Fiona Kim |Mathematics | Best Researcher Award

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Dr. Fiona Kim |Mathematics | Best Researcher Award

University of New South Wales | Australia                      

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Early Academic Pursuits 📚

Dr. Fiona Kim began her academic journey with a Bachelor of Commerce (Honours) at the University of Western Australia from 2013 to 2016, where she majored in Economics and Marketing, achieving First Class Honours and maintaining an impressive GPA. She then pursued a PhD in Applied Statistics at the University of New South Wales from June 2019 to December 2022. Her research focused on cutting-edge areas such as natural language processing, machine learning, big data, and Bayesian Statistics. Dr. Kim's academic excellence was recognized with awards like the Australian Government Research Training Program Scholarship and Best Statistics Talk at UNSW’s postgraduate conference in 2020 and 2022.

Professional Endeavors 💼

Dr. Kim's professional career is marked by her roles across various industries. She served as a Senior Data Analyst at FT Strategies in 2024, where she led projects in financial modeling, AI use-case identification, and audience segmentation. Prior to that, she was a Product Data Scientist at Canva (2023-2024), contributing to the growth of the Canva for Teams product through data analysis, model building, and A/B testing. Her earlier roles include being an Academic at UNSW (2019-2022), where she facilitated and designed courses in analytics, and an Analytics and AI Consultant at Deloitte Consulting (2017-2019), where she led data-driven projects across multiple industries.

Contributions and Research Focus 🔍

Dr. Kim's contributions are vast and varied, focusing on data analysis, machine learning, and data visualization. At Canva, she developed models to enhance subscription conversion and retention, and at Deloitte, she improved operational efficiency for clients through data insights. Her research in applied statistics, particularly in natural language processing and machine learning, has positioned her as a leader in the field, with her work contributing to both academic knowledge and practical applications in industry.

Accolades and Recognition 🏆

Dr. Kim has been recognized for her exceptional contributions throughout her career. She received the Best Statistics Talk award at UNSW’s postgraduate conference twice and was a runner-up once. Her academic excellence earned her the Australian Government Research Training Program Scholarship, and she was also an ambassador for Women in Science and Maths at UNSW.

Impact and Influence 🌟

Dr. Kim's work has had a significant impact on the organizations she has been a part of. At FT Strategies, her financial modeling and AI initiatives have shaped strategic decisions. Her contributions at Canva have driven product growth, and her academic leadership at UNSW has influenced the next generation of data scientists. Her work at Deloitte improved client operations, demonstrating her ability to drive tangible outcomes through data.

Legacy and Future Contributions 🌍

Dr. Fiona Kim's legacy lies in her ability to bridge the gap between academic research and industry application. Her contributions to data science, particularly in natural language processing and machine learning, continue to influence both fields. As she progresses in her career, Dr. Kim is poised to make further contributions that will shape the future of data science, analytics, and their applications across industries.

 

Publications

📄 Bias intervention messaging in student evaluations of teaching: the role of gendered perceptions of bias
Authors: Fiona Kim, Lisa A. Williams, Emma L. Johnston, Yanan Fan
Journal: Heliyon
Year: 2024

 

Dimitrios Karapiperis | Computer Science | Best Research Award

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Dr. Dimitrios Karapiperis | Computer Science | Best Research Award

International Hellenic University | Greece

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🎓 Early Academic Pursuits

Dr. Dimitrios Karapiperis embarked on his academic journey with a BSc degree in Information Technology from the Technological Educational Institute of Thessaloniki, Greece, where he developed a strong foundation in applied technology. His passion for computer science led him to pursue an MSc degree in Software Engineering at the University of York, UK, funded by the State Scholarships Foundation of Greece (ΙΚΥ). During this time, he honed his skills in software engineering and expanded his knowledge in computer science.

Furthering his academic aspirations, Dr. Karapiperis earned a PhD in Computer Science from the Hellenic Open University, Greece. His research during this period focused on the field of Entity Resolution (Record Linkage), where he developed similarity algorithms, data structures, approximation schemes, and scalable distributed solutions. This phase of his education laid the groundwork for his future contributions to the field of computer science.

💼 Professional Endeavors

Dr. Karapiperis' professional career is marked by his dedication to both teaching and research. He has held various academic positions, including his current role as a lecturer at the Hellenic Open University, where he teaches courses on Data Mining and Machine Learning techniques. He also serves as an adjunct lecturer at the International Hellenic University, Greece, where he imparts knowledge on subjects such as Knowledge Management in the Web, Big Data and Cloud Computing, and Exploratory Data Analysis and Visualization. His previous roles include an adjunct lecturer position at the University of Western Macedonia, Greece, where he taught courses in Data Technologies and Database Management. Additionally, Dr. Karapiperis has experience as a research intern at the University of York, UK, and as a research assistant at the University of Macedonia, Greece, where he developed web and database applications.

