Dr D Maneiah
CMR Technical Campus
Research areas: Engineering · Mechanical Engineering · Advanced Welding Techniques Analysis · Welding Techniques and Residual Stresses · Cellular and Composite Structures
0000-0002-1462-9470
About
Dr. D. Maneiah is presently working as a Professor and Dean of Student Affairs, CMR Technical Campus, (A Unit of CMR Group of Institutions) Hyderabad, Telangana. He acquired Bachelor’s degree (Mechanical Engineering) and Master’s degree (Industrial Engineering) from Sri Venkateswara University, Andhra Pradesh. He completed his Ph.D degree in the area of FS Welding from Jawaharlal Nehru Technological University, Hyderabad. He has 22 years’ experience in teaching field and 6 years of Research experience. His major areas of research interests include Manufacturing, Composite materials and structures, Optimization, and utilization of light-weight materials in structural applications. Dr. D. Maneiah co-authored a book titled “Development of Labyrinth Type Solar Thermal Energy Storage System”– ISBN number: 978-620-0-11406-8 in Lambert Academic Publishing, Germany. He has published 60 research papers in reputed National and International journals and presented 10 papers in International/National conferences and 18 patents published and also received RS1 crore grant from DST-SEED. He has conducted many national events like Short term training programs and Faculty Development Programs in the field of Mechanical engineering. He also a Fellow member in Institution of Engineers and a life member of various professional bodies including Indian Society of Technical Education (ISTE), Society of Automotive Engineering (SAE), Institute of Electrical and Electronics Engineers (IEEE), and Indian Society of Mechanical Engineers (ISME).
Employment
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CMR Technical Campus HOD2010 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (35)
- Machine Learning for Additive Manufacturing of 3D Printed Multi‐Material Tissue Mimicking Anatomical Structures Save
- Analysis of the Medicine Learning Integrated Executive Support System for Clinical Prediction Using AI and ML Save
- Deep learning-based analysis and prediction of 3D printing process parameters using a ceramic composite dataset Save
- A More Adaptable and Accessible Pdf Chat_Bot Algorithm by Using Generative Artificial Intelligence (LLMS&RAG) Save
- A Safe and Secured Deep Learnıng Cnn Approach for Robust Intellıgent Malware Detectıon Usıng Artıfıcıal Intellıgence Save
- The Evaluation of Data Science Algorithms for Implementing Machine Learning Smart Healthcare System Using Fuzzy Control Save
- Maximization of Tensile Strength of Aluminum 6061 Alloy T6 Grade Friction Welded Joints by Using the Desirability Function Save
- A review on process parameter optimization of friction stir welded dissimilar alloys Save
- Axial crushing behaviour of Kevlar polymer composite tubular structures under quasi-static compression Save
- CFD analysis of diesel-methanol blend in 4-stroke variable compression ratio internal combustion engine Save
- Effect of welding angle on strength of friction welded aluminum 6061-T6 alloy welded joints Save
- Experimental investigation of mechanical properties and sliding wear behavior of poly propylene reinforced epoxy composites with filler material Save
- Influence of abrasive water jet machining parameters on material removal rate of hybrid metal matrix composites Save
- Progressive collapse behaviour of aluminium-composite bitubular energy absorbers subjected to axial loading Save
- Double Diffusion Caused by Hot Strip in Porous Material Save
- Experimental Investigation on Strength of Friction Stir Welded Al 6061-T6 Alloy Joints with Varying Oblique Angle Save
- Finite element investigations on the effect of stiffeners in polygonal tubes under axial impact Save
- Gas tungsten and shielded metal arc welding of stainless steel 310 and 304 grades over single and double ‘V' butt joints Save
- Improving the energy-absorbing properties of hybrid aluminum-composite tubes using nanofillers for crashworthiness applications Save
- Optimization of machining parameters for surface roughness during abrasive water jet machining of aluminium/magnesium hybrid metal matrix composites Save