Instructor

Dr. Abdul Waris

Research Associate, Chair of Geotechnical Engineering
University of Siegen, Germany

Ph.D. in Geotechnical Engineering, IIT Hyderabad · Prime Minister’s Research Fellow

PMRF
Prime Minister’s Research Fellow
Gold
Institute Gold Medalist, M.Tech
10
Journal articles
2026
Research Excellence Award
About

Research, teaching and practice

Dr. Abdul Waris is a Research Associate (Wissenschaftlicher Mitarbeiter) at the Chair of Geotechnical Engineering, University of Siegen, Germany, where he teaches, mentors and supervises Master’s students. His research covers reliability analysis, uncertainty quantification and machine learning in geotechnical engineering, with a focus on surrogate modelling, offshore geotechnics, and probabilistic, data-driven approaches to geotechnical risk assessment.

He holds a Ph.D. in Geotechnical Engineering from IIT Hyderabad, where he was a Prime Minister’s Research Fellow. His doctoral thesis, “Reliability Analysis of Unsaturated Finite Slopes under Rainfall Conditions Using Data-Driven Computational Frameworks”, was supervised by Prof. B. Munwar Basha, and his Ph.D. research received the Research Excellence Award 2026 at IIT Hyderabad.

He has delivered hands-on training in Machine Learning and Finite Element Methods for Civil and Geotechnical Engineering, lectured on ML in geotechnics at faculty development programmes in India, and presented his research in Oslo (Norway), Barcelona (Spain) and at Oregon State University (USA). His work appears in Q1 journals from ASCE, Springer, Elsevier and Nature Portfolio.

Areas of expertise

  • Computational Geomechanics
  • Uncertainty Quantification
  • Reliability Analysis
  • Scientific Machine Learning
  • Surrogate Modelling
  • Offshore Geotechnics

Tools

Python · MATLAB · Octave · C · PLAXIS · ABAQUS · HYDRUS · GIS · AutoCAD

Courses

Learn with Dr. Abdul Waris

Sat17OctStarts Saturday, 17 October 2026
Registration open · Cohort 01Live online · Beginner-friendly

AI & Machine Learning for Civil Engineers

From Engineering Data to Prediction, Explainability & Uncertainty

A live, code-along online workshop that takes Civil Engineers from raw engineering data to trustworthy ML predictions, explainable models and an introduction to uncertainty quantification. No prior Python or Machine Learning experience required.

8
Live sessions
90 min
Per session
12 hrs
Live instruction
Google Colab
Code in browser
17 Oct
Cohort starts
Live
Online format
6-step
Practical workflow
Civil
Engineering focus
Dr. Abdul WarisUniversity of Siegen, Germany
Education

Academic background

  1. 2022 – 2026

    Ph.D., Geotechnical Engineering

    Indian Institute of Technology Hyderabad

    Prime Minister’s Research Fellowship · CGPA 9.54/10 · Research Excellence Award 2026 · Civil Engineering department Ph.D. representative, 2023–24

  2. 2020 – 2022

    M.Tech., Geotechnical Engineering

    National Institute of Technology Durgapur

    Institute Gold Medalist · CGPA 9.19/10 · AICTE PG Scholarship

  3. 2016 – 2020

    B.Tech., Civil Engineering

    Islamic University of Science and Technology, Awantipora

    CGPA 9.46/10 · Ranked 2nd among 120+ students · 1st among 56 in MATLAB for Engineers

Experience

Teaching & positions

  1. June 2026 – present

    Research Associate (Wissenschaftlicher Mitarbeiter)

    University of Siegen, Germany

    Teaches, mentors and supervises Master’s students with Prof. Dr.-Ing. habil. Kerstin Lesny while researching reliability analysis, uncertainty quantification and ML applications in geotechnical engineering.

  2. Jan – Apr 2024

    Course Instructor, Structural Analysis-I

    Kashmir University

    Taught 3rd-semester B.Tech. students.

  3. 2022 – 2025

    Teaching Assistant

    IIT Hyderabad and NIT Srinagar

    Geotechnical Engineering I and II, and Surveying-I, including running surveying labs and coordinating the surveying camp.

Invited lectures

Talks & workshops

June 2025

Introduction to Machine Learning and Finite Element Methods in Geotechnical Engineering

Invited resource person, five-day workshop

National Institute of Technology Srinagar, India

March 2025

Unlocking Geotechnical Insights with Machine Learning: Fundamentals to Applications

Invited lecture, national Faculty Development Program on AI and Automation in Civil Engineering

Dr. D.Y. Patil Institute of Technology, Pune, India

September 2024

Machine Learning for Geotechnical Engineers: Fundamentals and Practical Applications

Invited talk

Oregon State University, USA

Recognition

Honours & awards

  • Research Excellence Award 2026 for outstanding research during the Ph.D. at IIT Hyderabad
  • Prime Minister’s Research Fellowship, one of India’s most prestigious Ph.D. fellowships
  • International Travel Grant (ANRF-ITS) to present at ICGRE 2025, Barcelona, Spain
  • Institute Gold Medal, M.Tech. Geotechnical Engineering, NIT Durgapur (2020–22)
  • AICTE PG Scholarship for the M.Tech. at NIT Durgapur
  • GATE 2020 qualified, 94.4 percentile
  • Among the national toppers in the NPTEL course Geotechnical Engineering-I (IIT Kharagpur)
Publications

Selected journal articles

  1. In press

    Reliability Analysis of Unsaturated Soil Slopes using Advanced Surrogate Models: A Comparative Study of PCE-MCS, K-MCS, and Gradient-Based Methods

    Waris, K.A., and Basha, B.M. Journal of Computing in Civil Engineering, ASCE

  2. 2026

    Reliability Analysis of Unsaturated Soil Slopes under Correlated Non-Gaussian Inputs using Surrogate-Enhanced MCS, FORM and SORM

    Waris, K.A., and Basha, B.M. International Journal of Geomechanics, ASCE

  3. 2026
  4. 2026

    Probabilistic Stability Assessment of Ash Dykes Using Surrogate Models and Multi-Slip Surface Analysis

    Kandikonda, A., Waris, K.A., and Basha, B.M. Geotechnical and Geological Engineering, Springer

  5. 2025

    Optimization of Factors of Safety and Displacements of Unsaturated Soil Slopes by Bio-Inspired Meta-Heuristic Methods

    Waris, K.A., and Basha, B.M. International Journal of Geomechanics, ASCE

  6. 2025

    Detection and Prediction of Slope Stability in Unsaturated Finite Slopes using Interpretable Machine Learning

    Waris, K.A., Rahaman, M.A., and Basha, B.M. Modeling Earth Systems and Environment, Springer

  7. 2024

    Pseudo-Static Slope Stability Analysis using Explainable Machine Learning Techniques

    Waris, K.A., Sheikh, J.F., Alluri, H.R., and Basha, B.M. Natural Hazards, