Dr. Vamsi Inturi | Machine Learning | Best Researcher Award

Dr. Vamsi Inturi | Machine Learning | Best Researcher Award

Dr. Vamsi Inturi, Chaitanya Bharathi Institute of Technology, India

Dr. Vamsi Inturi is an accomplished researcher and academic specializing in Mechanical Engineering, with expertise in fault diagnosis, health monitoring, and digital twin technologies. He earned his Ph.D. from BITS Pilani, focusing on adaptive condition monitoring for wind turbine gearboxes. With experience spanning postdoctoral research at Trinity College Dublin and academic roles in India, he has made significant contributions to machine learning applications in engineering. He has received prestigious awards, including the Best Paper Award at the 43rd International JVE Conference. His research integrates AI and signal processing to enhance predictive maintenance and mechanical system reliability.

Professional Profile:

Google Scholar

Orcid

Scopus

🏆 Suitability for Award 

Dr. Vamsi Inturi is an outstanding candidate for the Best Researcher Award, given his pioneering work in mechanical fault diagnosis, machine learning, and predictive maintenance. His research significantly impacts renewable energy systems, particularly wind turbines, optimizing efficiency and reducing downtime. Recognized with international travel grants, research fellowships, and best paper awards, he has demonstrated academic excellence and innovation. His work in digital twins and signal processing has been published in high-impact journals, reinforcing his status as a leader in mechanical engineering research. His commitment to advancing engineering solutions makes him highly deserving of this prestigious recognition.

🎓 Education

Dr. Vamsi Inturi holds a Ph.D. in Mechanical Engineering from BITS Pilani (2016-2020), where he developed an adaptive condition monitoring scheme for wind turbine gearboxes under the supervision of Prof. Sabareesh G R and Prof. Pavan Kumar P. He earned his M.Tech in Machine Design from JNTU Kakinada (2012-2014), focusing on modeling process parameters in milling aluminum composites. His academic journey began with a Bachelor’s in Mechanical Engineering, followed by extensive research in fault diagnosis and mathematical modeling. His interdisciplinary expertise bridges mechanical systems, AI-driven analytics, and sustainable energy solutions, shaping advancements in mechanical diagnostics.

👨‍🏫 Experience 

Dr. Vamsi Inturi has a diverse academic and research career. He is currently an Assistant Professor at CBIT(A), Hyderabad, specializing in engineering drawing, robotics, and mechanical systems. Previously, he was a Postdoctoral Researcher at Trinity College Dublin, managing the REMOTE-WIND project. He also served as a Research Scholar at BITS Hyderabad, working on mechanical vibrations and fault diagnosis. His teaching experience includes faculty positions at PACEITS and QISIT, mentoring students in mechanical design and computational modeling. With extensive research output in AI-driven diagnostics, he plays a crucial role in advancing predictive maintenance strategies.

🏅 Awards and Honors

Dr. Vamsi Inturi has received multiple accolades for his research excellence. He was awarded the Best Paper Award at the 43rd International JVE Conference (2019) and recognized for outstanding Ph.D. performance (2017-18). As a CSIR Senior Research Fellow (2019-20), he contributed to groundbreaking studies in mechanical diagnostics. He also secured a CSIR International Travel Grant (2019) to present his research globally. Additionally, he was elected a campus-level senate member for Ph.D. programs (2018-20). His expertise has made him a sought-after speaker and session co-chair at international mechanical engineering conferences.

🔍 Research Focus 

Dr. Vamsi Inturi’s research centers on health monitoring, fault diagnosis, and AI-driven mechanical analytics. His work integrates machine learning, signal processing, and digital twin technologies to enhance predictive maintenance in mechanical systems, particularly wind turbines. He specializes in mathematical modeling and deep learning applications for fault detection, helping industries reduce operational risks. His studies on adaptive condition monitoring schemes for gearboxes have led to innovative diagnostic frameworks. His interdisciplinary approach merges mechanical engineering with computational intelligence, making significant contributions to sustainable energy and industrial automation.