🔬 Contributions and Research Focus

Dr. Karapiperis has made significant contributions to the field of computer science, particularly in the area of privacy-preserving record linkage. His research work includes the design of similarity algorithms, data structures, and approximation schemes that enable large-scale systems to perform record linkage while preserving privacy. His innovative use of randomization schemes, such as Locality-Sensitive Hashing (LSH) and count-min sketches, has advanced the field and provided practical solutions for handling voluminous data. In addition to his research, Dr. Karapiperis has supervised over 30 post-graduate theses at the International Hellenic University and Hellenic Open University, guiding students in topics related to Big Data management and the design of efficient algorithms.

🏆 Accolades and Recognition

Throughout his career, Dr. Karapiperis has earned recognition for his contributions to academia and research. His dedication to teaching, research, and the development of innovative algorithms has positioned him as a respected figure in the field of computer science. His expertise and commitment to advancing knowledge have garnered him the respect of his peers and students alike.

🌍 Impact and Influence

Dr. Karapiperis' work has had a profound impact on the field of computer science, particularly in the areas of data management and privacy-preserving technologies. His research on scalable and distributed solutions for Entity Resolution has influenced the development of more secure and efficient systems for handling large datasets. Moreover, his role as an educator has enabled him to shape the minds of future computer scientists, ensuring that his influence extends beyond his own research.

🚀 Legacy and Future Contributions

As Dr. Karapiperis continues his academic and research endeavors, his legacy is one of innovation, dedication, and impact. His ongoing work in developing cutting-edge algorithms and scalable solutions positions him as a leader in the field. With a strong foundation in both education and research, Dr. Karapiperis is poised to make even greater contributions to computer science in the years to come.

 

Publications

  • 📝Predicting Football Match Results Using a Poisson Regression Model
    Authors: Konstantinos Loukas, Dimitrios Karapiperis, Georgios Feretzakis, Vassilios S. Verykios
    Journal: Applied Sciences
    Year: 2024
  • 📝A Suite of Efficient Randomized Algorithms for Streaming Record Linkage
    Authors: Dimitrios Karapiperis, Christos Tjortjis, Vassilios S. Verykios
    Journal: IEEE Transactions on Knowledge and Data Engineering
    Year: 2024
  • 📝Machine Learning in Medical Triage: A Predictive Model for Emergency Department Disposition
    Authors: Georgios Feretzakis, Aikaterini Sakagianni, Athanasios Anastasiou, Ioanna Kapogianni, Rozita Tsoni, Christina Koufopoulou, Dimitrios Karapiperis, Vasileios Kaldis, Dimitris Kalles, Vassilios S. Verykios
    Journal: Applied Sciences
    Year: 2024
  • 📝Tracing Student Activity Patterns in E-Learning Environments: Insights into Academic Performance
    Authors: Evgenia Paxinou, Georgios Feretzakis, Rozita Tsoni, Dimitrios Karapiperis, Dimitrios Kalles, Vassilios S. Verykios
    Journal: Future Internet
    Year: 2024

 

Anastasios Liapakis | Computer Science | Best Researcher Award

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Assist Prof Dr. Anastasios Liapakis | Computer Science | Best Researcher Award

University of West Attica | Greece

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Early Academic Pursuits 📚

Dr. Anastasios Liapakis embarked on his academic journey with a strong foundation in Agricultural Engineering at the Agricultural University of Athens, where he completed his B(Eng) with a commendable grade of 7.27/10. Driven by a passion for data and analytics, he pursued a Master of Business Administration (MBA) specializing in Data Analytics at the same institution. His dedication and academic excellence earned him a top grade of 8.59/10. Dr. Liapakis continued his pursuit of knowledge by obtaining a PhD in Informatics, focusing on Big Data Analytics in Agricultural Digital Markets. His research in this area, completed with an "Excellent" grade, laid the groundwork for his future contributions to the field.

Professional Endeavors 🚀

Dr. Liapakis has held several key academic positions that have shaped his career. He is currently an Adjunct Assistant Professor at the University of West Attica, where he teaches modules on E-governance and Databases. His experience spans various institutions, including the University of Peloponnese, where he taught Programming II, and the National & Kapodistrian University of Athens, where he delivered courses on Object-Oriented Programming, Software Systems Design, and e-Government Systems. As the Academic Head of the Informatics Department at New York College, Athens, he managed programs in Computing, Software Engineering, and Data Analytics, showcasing his leadership and expertise in the field.

Contributions and Research Focus 🔬

Dr. Liapakis' research interests lie at the intersection of Artificial Intelligence (AI), Big Data Analytics, and Cultural Heritage Information Management. He has made significant contributions to the understanding and application of AI in various domains, particularly in opinion mining and big data analytics. His work has been instrumental in developing innovative solutions for the agricultural sector, including automated monitoring and control systems against pests in the Mediterranean region. His research projects, funded by the EU, have had a profound impact on the industry, highlighting his ability to bridge the gap between academia and real-world applications.

