Dr. Daljit Singh

Basic Details

Name

Dr. Daljit Singh

Designation

Assistant Professor (Guest Faculty)

Department

Civil Engineering

Contact

Phone (O)

NA

Phone(R)

NA

Mobile

8968160830

e-mail

daljitsingh@sliet.ac.in, daljitsaini1994@gmail.com

Educational Details

Educational Qualification

1. Ph.D. (Civil Engineering, Structures), Punjab Engineering College, Deemed to be University Sector 12 Chandigarh
2. M.Tech. (Civil Engineering, Structures), Punjab Engineering College, Deemed to be University Sector 12 Chandigarh
3. B.Tech (Civil Engineering), Guru Nanak Dev Engineering College, Ludhiana, Punjab
4. Diploma (Civil Engineering), Chandigarh College of Engineering and Technology Sector 26, Chandigarh

Experience

Experience

1. Worked as Assistant Professor in Civil Engg Department at Maharaja Agrasen University Baddi. ((1-08-2017 to 22-06-2018)

2. Worked as Site Engineer at Shivinderpal Company. (23-06-2018 to 31.07.2018)

Award

Award

1. Best Paper Award in Category of Research Scholar in research paper with title ‘Machine learning Regression Model to predict the water/cement ratio for the Concrete mixes as per IS 10262:2019’ presented at International conference on trends in Management, Engineering and Technology (ICMET – 2022), held on December 26-27, 2022, jointly organised by VVIT, Purnea, Bihar and Global Conference Hub, Coimbatore, India.

Publications

Publications

1. Singh, D., & Singla, S. (2024). Effect of chloride and sulphate attack in concrete containing biomass ash and silica fumes. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 48(2), 825–841. https://doi.org/10.1007/s40996-023-01332-2
2. Sunita, Sood, V., Singh, S., Gupta, P. K., Gusain, H. S., Tiwari, R. K., Khajuria, V., & Singh, D. (2024). Estimation and Validation of Snowmelt Runoff Using Degree Day Method in Northwestern Himalayas. Climate, 12(12), 200. https://doi.org/10.3390/cli12120200
3. Research paper with title ‘Machine learning Regression Model to predict the water/cement ratio for the Concrete mixes as per IS 10262:2019’ presented at International conference on trends in Management, Engineering and Technology (ICMET – 2022), held on December 26-27, 2022, jointly organised by VVIT, Purnea, Bihar and Global Conference Hub, Coimbatore, India.
4. Research paper with title ‘A Machine Learning-Based Model to Predict Compressive Strength of High Performance Concrete’. IUP Journal of Structural Engineering, Vol. 18, Issue 1, January 2025.
5. Research paper with title ‘Strength and microstructure analysis of geopolymer paste using glass powder, slag and fly ash’. IUP Journal of Structural Engineering, Vol. 18, Issue 1, January 2025.

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