Khrystyna Lipianina-Honcharenko | Computer Science | Young Scientist Award

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Dr. Khrystyna Lipianina-Honcharenko | Computer Science | Young Scientist Award

Associate professor, Ph.D. in information technologies at West Ukrainian National University, Ukraine

Khrystyna Lipianina-Honcharenko is a promising candidate for the Young Scientist Award due to her strong academic background and substantial contributions to research in information technology, machine learning, and socio-economic modeling. Holding a PhD in Technical Sciences and serving as an Associate Professor at the West Ukrainian National University, she has extensive experience in both teaching and research. Khrystyna is involved in high-impact international projects, such as TruScanAI and Erasmus+ initiatives, demonstrating her leadership and collaboration in cutting-edge technological advancements. Her research on data analysis, simulation, and machine learning positions her at the forefront of modern scientific inquiry. While her proficiency in English and publication presence are notable, further enhancement of her language skills and expanding her network in global research circles could increase her influence. Overall, Khrystyna’s innovative research and leadership make her a strong contender for the award, with significant potential for future contributions to the scientific community.

Professional Profile 

Education🎓

Khrystyna Lipianina-Honcharenko has an extensive educational background, primarily from West Ukrainian National University, where she has completed multiple degrees. She holds a Bachelor’s degree in Economic Cybernetics (2007–2011), followed by a Master’s in Information Technologies in Economics (2011–2012). Khrystyna continued her academic journey as a postgraduate student at the Department of Economic Cybernetics and Informatics, earning a PhD in Technical Sciences in Information Technology (2019). Her academic pursuits are ongoing, as she is currently working towards her Doctor of Technical Sciences degree in the Department of Information Computer Systems and Control at the same university, which she is expected to complete in 2025. Her education reflects a strong foundation in both the technical and economic aspects of information systems, further enhanced by her focus on machine learning and data analysis. This solid academic background has significantly contributed to her research and teaching expertise.

Professional Experience📝

Khrystyna Lipianina-Honcharenko has a rich professional experience in academia, primarily at West Ukrainian National University (WNU). She began her career as a Laboratory Assistant in the Department of Economic Cybernetics and Informatics from 2012 to 2014, where she gained foundational experience in research and teaching. Khrystyna then advanced to the role of Lecturer in the same department from 2013 to 2020, and later became a Senior Lecturer in the Department of Information Computer Systems and Control from 2020 to 2021. Her expertise was further recognized when she was promoted to Associate Professor in 2021, a position she holds currently. Throughout her career, Khrystyna has not only contributed to teaching but has also been actively involved in research, particularly in areas such as machine learning, data analysis, and socio-economic modeling. Her experience spans both academic instruction and hands-on involvement in high-impact international research projects, highlighting her leadership and expertise.

Research Interest🔎

Khrystyna Lipianina-Honcharenko’s research interests lie at the intersection of information technology, machine learning, and socio-economic modeling. She is particularly focused on data analysis, simulation, and the application of artificial intelligence methods in cyber-physical systems. Her work explores the use of machine learning techniques to model and forecast socio-economic processes, aiming to improve decision-making in various fields, including economics and technology. Khrystyna has also contributed to innovative projects like TruScanAI, which uses AI to detect fake information, and Auralisation of Acoustic Heritage Sites, which combines augmented and virtual reality to preserve cultural heritage. Her research interests extend to structural and statistical identification of hierarchical objects, as well as the development of tools for analyzing complex systems. Through these endeavors, Khrystyna seeks to advance the integration of technology and data-driven methods in solving real-world challenges, particularly in the context of socio-economic systems and information technologies.

Award and Honor🏆

Khrystyna Lipianina-Honcharenko has been recognized for her significant contributions to research and education, particularly in the fields of information technology and machine learning. While specific awards and honors are not detailed in the available information, her involvement in prestigious international projects such as Erasmus+ and her participation in high-impact research initiatives like TruScanAI and Auralisation of Acoustic Heritage Sites underscore her academic and professional recognition. These projects highlight her leadership and innovation, earning her respect within the academic community. Additionally, her active role in the Erasmus+ KA2 Work4CE program demonstrates her commitment to advancing higher education and interdisciplinary collaboration. Khrystyna’s extensive publication record and contributions to scientific advancements further demonstrate her growing influence in her field. As she continues to contribute to international collaborations and projects, it is likely that her efforts will lead to more formal recognitions and awards, further solidifying her place as a leader in her research domain.

Research Skill🔬

Khrystyna Lipianina-Honcharenko possesses a diverse and robust set of research skills, particularly in the areas of data analysis, machine learning, and modeling of socio-economic processes. She is proficient in programming languages such as R and Python, which are essential for data processing, algorithm development, and machine learning applications. Her expertise extends to using various application packages like MS Excel, Mathcad, AnyLogic, and GeoDa, allowing her to model complex systems and analyze large datasets effectively. Khrystyna is well-versed in both qualitative and quantitative research methodologies, including structural and statistical identification of hierarchical objects, a skill she applied in projects related to cyber-physical systems. Her ability to combine technical knowledge with socio-economic modeling enables her to tackle interdisciplinary research challenges. Moreover, her involvement in international projects showcases her capacity for collaborative, cross-cultural research, further enhancing her adaptability and competence in applying advanced research techniques in diverse contexts.

Conclusion💡

Khrystyna Lipianina-Honcharenko is a strong candidate for the Young Scientist Award, thanks to her academic accomplishments, innovative research projects, and leadership in international collaborations. Her dedication to the field of information technology, machine learning, and socio-economic modeling positions her as an emerging scientist with significant potential for future contributions. With continued professional development in areas such as language proficiency and broader networking, Khrystyna could enhance her impact and further distinguish herself in her field.

Publications Top Noted✍️

  • Title: Decision tree based targeting model of customer interaction with business page
    Authors: H Lipyanina, A Sachenko, T Lendyuk, S Nadvynychny, S Grodskyi
    Year: 2020
    Citations: 37

  • Title: Economic Crime Detection Using Support Vector Machine Classification
    Authors: A Krysovatyy, H Lipyanina-Goncharenko, S Sachenko, O Desyatnyuk
    Year: 2021
    Citations: 25

  • Title: Assessing the investment risk of virtual IT company based on machine learning
    Authors: H Lipyanina, V Maksymovych, A Sachenko, T Lendyuk, A Fomenko, I Kit
    Year: 2020
    Citations: 24

  • Title: Targeting Model of HEI Video Marketing based on Classification Tree
    Authors: H Lipyanina, S Sachenko, T Lendyuk, A Sachenko
    Year: 2020
    Citations: 22

  • Title: Concept of the intelligent guide with AR support
    Authors: K Lipianina-Honcharenko, R Savchyshyn, A Sachenko, A Chaban, I Kit
    Year: 2022
    Citations: 19

  • Title: Intelligent Method of a Competitive Product Choosing based on the Emotional Feedbacks Coloring
    Authors: R Gramyak, H Lipyanina-Goncharenko, A Sachenko, T Lendyuk
    Year: 2021
    Citations: 19

  • Title: Method of detecting a fictitious company on the machine learning base
    Authors: H Lipyanina, S Sachenko, T Lendyuk, V Brych, V Yatskiv, O Osolinskiy
    Year: 2021
    Citations: 17

  • Title: Multiple regression method for analyzing the tourist demand considering the influence factors
    Authors: V Krylov, A Sachenko, P Strubytskyi, D Lendiuk, H Lipyanina
    Year: 2019
    Citations: 13

  • Title: Recognizing the Fictitious Business Entity on Logistic Regression Base
    Authors: A Krysovatyy, K Lipianina-Honcharenko, S Sachenko, O Desyatnyuk
    Year: 2022
    Citations: 9

  • Title: Сучасні інформаційні технології
    Authors: ОВ Вовкодав, ХВ Ліп’яніна
    Year: 2017
    Citations: 9

  • Title: Classification Method of Fictitious Enterprises Based on Gaussian Naive Bayes
    Authors: A Krysovatyy, H Lipyanina-Goncharenko, O Desyatnyuk, S Sachenko
    Year: 2021
    Citations: 8

  • Title: Intelligent information system for product promotion in internet market
    Authors: K Lipianina-Honcharenko, C Wolff, A Sachenko, O Desyatnyuk
    Year: 2023
    Citations: 7

  • Title: An intelligent method for forming the advertising content of higher education institutions based on semantic analysis
    Authors: K Lipianina-Honcharenko, T Lendiuk, A Sachenko, O Osolinskyi
    Year: 2021
    Citations: 7

  • Title: Intelligent waste-volume management method in the smart city concept
    Authors: K Lipianina-Honcharenko, M Komar, O Osolinskyi, V Shymanskyi
    Year: 2023
    Citations: 6

  • Title: Intelligent method for classifying the level of anthropogenic disasters
    Authors: K Lipianina-Honcharenko, C Wolff, A Sachenko, I Kit, D Zahorodnia
    Year: 2023
    Citations: 6

Hao Wu | Protein engineering | Best Researcher Award

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Assoc. Prof. Dr. Hao Wu | Protein engineering | Best Researcher Award

Teacher  at Changsha University of Science and Technology, China

Dr. Hao Wu is a highly qualified researcher with a Ph.D. in Microbiology and extensive postdoctoral experience. Currently serving as an Associate Professor at Changsha University of Science & Technology, his research focuses on food biotechnology, protein engineering, and synthetic biology, particularly in the development of anti-diabetic compounds, enzyme engineering, and the production of human milk oligosaccharides. With over 20 publications in high-impact journals and leadership in numerous first-author and corresponding author roles, Dr. Wu has made significant contributions to applied food science and biotechnology. His work on enzyme stability and microbial fermentation has direct industrial and health-related implications. Additionally, he is actively involved in peer review and editorial positions for several prestigious journals. While his profile would benefit from further recognition through awards and major project leadership, his impressive publication record and research contributions make him a strong contender for the Best Researcher Award.

Professional Profile 

Education🎓

Dr. Hao Wu holds a Ph.D. in Microbiology, which he earned in 2019 from Guangxi University in Nanning, Guangxi, China. He also completed his Bachelor of Science in Bioengineering at Guangxi University in 2013. His academic background provides a solid foundation for his current research, bridging microbiology, biotechnology, and food science. During his doctoral studies, Dr. Wu specialized in the molecular aspects of food biotechnology and protein engineering, laying the groundwork for his postdoctoral research at Jiangnan University. This advanced training has been crucial in shaping his research focus on the production of anti-diabetic compounds, enzyme modification, and synthetic biology applications. Throughout his academic journey, Dr. Wu has gained a strong grasp of both theoretical and practical aspects of bioengineering, allowing him to make significant contributions to the field of food biotechnology. His educational path reflects a deep commitment to advancing the understanding of microbiology and food science.

Professional Experience📝

Dr. Hao Wu has a rich professional background, combining research and teaching roles in the field of food biotechnology. After completing his Ph.D., he gained postdoctoral experience at Jiangnan University, where he advanced his research in protein engineering and microbial fermentation techniques. In December 2021, Dr. Wu joined Changsha University of Science & Technology as an Associate Professor in the School of Food Science and Bioengineering, where he has continued his research on food biotechnology, synthetic biology, and enzyme engineering. His work focuses on developing innovative solutions such as producing anti-diabetic compounds through microbial fermentation and engineering enzymes for the production of functional sugars and sugar alcohols. Dr. Wu’s role as a professor also involves mentoring graduate students and contributing to the university’s research initiatives. His experience as a peer reviewer and editorial board member for numerous scientific journals further highlights his active engagement in the scientific community.

Research Interest🔎

Dr. Hao Wu’s research interests are centered around food biotechnology, protein engineering, fermentation engineering, and synthetic biology. His work focuses on the development of potential anti-diabetic compounds through microbial fermentation techniques, employing methods such as microbial mutation breeding and fermentation process control. Additionally, Dr. Wu is dedicated to the molecular modification of enzymes, particularly in improving their thermal stability, catalytic activity, and substrate specificity for the production of functional sugars and sugar alcohols. Another key area of his research involves using cutting-edge synthetic biological technologies, including gene editing and metabolic engineering, to design and construct efficient cell factories for producing human milk oligosaccharides. His innovative approaches aim to address pressing challenges in the food industry, including the creation of healthier food ingredients and more sustainable production methods. Dr. Wu’s interdisciplinary expertise allows him to make significant contributions to both the scientific community and the applied biotechnology sector.

Award and Honor🏆

Dr. Hao Wu has earned several notable awards and honors throughout his academic and professional career, reflecting his outstanding contributions to the fields of food biotechnology and microbiology. As a leading researcher in the production of functional food ingredients and enzyme engineering, he has gained recognition for his innovative work, particularly in developing anti-diabetic compounds through microbial fermentation and engineering enzymes with improved properties. His research has been widely published in prestigious journals, and his work has attracted significant attention from the scientific community. Dr. Wu’s leadership extends beyond research, as he serves as a peer reviewer for numerous scientific journals, such as Journal of Agricultural and Food Chemistry and Critical Reviews in Food Science and Nutrition. His expertise has also led to editorial roles, including membership on the editorial boards of Food Science and Human Wellness and Journal of Future Foods, further demonstrating his respected status in the field.

Research Skill🔬

Dr. Hao Wu possesses a diverse set of research skills that have significantly contributed to his success in food biotechnology and microbiology. His expertise spans several advanced techniques, including microbial fermentation, protein engineering, and enzyme modification. Dr. Wu is proficient in employing microbial mutation breeding and fermentation process control to produce bioactive compounds, particularly for anti-diabetic applications. His work in molecular modification of enzymes focuses on improving their thermal stability, catalytic activity, and substrate specificity, using cutting-edge approaches like computational design and rational engineering. In addition, Dr. Wu is well-versed in synthetic biology techniques, such as gene editing and metabolic engineering, which he uses to design high-efficiency cell factories for the production of human milk oligosaccharides. His ability to integrate various biotechnological methodologies, along with his comprehensive understanding of biochemistry, enables him to address complex challenges and make innovative contributions to both the scientific community and the food industry.

Conclusion💡

Dr. Hao Wu is a strong candidate for the Best Researcher Award, particularly due to his:

  • High-quality publications,

  • Pioneering work in enzyme and metabolic engineering,

  • Leadership in synthetic biology applications for food science, and

  • Active contribution to the academic community through editorial roles.

If complemented by evidence of major grant leadership, mentorship of young researchers, and international academic visibility, his candidacy would be even more compelling.

Publications Top Noted✍️

  • Research Progress on the Preparation and Function of Antioxidant Peptides from Walnuts

    • Authors: Yuxi Hu, Ce Ni, Yingying Wang, Xun Yu, Hao Wu, Jia Tu, Changzhu Li, Zhihong Xiao, Li Wen

    • Year: 2023

    • Citation: International Journal of Molecular Sciences, DOI: 10.3390/ijms241914853

  • D-allulose, a Versatile Rare Sugar: Recent Biotechnological Advances and Challenges

    • Authors: Wenli Zhang, Ding Chen, Jiajun Chen, Wei Xu, Qiuming Chen, Hao Wu, Cuie Guang, Wanmeng Mu

    • Year: 2023

    • Citation: Critical Reviews in Food Science and Nutrition, DOI: 10.1080/10408398.2021.2023091

  • Engineering the Thermostability of D-lyxose Isomerase from Caldanaerobius Polysaccharolyticus via Multiple Computer-Aided Rational Design for Efficient Synthesis of D-Mannose

    • Authors: Hao Wu, Ming Yi, Xiaoyi Wu, Yating Ding, Minghui Pu, Li Wen, Yunhui Cheng, Wenli Zhang, Wanmeng Mu

