Management (ICDAM-2022), jointly organized by The Karkonosze University of Applied Science, Poland, in association with the University of Craiova Romania, Warsaw University of Life Sciences Poland, and Tun Hussein Onn University Malaysia, on 25th – 26th June, 2022. These engagements reflect her active involvement in the academic community and her commitment to advancing research in her field.

Research Interest:

Parallel and high-performance computing, Internet of Things (IoT), machine learning, blockchain, and healthcare are among Dr. Sita Rani’s areas of expertise and interest. Her work likely involves leveraging these technologies to advance various aspects of healthcare, such as data analysis, system optimization, and security within the context of healthcare systems and IoT devices. Dr. Rani’s focus reflects a multidisciplinary approach, integrating cutting-edge technologies to address complex challenges in healthcare and related fields.

Memberships:

Dr. Sita Rani holds memberships in several prestigious professional organizations:

  1. IEEE Membership (Yearly up to December 2023) with Membership Number: 97635456.
  2. IAEngg Membership (Lifetime) with Membership Number: 273196.
  3. ISTE Membership (Lifetime) with LM-131713.
  4. Women’s Indian Chamber of Commerce and Industry (WICCI) – Chandigarh SME & MSME Council – Vice-President.

Awards:

Dr. Sita Rani is an esteemed member of several renowned professional organizations. She holds an IEEE Membership, which is valid yearly until December 2023, with the membership number 97635456. Additionally, she is a lifetime member of the IAEngg with the membership number 273196 and the ISTE with LM-131713. Dr. Rani also holds a significant position as the Vice-President of the Women’s Indian Chamber of Commerce and Industry (WICCI) – Chandigarh SME & MSME Council, showcasing her active involvement in professional and leadership roles within her field.

Publications:

IoT equipped intelligent distributed framework for smart healthcare systems

  • Published in Energy in 2023 with 117 citations.

Cloud and fog computing platforms for internet of things

  • Published in Energy in 2022 with 113 citations.

AI-Centric Smart City Ecosystems: Technologies, Design and Implementation

  • Published in Energy in 2022 with 75 citations.

Amalgamation of advanced technologies for sustainable development of smart city environment: A review

  • Published in Energy in 2021 with 67 citations.

Threats and corrective measures for IoT security with observance of cybercrime: A survey

  • Published in Energy in 2021 with 66 citations.

Exploring the application sphere of the internet of things in industry 4.0: a review, bibliometric and content analysis

  • Published in Energy in 2022 with 57 citations.

Handbook of Research on AI-Based Technologies and Applications in the Era of the Metaverse

  • Published in Energy in 2023 with 53 citations.

Fog computing in industry 4.0: Applications and challenges—A research roadmap

  • Published in Energy in 2022 with 50 citations.

 

 

Ms. Mohaddeseh Koosha | Artificial Intelligence | Best Researcher Award

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Ms. Mohaddeseh Koosha : Leading Researcher in Artificial Intelligence

PhD Student at Artificial Intelligence, Amirkabir University of Technology, Iran

She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Ms. Mohaddeseh Koosha is an expert in signal and image processing with a passion for extracting features from natural patterns. She enjoys applying evolutionary algorithms to solve regression and classification problems and has a keen interest in studying scientific papers for new ideas. Ms. Koosha holds a Master’s degree in Electronics from Sharif University of Technology and is currently completing her Ph.D. in Computer Engineering with a focus on Artificial Intelligence at Amirkabir University of Technology. While she initially worked in electrical engineering, specifically in microelectronics and VHDL, she transitioned her focus to Artificial Intelligence eight years ago. Ms. Koosha has published in high-impact journals such as Knowledge-Based Systems (Elsevier) and IET Image Processing, as well as in conference publications. She has served as a peer-reviewer for IET Image Processing and has collaborated with Professor Mohammad Mehdi Ebadzadeh on Genetic Programming within the field of Evolutionary Algorithms. Throughout her career, Ms. Koosha has successfully completed several engineering projects for various companies, showcasing her expertise and practical skills in the field.

Research, Innovations and Extension:

Ms. Mohaddeseh Koosha has completed 12 research projects and has ongoing research activities. She has a citation index of 12 in Scopus/Web of Science or PubMed/Indian Citation Index. Additionally, she has been involved in 8 consultancy and industry-sponsored projects. Ms. Koosha has published 2 books with ISBN (text, reference, chapters, and conference proceedings) and has a cumulative project cost of USD/INR 30,000. She has published patents and has 2 journals indexed in SCI and SCIE. She has also held editorial appointments in journals/conferences and has 2 publications in Scopus, Web of Science, and PubMed indexes. Furthermore, she has a notable H-index based on Scopus/Web of Science, has organized research conferences/workshops, and has been involved in collaborative activities and received numerous awards and recognition. Ms. Koosha is a member of professional bodies and has functional MoUs with other universities/industries/corporates.

Research & Development:

👩‍🔬 Ms. Mohaddeseh Koosha is currently focusing on using artificial intelligence in developing biometric research, particularly in extracting biometric features from face and eyes. She is also using probabilistic genetic programming to resolve regression problems, such as making predictions from data gathered from CT Scan devices and making pollution condition forecasts. Additionally, she is enthusiastic about gathering healthcare-relevant features and observing their influence on life expectancy.