Accolades and Recognition 🏆

Throughout his career, Dr. Liapakis has been recognized for his outstanding academic performance and research contributions. He received multiple scholarships and financial awards, including one from the Agricultural University of Athens for his exceptional performance in the MBA program and another from the Greek State Scholarships Foundation during his undergraduate studies. His research has also garnered accolades, including a Best Paper Award at the International Journal of Computational Linguistics in 2020, solidifying his reputation as a leading researcher in his field.

Impact and Influence 🌍

Dr. Liapakis' work has had a significant impact on the academic community and beyond. His research in big data analytics and AI has influenced how these technologies are applied in various sectors, particularly in agriculture and food industries. His contributions to sentiment analysis, particularly in the context of the Greek language, have provided valuable insights for both academia and industry. Additionally, his involvement in PhD supervision and as a reviewer for various research journals demonstrates his commitment to shaping the future of research in his field.

Legacy and Future Contributions 🌟

As Dr. Liapakis continues to advance his research in AI and big data, his legacy is one of innovation and dedication to the application of cutting-edge technologies in solving real-world problems. His ongoing work in cultural heritage information management and his leadership in academic programs ensure that his contributions will continue to influence future generations of researchers and practitioners. Dr. Liapakis' vision for integrating AI into various sectors, coupled with his extensive experience and accolades, positions him as a thought leader poised to make lasting contributions to both academia and industry.

 

Publications

  • 📝A Sentiment Analysis Approach for Exploring Customer Reviews of Online Food Delivery Services: A Greek Case
    Authors: Fragkos, N.; Liapakis, A.; Ntaliani, M.; Ntalianis, F.; Costopoulou, C.
    Journal: Preprints 2024, 2024041203
    Year: 2024
  • 📝Ethical Use of Artificial Intelligence and New Technologies in Education 5.0
    Authors: Liapakis, A., Smyrnaiou, Z., & Bougia, A.
    Journal: International Journal of Artificial Intelligence, Machine Learning and Data Science
    Year: 2023
  • 📝Big Data, Sentiment Analysis, and Examples during the COVID-19 Pandemic
    Authors: Diareme, K. C., Liapakis, A., & Efthymiou, I.
    Journal: HAPSc Policy Briefs Series
    Year: 2022
  • 📝An Aspect-Based Sentiment Analysis System to Analyze Customers’ Reviews from Food and Beverage Opinion and Review Webpages: The Greek Case
    Authors: Liapakis, A., Tsiligiridis, T., Yialouris, C., & Costopoulou, C., Diareme, K.C.
    Journal: Information (Accepted for publication)
    Year: 2021
  • 📝A Corpus-Driven, Aspect-Based Sentiment Analysis to Evaluate in Almost Real-Time, a Large Volume of Online Food & Beverage Reviews
    Authors: Liapakis, A., Tsiligiridis, T., Yialouris, C., & Maliappis, M.
    Journal: International Journal of Computational Linguistics (IJCL)
    Year: 2020

 

Mona Ebadi Jalal | Computer Science | Best Researcher Award

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Ms. Mona Ebadi Jalal | Computer Science | Best Researcher Award

University of Louisville | United States

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Orcid

Google Scholar

Early Academic Pursuits 🎓

Ms. Mona Ebadi Jalal's academic journey is marked by excellence and dedication. She is currently pursuing a PhD in Computer Science at the University of Louisville, where she maintains a perfect GPA of 4.00. Her research focuses on the cutting-edge fields of Machine Learning and Deep Learning, under the guidance of Professor Adel Elmaghraby. Prior to this, she earned a Master’s Degree in Information Technology Engineering from K. N. Toosi University of Technology (KNTU) in Tehran, Iran, where she graduated with an impressive GPA of 17.75/20. Her master’s thesis involved developing a novel deep learning model using recurrent neural networks to forecast incoming call volumes in call centers, a project that earned a perfect grade of 20/20. She also holds a Bachelor’s Degree in Computer Engineering - Software from Payame Noor University in Hamedan, Iran, where she developed a patient information management system for a hospital as part of her thesis.

Professional Endeavors 💼

Ms. Ebadi Jalal’s professional career is equally distinguished. She is currently a PhD Fellow and Research Assistant at the University of Louisville, where she conducts in-depth research in customer behavior analysis, medical image analysis, and diagnostics prediction, utilizing advanced Machine Learning and Deep Learning methods. Before pursuing her PhD, she worked as an IT Consultant specializing in SAP ABAP and Business Data Analysis at Naghshe Aval Keyfiat (NAK) and Faraz Andishan Hesab Companies in Tehran, Iran. During this period, she designed and implemented custom solutions within the SAP framework, conducted thorough analyses of business processes, and managed end-to-end project lifecycles. She has also served as a Software Developer, developing and maintaining web applications and managing relational databases.

Contributions and Research Focus 🔬

Ms. Ebadi Jalal’s contributions to the field of computer science are significant and diverse. Her research primarily focuses on the application of Machine Learning and Deep Learning to customer behavior analysis and medical diagnostics. She has developed predictive models for call center operations and contributed to the advancement of personalized marketing through counterfactual analysis. Her recent work includes a deep learning framework for abnormality detection in nailfold capillary images, which has the potential to revolutionize diagnostics in medical imaging.

Accolades and Recognition 🏅

Ms. Ebadi Jalal’s academic and professional achievements have been recognized with numerous awards and honors. She was awarded a prestigious fellowship for her PhD studies at the University of Louisville in 2022. During her time at K. N. Toosi University of Technology, she was nominated for the Superior Student Researcher honor in 2014. Additionally, she ranked in the top 1% in Iran’s nationwide graduate-level entrance exam in Information Technology Engineering in 2012 and received a national graduate-level full scholarship.

Impact and Influence 🌍

Ms. Ebadi Jalal’s work has had a profound impact on both academia and industry. Her research has led to new insights in customer behavior analysis and medical image diagnostics, influencing the development of more effective marketing strategies and diagnostic tools. As a peer reviewer for several prestigious journals, including IEEE Access and Scientific Reports, she contributes to the advancement of knowledge in her field by ensuring the quality and rigor of published research.

Legacy and Future Contributions 🌟

Ms. Ebadi Jalal is poised to leave a lasting legacy in the field of computer science. Her ongoing research in machine learning and deep learning holds the potential to drive significant advancements in both customer behavior analysis and medical diagnostics. With her strong academic background, extensive professional experience, and numerous accolades, she is well-positioned to continue making groundbreaking contributions to the field in the years to come. Her future work will likely influence the next generation of researchers and practitioners, further solidifying her impact on the world of technology.

Publications

📝 Artificial Intelligence Algorithms in Nailfold Capillaroscopy Image Analysis: A Systematic Review

Journal: MedRxiv
Year: 2024
Authors: Emam, Omar S.; Jalal, Mona Ebadi; Garcia-Zapirain, Begonya; Elmaghraby, Adel S.

📝 Analyzing the Dynamics of Customer Behavior: A New Perspective on Personalized Marketing through Counterfactual Analysis

Journal: Journal of Theoretical and Applied Electronic Commerce Research
Year: June 2024
Authors: Mona Ebadi Jalal; Adel Elmaghraby

📝 Forecasting Incoming Call Volumes in Call Centers with Recurrent Neural Networks

Journal: Journal of Business Research
Year: November 2016
Authors: Mona Ebadi Jalal; Monireh Hosseini; Stefan Karlsson

📝 Analysis of Customer Behavior in Purchasing and Sending Online Group SMS Using Data Mining Based on the RFM Model

Journal: Sharif Journal of Industrial Engineering & Management
Year: February 20, 2016
Authors: Mona Ebadi Jalal; Somayeh Alizadeh




Kalyanapu Srinivas | Computer Science | Best Researcher Award

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Dr. Kalyanapu Srinivas | Computer Science | Best Researcher Award

Vaagdevi Engineering College | India

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Early Academic Pursuits 🎓

Dr. Kalyanapu Srinivas embarked on his academic journey with a Bachelor of Technology (B.Tech) in Computer Science Engineering from Vidya Bharathi Institute of Technology, graduating in 2006 with First Division honors. He continued to advance his studies with a Master of Technology (M.Tech) in Software Engineering from Ramappa Engineering College in 2010, where he achieved Distinction with a 78.2% score. Further solidifying his academic prowess, Dr. Srinivas completed his Ph.D. in Cryptography & Network Security at JNTU, Hyderabad in 2020.

Professional Endeavors 💼

Dr. Srinivas has accumulated over 16 years of experience in academia. His professional journey includes roles such as Assistant Professor at various institutions, including Vaagdevi Engineering College, Kakatiya Institute of Technology and Science, and SR Engineering College. His tenure in these roles highlights his commitment to advancing the field of computer science and engineering. Notably, he has been involved in teaching, research, and academic administration.

Contributions and Research Focus 🔬

Dr. Srinivas’s research primarily focuses on Cryptography and Network Security, with a keen interest in Data Mining, Cloud Computing, and Quantum Computing. His Ph.D. thesis, titled "Novel Techniques for Image-Based Key Generation using Chinese Remainder Theorem and Chaotic Logistic Maps," reflects his innovative approach to enhancing security protocols. Additionally, his ongoing research guidance includes supervising several Ph.D. students in areas such as Wireless Networks and Cloud Computing.

Accolades and Recognition 🏆

Dr. Srinivas has earned significant recognition throughout his career. His work in machine learning and cryptography has led to the publication of a patent on Alzheimer's prediction using machine learning. He has also been honored as a session chair at the International Conference on Research in Science, Engineering, Technology, and Management (ICRSETM2020) and served as a guest speaker at SAFER INTERNET DAY 2023. His expertise has been acknowledged through editorial and review roles for various conferences and journals.

Impact and Influence 🌍

Dr. Srinivas’s contributions extend beyond his research. His involvement in organizing and participating in short-term training programs (STTP) on IoT simulation and fog computing showcases his dedication to fostering knowledge and innovation in emerging technologies. His role as a primary evaluator for TOYCATHON 2021 further emphasizes his influence in shaping the future of technology education and development.

Legacy and Future Contributions 🚀

Looking ahead, Dr. Srinivas is poised to continue making impactful contributions to the fields of cryptography and network security. His research initiatives and academic leadership are expected to drive advancements in secure computing and innovative technologies. As he mentors the next generation of researchers and contributes to cutting-edge research, his legacy in the academic and professional realms will undoubtedly endure, inspiring future advancements in technology and education.

 

Publications 📚

  • Article: Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
    Authors: Stateczny, A., Narahari, S.C., Vurubindi, P., Guptha, N.S., Srinivas, K.
    Journal: Remote Sensing
    Year: 2023
  • Article: User-segregation based channel estimation in the MIMO system
    Authors: Patra, R.K., Kumar, M.H., Srinivas, K., Sekhar, P.C., Subhashini, S.J.
    Journal: Physical Communication
    Year: 2023
  • Book Chapter: An Enhancement in Crypto Key Generation Using Image Features with CRT
    Authors: Srinivas, K., Kumar, N.S., Sanathkumar, T., Rama Devi, K.
    Book: Cognitive Science and Technology
    Year: 2023
  • Article: Plant disease classification using deep bilinear CNN
    Authors: Rao, D.S., Ramesh Babu, C., Kiran, V.S., Mohan, G.S., Bharadwaj, B.L.
    Journal: Intelligent Automation and Soft Computing
    Year: 2022
  • Article: Symmetric key generation algorithm using image-based chaos logistic maps
    Authors: Srinivas, K., Janaki, V.
    Journal: International Journal of Advanced Intelligence Paradigms 🧠
    Year: 2021

 

Sasank V.V.S | Computer Science | Best Researcher Award

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Assist Prof Dr. Sasank V.V.S | Computer Science | Best Researcher Award

K L University | India

Author Profile

Scopus

Early Academic Pursuits

Dr. Sasank V.V.S. exhibited a strong academic foundation from the outset. He completed his secondary education at Jassver English Medium School in 2007 with a First Class distinction, scoring 72.66%. He continued to excel in his Intermediate studies at Mega Junior College, graduating in 2009 with an 84.1% mark, also achieving First Class. His academic journey progressed to higher education at Gitam Institute of Technology, GITAM University, where he obtained his B.Tech in Information Technology in 2013 with a CGPA of 8.15, earning a Distinction. He further advanced his education with an M.Tech in Computer Science and Technology from the same institution, graduating in 2016 with a remarkable 9.11 CGPA, securing the top rank in his department. Dr. Sasank completed his Ph.D. at K.L. University in 2023, marking a significant milestone in his academic career.

Professional Endeavors

Dr. Sasank has a rich professional background in both academia and industry. He began his teaching career as a Teaching Assistant in the CSE Department at Gitam University from October 2015 to April 2016. He then served as an Assistant Professor at the Lendi Institute of Engineering & Technology, VIZIANAGARAM, from June 2016 to April 2017. Following this, he joined Anil Neerukonda Institute of Technology & Sciences (ANITS) as an Assistant Professor and Placement Officer from June 2017 to April 2019. He has been affiliated with K L University since July 2019, initially in the CSE Department and later in the CSIT Department, where he also served as the ERP Registration In-charge. His teaching repertoire includes subjects such as DBMS, Software Engineering, Computer Architecture & Organization, Term Paper, UI/UX Design, and DevOps.

Contributions and Research Focus

Dr. Sasank's research primarily focuses on advanced topics in computer science and engineering. His areas of interest include brain tumor classification, real-time traffic management using IoT and machine learning techniques, and the evolution of modern women in literature. He has published a significant number of papers in reputed journals, including  SCI papers and several Scopus-indexed articles. His notable publications include works on hybrid deep neural networks, automatic tumor growth prediction, and brain tumor classification using modified kernel-based softplus extreme learning machines. Additionally, he has guided numerous B.Tech and M.Tech project batches, contributing to the academic growth of his students.

Accolades and Recognition

Dr. Sasank has received several accolades for his academic and research achievements. He was the top ranker in his M.Tech program at Gitam University in 2016. He has published 18 papers, including SCI, Scopus, and WOS-indexed journals, and has contributed to two book chapters. His innovative research has led to the publication of two patents: one on real-time traffic management using IoT and machine learning techniques, and another on the evolution of modern women in Manju Kapur’s novels. Additionally, he has earned global certifications, including Google Associate Cloud Engineer and AWS Cloud Practitioner, and has presented his research at various international conferences.

Impact and Influence

Dr. Sasank's contributions to the field of computer science and engineering have had a significant impact on both academic and practical applications. His research on brain tumor classification and real-time traffic management has potential real-world implications, advancing the fields of medical imaging and smart city technologies. As an educator, he has influenced many students through his teaching and mentorship, guiding them in their academic and research endeavors.

Legacy and Future Contributions

Dr. Sasank's ongoing research and academic activities are expected to leave a lasting legacy in the field of computer science and engineering. His contributions to brain tumor classification and IoT-based traffic management are poised to influence future research and development in these areas. As he continues to publish and present his work, Dr. Sasank is likely to inspire and mentor the next generation of engineers and researchers, ensuring continued innovation and excellence in his field.

 

Notable Publications

Prostate cancer classification using adaptive swarm Intelligence based deep attention neural network 2024

Effective Segmentation and Brain Tumor Classification Using Sparse Bayesian ELM in MRI Images 2023

Hybrid deep neural network with adaptive rain optimizer algorithm for multi-grade brain tumor classification of MRI images 2022 (14)

An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour 2022 (27)

Hate Speech & Offensive Language Detection Using ML &NLP 2022 (4)

 

 

 

 

Yang Liu | Computer Science | Best Researcher Award

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Prof. Yang Liu | Computer Science | Best Researcher Award

Henan University of Technology | China

Author Profile

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Early Academic Pursuits

Prof. Yang Liu was born in November 1978. She pursued her academic journey in the field of Computer Science, culminating in a Ph.D. from the School of Computer Science at Northwestern Polytechnical University (NWTU) between September 2003 and November 2007. Her early academic career set a strong foundation for her expertise in distributed computing and blockchain technology.

Professional Endeavors

After earning her Ph.D., Prof. Liu began her professional career as an Assistant Researcher at the Shenzhen Institutes of Advanced Technology, part of the China Academy of Sciences, from November 2007 to February 2009. Since March 2009, she has been a Professor at the College of Information Science and Engineering, Henan University of Technology (HAUT). Her professional journey has been marked by significant contributions to academia and research, particularly in the realms of distributed computing and blockchain.

Contributions and Research Focus

Prof. Liu's research interests are deeply rooted in distributed computing and blockchain technology, focusing on developing secure and efficient consensus mechanisms in blockchain systems, implementing blockchain-based solutions for food traceability and circulation, and researching adaptive resource scheduling and allocation mechanisms in cloud environments. Her contributions extend to developing distributed computing technologies tailored for big data domains. Prof. Liu's work has been instrumental in advancing the practical application and theoretical understanding of these technologies, significantly impacting various real-world scenarios.

Accolades and Recognition

Prof. Liu has garnered numerous awards and honors, underscoring her substantial contributions to science and technology. These include being appointed Chief Science Expert of Henan Province in 2023, receiving the New Century Excellent Talents award from the Ministry of Education of China in 2012, and leading an Innovative Research Team in Science and Technology at the University of Henan Province in 2017. Her achievements also encompass the Prize of Scientific and Technological Achievements of Henan Province in 2013, along with the Henan Province Award for Outstanding Publications in Natural Science in 2011. These accolades affirm Prof. Liu's impactful role in advancing research and innovation, particularly within Henan Province and across China.

Impact and Influence

Prof. Liu's influence extends beyond her research into pivotal roles within various organizations. She serves as a Technical Committee Member for Systems Software and Blockchain at the China Computer Federation (CCF), highlighting her expertise in these critical fields. Additionally, as Deputy Director of the Academic Committee at the Henan Blockchain Technology Research Association and a member of the Experts Committee at the Zhengzhou Information Promote Association, she plays a significant role in shaping the future of computing and blockchain technology. Her leadership and contributions in these positions underscore her commitment to advancing these domains, both locally and on a broader scale.

Legacy and Future Contributions

Prof. Liu has authored numerous publications that have contributed to the body of knowledge in her field. Some notable works include research on consensus algorithms, cloud computing resource management, and energy-efficient communication in wireless sensor networks. Her ongoing research and future contributions are expected to further advance the fields of distributed computing and blockchain, influencing both academic research and practical applications.