    • Year: 2023

    • Citation: Synthetic and Systems Biotechnology, DOI: 10.1016/j.synbio.2023.04.003

  • Overview of Strategies for Developing High Thermostability Industrial Enzymes: Discovery, Mechanism, Modification and Challenges

    • Authors: Hao Wu, Qiuming Chen, Wenli Zhang, Wanmeng Mu

    • Year: 2023

    • Citation: Critical Reviews in Food Science and Nutrition, DOI: 10.1080/10408398.2021.1970508

  • Alanine Substitution to Determine the Effect of LR5 and YR6 Rice Peptide Structure on Antioxidant and Anti-Inflammatory Activity

    • Authors: Yun-Hui Cheng, Bu-Qing Liu, Bo Cui, Li Wen, Zhou Xu, Mao-Long Chen, Hao Wu

    • Year: 2023

    • Citation: Nutrients, DOI: 10.3390/nu15102373

  • Recent Development of Phenyllactic Acid: Physicochemical Properties, Biotechnological Production Strategies and Applications

    • Authors: Hao Wu, Cuie Guang, Wenli Zhang, Wanmeng Mu

    • Year: 2023

    • Citation: Critical Reviews in Biotechnology, DOI: 10.1080/07388551.2021.2010645

  • Application Prospects and Opportunities of Inorganic Nanomaterials for Enzyme Immobilization in the Food-Processing Industry

  • Glycosyltransferase from Bacteroides Gallinaceum Is a Novel α-1,3-Fucosyltransferase That Can Be Used for 3-Fucosyllactose Production In Vivo by Metabolically Engineered Escherichia Coli

    • Authors: Geng Chen, Hao Wu, Yingying Zhu, Li Wan, Wenli Zhang, Wanmeng Mu

    • Year: 2022

    • Citation: Journal of Agricultural and Food Chemistry, DOI: 10.1021/acs.jafc.1c06719

  • D-Mannose-Producing Isomerases and Epimerases: Properties, Comparisons, and Different Strategies

  • L-Arabinose Isomerase: Sources, Biochemical Properties, and Its Use to Produce D-Tagatose

  • Engineering Escherichia Coli for Highly Efficient Production of Lacto-N-triose II from N-acetylglucosamine, the Monomer of Chitin

  • Efficient Control of Acrylamide in French Fries by an Extraordinarily Active and Thermo-Stable L-Asparaginase: A Lab-Scale Study

  • Microbial Production, Molecular Modification, and Practical Application of L-Asparaginase: A Review

  • Metabolic Engineering of Escherichia Coli for Efficient Biosynthesis of Lacto-N-tetraose Using a Novel β-1,3-Galactosyltransferase from Pseudogulbenkiania Ferrooxidans

  • Metabolic Engineering of Escherichia Coli for Lacto-N-triose II Production with High Productivity

Jian Liu | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Jian Liu | Engineering | Best Researcher Award

Deputy Director of the Department at Tiangong University, China

Assoc. Prof. Dr. Jian Liu is a senior experimentalist and Master’s Supervisor at Tiangong University, specializing in ultra-fine fiber preparation, textile machinery design, and automation. With a PhD in Mechanical Design and Theory, he has led and contributed to six major research projects, including those funded by the National Natural Science Foundation of China and the National Development and Reform Commission. Dr. Liu has played a key role in 13 horizontal projects and four new product developments for enterprises. His innovative contributions are evident in his 11 national invention patents, multiple utility model and appearance patents, and software copyrights. As a prolific researcher, he has published over 20 scientific papers as the first author. Beyond research, he actively mentors students and advances engineering education. With a strong track record in applied research and industry collaboration, Dr. Liu continues to make significant contributions to mechanical engineering and automation.

Professional Profile 

Education

Assoc. Prof. Dr. Jian Liu has a strong academic background in mechanical engineering. He earned his Bachelor of Engineering degree in Mechanical Design, Manufacturing, and Automation from the School of Mechanical Engineering at Shandong University of Technology in 2007. Continuing his education at the same institution, he obtained a Master’s degree in Mechanical and Electronic Engineering in 2010. Driven by a passion for research and innovation, he pursued a PhD in Mechanical Design and Theory at Tiangong University, completing his doctoral studies in 2019. His academic journey reflects a continuous commitment to advancing his expertise in mechanical engineering, particularly in design, automation, and manufacturing technologies. Through his higher education and research, Dr. Liu has developed a strong foundation that supports his contributions to both academia and industry, playing a crucial role in advancing new technologies and mentoring the next generation of engineers.

Professional Experience

Assoc. Prof. Dr. Jian Liu has extensive professional experience in mechanical engineering education and research. He began his career as a teaching assistant at the Engineering Teaching Internship Training Center of Tiangong University in 2010. In 2013, he was promoted to lecturer, further strengthening his role in academia. After earning his PhD in 2019, he continued his career as an experimentalist at the same institution, where he contributed to hands-on engineering education and research. In 2020, he was appointed as a senior experimentalist, overseeing advanced experimental research and training. With over a decade of experience, Dr. Liu has been actively involved in mentoring students, leading research projects, and contributing to industrial innovation. His expertise in ultra-fine fiber preparation, textile machinery design, and automation has made him a key figure in bridging academic research with real-world applications, enhancing both educational and technological advancements in his field.

Research Interest

Assoc. Prof. Dr. Jian Liu’s research interests lie in the fields of ultra-fine fiber preparation technology, textile machinery design, and automation. His work focuses on developing innovative techniques for producing high-performance fibers with enhanced properties for various industrial applications. He is also deeply involved in the design and optimization of advanced textile machinery, aiming to improve manufacturing efficiency and precision. Additionally, Dr. Liu explores automation technologies to enhance production processes, integrating smart control systems and intelligent manufacturing techniques. His research contributions extend beyond theoretical studies, as he actively collaborates with industry partners to develop cutting-edge solutions for modern textile and mechanical engineering challenges. With numerous patents and publications, Dr. Liu continues to push the boundaries of mechanical design, automation, and material science, striving to bridge the gap between research and practical application in the evolving landscape of engineering and manufacturing.

Award and Honor

You haven’t mentioned specific awards and honors in your resume. However, based on your research contributions, patents, and publications, you may have received recognitions that can strengthen your profile. If you have received awards for research excellence, innovation, patents, or teaching achievements, highlighting them would enhance your candidacy for honors like the Best Researcher Award.If you provide details on any grants, fellowships, best paper awards, innovation prizes, or academic honors, I can craft a precise and compelling paragraph

Research Skill

Assoc. Prof. Dr. Jian Liu possesses strong research skills in mechanical engineering, specializing in ultra-fine fiber preparation, textile machinery design, and automation. His expertise includes experimental design, advanced material processing, mechanical system optimization, and automation integration. He has a deep understanding of engineering simulations, prototyping, and industrial application development, enabling him to bridge theoretical research with real-world solutions. Dr. Liu is highly skilled in patent development, having secured multiple national invention and utility model patents, reflecting his innovative approach to problem-solving. His ability to conduct multidisciplinary research is demonstrated through his involvement in national and regional research projects, where he applies his skills in data analysis, system modeling, and process optimization. Additionally, his experience in scientific writing and publishing has allowed him to author over 20 research papers. With a strong foundation in mechanical design and automation, Dr. Liu continues to drive innovation in engineering research.

Conclusion

Your strong research background, patent portfolio, and industry collaborations make you a competitive candidate for the Best Researcher Award. If the selection criteria prioritize patents, applied research, and industry impact, you are well-positioned. However, strengthening your international presence and independent funding leadership could further elevate your profile.