📚 Publication Top Notes:

  • Title: Comparison of Condition Monitoring Techniques in Assessing Fault Severity for a Wind Turbine Gearbox Under Non-Stationary Loading
    • Volume: 124
    • Citations: 102
  • Title: Evaluation of Surface Roughness in Incremental Forming Using Image Processing-Based Methods
    • Year: 2020
    • Citations: 68
  • Title: Integrated Condition Monitoring Scheme for Bearing Fault Diagnosis of a Wind Turbine Gearbox
    • Year: 2019
    • Citations: 63
  • Title: Comprehensive Fault Diagnostics of Wind Turbine Gearbox Through Adaptive Condition Monitoring Scheme
    • Year: 2021
    • Citations: 45
  • Title: Optimal Sensor Placement for Identifying Multi-Component Failures in a Wind Turbine Gearbox Using Integrated Condition Monitoring Scheme
    • Year: 2022
    • Citations: 30

 

Assist Prof Dr. Ebtisam Alabdulqader | Machine Intelligence | Best Researcher Award

Assist Prof Dr. Ebtisam Alabdulqader | Machine Intelligence | Best Researcher Award

Assist Prof Dr. Ebtisam Alabdulqader , Kind Saud University , Saudi Arabia

Prof. Dr. Ebtisam Alabdulqader, an esteemed academic at King Saud University 🎓, possesses a rich educational background, including a Ph.D. in Computing Sciences from Newcastle University, UK, and certifications in various domains such as user experience, bioethics, and cryptography. As the Vice Director of the Digital Innovation Unit and Assistant Professor in the Information Technology Department, she actively contributes to the advancement of education and innovation. Dr. Alabdulqader’s leadership extends to founding and leading the ArabHCI Community and serving as the Vice Chair of the Saudi ACM SIGCHI Chapter. Her extensive experience as a lecturer and teaching assistant underscores her commitment to nurturing future talents in the field of computer and information sciences. Dr. Alabdulqader’s involvement in numerous committees and projects further highlights her dedication to academic excellence and technological innovation 🌟.

🌐 Professional Profile:

Google Scholar

Education:

  • Ph.D. in Computing Sciences, School of Computing, Newcastle University, UK (2015-2019)
  • MSc in Information Systems, College of Computer and Information Sciences, King Saud University, Saudi Arabia (2007-2009)
  • Bachelors in Computer Applications, College of Computer and Information Sciences, King Saud University, Saudi Arabia (2000-2005)

Certificates:

  • Bioethics NCBE Training, KACST, Riyadh, Saudi Arabia (2021)
  • Certified User Experience Specialist (CXS), Akendi, London, UK (2019)
  • Good Clinical Practice (GCP) eLearning, NHS, Newcastle Upon Tyne, UK (2015)
  • Training on Cryptography, PMC in KSU, Riyadh, Saudi Arabia (2010)
  • Oracle Database 11g: Administration Workshop, ORACLE University, Riyadh, Saudi Arabia (2010)
  • MULTOS Developer, MULTOS, Warrington, UK (2009)
  • Network and Host Security, Security Academy I(TS)2, Riyadh, Saudi Arabia (2009)

Experience:

  • Vice Director of Digital Innovation Unit, Entrepreneurship Institute, King Saud University (2022-Present)
  • Assistant Professor, Information Technology Department, College of Computer and Information Sciences, King Saud University (2020-Present)
  • Founder and Leader, ArabHCI Community (2016-Present)
  • Vice Chair, Saudi ACM SIGCHI Chapter (2017-2021)
  • Lecturer, Information Technology Department, College of Computer and Information Sciences, King Saud University (2009-2020)
  • Teaching Assistant, Information Technology Department, College of Computer and Information Sciences, King Saud University (2005-2009)

Memberships in Scientific & Professional Societies:

  • ACM SIGCHI Member
  • Professional ACM Member
  • Open Lab, School of Computing, Newcastle University

Projects:

  • Lead hackathon organizer for “MITO Patient Engagement Study”
  • Designing technology for CueS: a wearable cueing device for stroke patients

Academic Activities:

  • Curriculum Review and Development Committee
  • Human Resources Committee (Head)
  • Graduation Projects Seminars Committee
  • Graduation Projects Examination Committee

Service Activities & Participations:

  • Active PC member in various ACM and non-ACM research venues
  • Judge in Fintech 101 Workshop for KSU Students
  • Judge for the International Mobile Gaming Awards

Invited Talks, Panels & Representation:

  • Panelist at the “Research Experiences in HCI” session by KSU CCIS
  • Invited panelist at CS-NCL equality and diversity events
  • ACM SIGCHI Inclusion Innovators, Inclusion team for SIGCHI Diversity & Inclusion Events/Activities

Honors and Awards:

    • CCIS Appreciation Award (2020)
    • Best Lecturer Award (2013)
    • Best Academic Advisor Award (2013)
    • Excellence in Research and Publications Award (2010)

Publication Top Notes:

inist HCI: Taking Stock, Moving Forward, and Engaging Community
Citation -14
IslamicHCI: Designing with and within Muslim Populations