 

Notable Publications

TortoiseBFT: An asynchronous consensus algorithm for IoT system 2024

Towards secure and efficient integration of blockchain and 6G networks 2024

A Pipeline-based Chain Structure Byzantine Consensus Algorithm for Blockchain Systems 2023

SoK: Research status and challenges of blockchain smart contracts 2023

MoryFabric: Reducing Transaction Abort by Actual Validity Verification and Reordering 2023

 

 

 

Merve Asiler | Computer Science | Best Researcher Award

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Ms. Merve Asiler | Computer Science | Best Researcher Award

Middle East Technical University | Turkey

Author Profile

Orcid

Googler Scholar

Early Academic Pursuits

Ms. Merve Asiler's academic journey began with an impressive performance at Yıldırım Beyazıt Science High School in Ankara, Turkey, where she graduated at the top of her class. She continued her education at the Middle East Technical University (METU) in Ankara, Turkey, earning dual bachelor's degrees in Computer Engineering and Mathematics. During her undergraduate studies, she developed a strong interest in algorithms, computer organization, operating systems, and computer graphics. She pursued her Master’s degree in Computer Engineering at METU, specializing in Big Data and Graph Databases, and is currently working towards her Ph.D. in Computer Engineering with a focus on Computer Graphics, Computational Geometry, and Digital Geometry Processing.

Professional Endeavors

Merve Asiler has accumulated extensive professional experience in both academia and industry. She has worked as a Research and Teaching Assistant at METU, where she has contributed to various courses, including Introduction to Computer Engineering Concepts, C Programming, Algorithms, and Computer Engineering Design. Her industry experience includes roles as a Software Developer at Accelerate Simulation Technologies, Turkish Aerospace, and Kale Yazilim. These roles involved developing software for unmeshed CAD geometries, engaging in modeling and simulation activities, and handling complex queries in large graph databases using Neo4j.

Contributions and Research Focus

Ms. Asiler's research primarily revolves around computer graphics, computational geometry, and digital geometry processing. Her Ph.D. research focuses on geometric kernel computation in 3D space, developing algorithms that outperform current methods for kernel computation. Her Master's research involved developing BB-Graph, a new subgraph isomorphism algorithm for querying big graph databases. This work was done in collaboration with Kale Yazilim and demonstrated significant performance improvements over existing algorithms.

Accolades and Recognition

Ms. Asiler has been recognized for her academic excellence with a GPA of 3.93/4.00 in her Ph.D. studies and 3.71/4.00 in her Master's program. She has published significant research papers, including a study on 3D geometric kernel computation in polygon mesh structures and a subgraph isomorphism algorithm for querying big graph databases. Her work has been published in reputable journals like Computers & Graphics and the Journal of Big Data.

Impact and Influence

Ms. Asiler's contributions to computer science, particularly in the areas of computer graphics and big data, have had a significant impact on both academia and industry. Her research on geometric kernels and graph databases has advanced the understanding and application of these complex areas. As a teaching assistant, she has influenced and mentored numerous students, preparing original programming assignments and supervising student projects.

Legacy and Future Contributions

Looking ahead, Ms. Asiler plans to leverage her expertise in mesh kernels to explore novel solutions for non-self-intersecting shape interpolation and star-shape decomposition problems. Her future contributions are likely to continue pushing the boundaries of computational geometry and computer graphics, benefiting both academic research and practical applications in various industries. With her strong foundation and ongoing commitment to research, Ms. Asiler is poised to make lasting contributions to the field of computer science.

 

Notable Publications

3D geometric kernel computation in polygon mesh structures 2024

HyGraph: a subgraph isomorphism algorithm for efficiently querying big graph databases 2022 (3)

 

 

 

Yongshin Park | Decision Sciences | Excellence in Research Award

Posted on by Book of Award

Dr. Yongshin Park | Decision Sciences | Excellence in Research Award

St. Edward's University | United States

Author Profile

Scopus

Orcid

Early Academic Pursuits

Dr. Yongshin Park embarked on his academic journey at North Dakota State University, where he obtained a Bachelor of Science in Industrial and Manufacturing Engineering in 2012. He continued his studies at the same institution, earning a Master’s degree in Managerial Logistics in 2013. Driven by a passion for data and analysis, Dr. Park further pursued a Graduate Degree Certificate in Statistics, which he completed alongside his Ph.D. in Transportation and Logistics in 2018. His dissertation, titled "Three Essays on Sustainability of Transportation and Supply Chain," laid the foundation for his future contributions to academia and industry.

Professional Endeavors

Dr. Park’s professional career began as a Research Assistant at North Dakota State University's Upper Great Plains Transportation Institute, where he worked from 2012 to 2018. He then transitioned to academia as a Lecturer at North Dakota State University, teaching various courses in Transportation, Operations, and Supply Chain Management. In 2018, Dr. Park joined St. Edward’s University in Austin, TX, where he initially served as an Assistant Professor of Operations Management. His exemplary performance led to his promotion to Associate Professor of Operations Management and Business Analytics in 2023, and he currently holds the position of Program Director for the MS in Business Analytics.

Contributions and Research Focus

Dr. Park’s research is deeply rooted in transportation and supply chain sustainability, financial management, and data analytics. His expertise spans a wide range of analytical tools and software, including R, SPSS, Python, and Tableau, among others. Dr. Park has authored multiple scholarly publications, with notable works focusing on topics such as port productivity, herd behavior in decision-making, and the sustainability performance of the construction sector. His interdisciplinary approach has also led to significant contributions in fields like hydrology education and media framing of social issues.

Accolades and Recognition

Throughout his career, Dr. Park has received numerous accolades for his research and teaching excellence. He was awarded the Munday School of Business Dean’s Excellent Research Grant twice, in 2022 and 2023. His innovative research on port infrastructure earned him a substantial grant from Gyeongsang National University, South Korea, in 2023. Additionally, Dr. Park’s academic achievements have been recognized with awards such as the Encouragement Paper Award from the Asian Association of Management Science and Application and the Excellent Student Paper Award from the Korean Transportation Association in America.

Impact and Influence

Dr. Park’s impact extends beyond his publications and grants. He has played a pivotal role in developing and modernizing academic programs at St. Edward’s University, including the MS in Business Analytics and the MBA Supply Chain Management Concentration. His dedication to teaching and mentorship has fostered the academic growth of numerous undergraduate and graduate students. Dr. Park's collaborative efforts with faculty and industry professionals have enriched the curriculum and enhanced the university's reputation in the field of business analytics.

Legacy and Future Contributions

Dr. Park’s legacy is characterized by his commitment to sustainability in transportation and supply chain management, as well as his innovative approach to data analytics and education. Looking ahead, he aims to continue his research on sustainability and efficiency in logistics and supply chains, with a focus on developing new models and tools to address emerging challenges in these fields. Dr. Park’s ongoing work promises to make significant contributions to both academia and industry, ensuring his lasting influence on future generations of scholars and practitioners.

Notable Publications

A responsive closed-loop supply chain network design under demand uncertainty 2024

Predicting Nurse Turnover for Highly Imbalanced Data Using the Synthetic Minority Over-Sampling Technique and Machine Learning Algorithms 2023 (1)

The efficient and stable planning for interrupted supply chain with dual‐sourcing strategy: a robust optimization approach considering decision maker's risk attitude 2023 (13)

Multi-criteria supplier selection problem with fuzzy demand: a newsvendor model 2022 (1)

A Comparative Time-Series Investigation of China and U.S. Manufacturing Industries’ Global Supply-Chain-Linked Economic, Mid and End-Point Environmental Impacts 2021 (5)

 

 

 

 

Ruichao Yang | Computer Science | Best Researcher Award

Posted on by Book of Award

Ms. Ruichao Yang | Computer Science | Best Researcher Award

Hong Kong Baptist University | Hong Kong

Author Profile

Scopus

Early Academic Pursuits

Ruichao Yang commenced their academic journey at Jilin University, where they systematically delved into computer science courses and participated in various competitions. Notably, they secured the third prize in the 5th "Certification Cup" National College Students Mathematical Modeling Network Challenge. Their undergraduate experience laid a robust foundation in data structure, algorithm design, and analytical skills, setting the stage for their future endeavors.

Professional Endeavors

Ruichao Yang's professional journey commenced with internships and later full-time roles at Microsoft China, where they showcased their prowess in software engineering and natural language processing. They contributed significantly to projects aimed at enhancing online keyword matching systems, filtering advertisements, and improving revenue through innovative approaches. Their expertise in programming languages, data structures, and algorithms proved instrumental in restructuring and optimizing advertising business systems.

Contributions and Research Focus

Ruichao Yang's academic background, coupled with their industry experience, fueled their research focus on improving the efficiency of computing systems, particularly cache optimization and deep learning network acceleration. Their contributions to building domain knowledge graphs and anomaly detection models underscore their commitment to advancing technology's practical applications, particularly in the realm of advertising and revenue optimization.

Accolades and Recognition

Throughout their academic and professional journey, Ruichao Yang garnered numerous accolades and awards, including academic scholarships, merit distinctions, and recognition for their leadership and volunteerism. Their consistent pursuit of excellence and dedication to their field have been acknowledged both within academia and the industry.

Impact and Influence

Ruichao Yang's work at Microsoft China and academic research endeavors have left a significant impact on the domains of software engineering and computer science. Their innovative approaches to problem-solving and contributions to optimizing advertising systems have not only enhanced user experiences but also contributed to revenue growth and operational efficiency.

Legacy and Future Contributions

As Ruichao Yang continues to navigate their career path, their legacy lies in their contributions to advancing technology's frontiers, particularly in software engineering, natural language processing, and computational optimization. Their future contributions are poised to further propel innovation, shape industry standards, and inspire the next generation of computer scientists and engineers.

Notable Publications

  • CoTea: Collaborative teaching for low-resource named entity recognition with a divide-and-conquer strategy 2024
  • Towards low-resource rumor detection: Unified contrastive transfer with propagation structure 2024

  • Reinforcement Subgraph Reasoning for Fake News Detection 2022 (29)

    A Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learning 2022 (20)

    Towards Fine-Grained Reasoning for Fake News Detection 2022 (35)