Publications Top Noted

  • Author(s): P. Wang, B. Wang, L. Zhao, L. Nie, J. Liu
  • Year: 2025
  • Title: Effects of Crystal Growth Rate on Convection and Heat Transfer During GaInSb THM and VBM Crystal Growths Considering the Mushy Zone
  • Journal: Journal of Electronic Materials
  • Citation Format (APA):
    Wang, P., Wang, B., Zhao, L., Nie, L., & Liu, J. (2025). Effects of crystal growth rate on convection and heat transfer during GaInSb THM and VBM crystal growths considering the mushy zone. Journal of Electronic Materials.
  • Citation Format (IEEE):
    P. Wang, B. Wang, L. Zhao, L. Nie, and J. Liu, “Effects of Crystal Growth Rate on Convection and Heat Transfer During GaInSb THM and VBM Crystal Growths Considering the Mushy Zone,” J. Electron. Mater., 2025.
  • Citation Format (Harvard):
    Wang, P., Wang, B., Zhao, L., Nie, L. and Liu, J. (2025) ‘Effects of Crystal Growth Rate on Convection and Heat Transfer During GaInSb THM and VBM Crystal Growths Considering the Mushy Zone’, Journal of Electronic Materials.

 

Bechoo Lal | Computer Science | Best Researcher Award

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Dr. Bechoo Lal | Computer Science | Best Researcher Award

Associate Professor of KLEF- KL University Vijayawada Campus Andhra Pradesh, India

Dr. Bechoolal 🌟 is an esteemed Associate Professor in Computer Science/Data Science with a passion for inspiring students through a deep understanding of technology and research. With a solid academic foundation that includes a PGP in Data Science from Purdue University and multiple PhDs in Information Systems and Computer Science 🎓, he brings a wealth of expertise to his teaching and research. Dr. Bechoolal has extensive experience in various institutions, from KLEF KL Deemed University to Western College 🏫, and has made significant contributions through his numerous research publications and certifications 🏅. His interests span Machine Learning, Data Science, and programming languages, and he actively engages in projects that explore digital transformation and its societal impacts 💻🔍. Fluent in English and Hindi 🇬🇧🇮🇳, he continues to advance knowledge and inspire the next generation of tech professionals.

Publication profile

Education

Dr. Bechoolal 🎓 is a distinguished academic with a rich educational background in Computer Science and Data Science. He earned a PGP in Data Science from Purdue University 🌟, where he specialized in data regression models and predictive data modeling. Dr. Bechoolal holds multiple PhDs—one in Information Systems from the University of Mumbai and another in Computer Science from SJJT University 🧠. His foundational studies include a Master of Technology in Computer Science from AAI-Deemed University, a Master of Computer Applications from Banaras Hindu University, and an undergraduate degree in Statistics from MG. Kashi Vidyapeeth University 📚. His continuous quest for knowledge is also reflected in his various certifications, including Machine Learning from Stanford University and an IBM Data Science Professional Certificate 🏅.

Academic Qualification

  • 📜 PGP in Data Science (2020-2021) from Purdue University, USA – Specializing in data regression models, predictive data modeling, and accuracy analyzing using machine learning.
  • 📜 PhD in Information System (2015-2019) from the University of Mumbai, India – Research Area: Data Science.
  • 📜 PhD in Computer Science (2011-2015) from SJJT University, India – Research Area: Machine Learning.
  • 📜 Master of Technology (M. Tech) in Computer Science and Engineering (2004-2006) from AAI-Deemed University, Allahabad, India.
  • 📜 Master of Computer Application (MCA) (1995-1998) from Institute of Science, Banaras Hindu University (BHU), India.
  • 📜 Graduation (Statistics-Hons) (1990-1993) from the Department of Mathematics and Statistics, MG Kashi Vidyapeeth University, India.

Data Science Certifications and Training

  • 🎓 Machine Learning, Stanford University, USA (2020)
  • 🎓 IBM Data Science Professional Certificate (2020)
  • 🎓 Data Science and Big Data Analytics (2019), ICT Academy, Govt. of India
  • 🎓 Security Fundamentals, Microsoft Technology Associate (2017)
  • 🎓 Intelligent Multimedia Data Warehouse and Mining (2009), University of Mumbai
  • 🎓 Python Programming (2017), University of Mumbai, India

 

Teaching Interest 

  • 📘 Data Science/Machine Learning
  • 📘 Database 📘 C/C++/Python Programming Languages
  • 📘 Software Engineering

Research Interest

  • 🔍 Machine Learning
  • 🔍 Data Science

Computer Science/Data Science Skills

💻 Machine Learning, Data Visualization, Big Data Analytics

📊 Predictive Modelling: Supervised Learning (Linear and Logistic Regression, Decision Tree, Support Vector Machine (SVM), Naïve Bayes Classifiers), Unsupervised Learning (K-Means clustering, principal components analysis (PCA))

💻 Programming Languages: Python (NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn), SPSS, R-Programming

💻 Operating Systems/Platforms: UNIX/LINUX, WINDOWS, MS-DOS

💻 C/C++, CORE JAVA Programming Languages

💻 DBMS/RDBMS: Oracle, SQL, MySQL, NoSQL

Publication top notes

  • Improving migration forecasting for transitory foreign tourists using an Ensemble DNN-LSTM model
    Authors: Nanjappa, Y., Kumar Nassa, V., Varshney, G., Pandey, S., V Turukmane, A.
    Journal: Entertainment Computing
    Year: 2024
    Citations: 0 📅
  • Using social networking evidence to examine the impact of environmental factors on social followings: An innovative Machine learning method
    Authors: Murthy, S.V.N., Ramesh, P.S., Padmaja, P., Reddy, G.J., Chinthamu, N.
    Journal: Entertainment Computing
    Year: 2024
    Citations: 0 📅
  • Real-Time Convolutional Neural Networks for Emotion and Gender Classification
    Authors: Singh, J., Singh, A., Singh, K.K., Samudre, N., Raperia, H.
    Conference: Procedia Computer Science
    Year: 2024
    Citations: 0 📅
  • Identification of Brain Diseases using Image Classification: A Deep Learning Approach
    Authors: Singh, J., Singh, A., Singh, K.K., Turukmane, A.V., Kumar, A.
    Conference: Procedia Computer Science
    Year: 2024
    Citations: 0 📅
  • Fake News Detection Using Transfer Learning
    Authors: Singh, J., Sahu, D.P., Gupta, T., Lal, B., Turukmane, A.V.
    Conference: Communications in Computer and Information Science
    Year: 2024
    Citations: 0 📅
  • Reliability Evaluation of a Wireless Sensor Network in Terms of Network Delay and Transmission Probability for IoT Applications
    Authors: Mishra, P., Dash, R.K., Panda, D.K., Lal, B., Sujata Gupta, N.
    Journal: Contemporary Mathematics (Singapore)
    Year: 2024
    Citations: 0 📅
  • TRANSFER LEARNING METHOD FOR HANDLING THE INTRUSION DETECTION SYSTEM WITH ZERO ATTACKS USING MACHINE LEARNING AND DEEP LEARNING
    Authors: Upender, T., Lal, B., Nagaraju, R.
    Conference: ACM International Conference Proceeding Series
    Year: 2023
    Citations: 0 📅
  • Monitoring and Sensing of Real-Time Data with Deep Learning Through Micro- and Macro-analysis in Hardware Support Packages
    Authors: Lal, B., Chinthamu, N., Harichandana, B., Sharmaa, A., Kumar, A.R.
    Journal: SN Computer Science
    Year: 2023
    Citations: 0 📅
  • An Efficient QRS Detection and Pre-processing by Wavelet Transform Technique for Classifying Cardiac Arrhythmia
    Authors: Lal, B., Gopagoni, D.R., Barik, B., Kumar, R.D., Lakshmi, T.R.V.
    Journal: International Journal of Intelligent Systems and Applications in Engineering
    Year: 2023
    Citations: 0 📅
  • IOT-BASED Cyber Security Identification Model Through Machine Learning Technique
    Authors: Lal, B., Ravichandran, S., Kavin, R., Bordoloi, D., Ganesh Kumar, R.
    Journal: Measurement: Sensors
    Year: 2023
    Citations: 3 📅📈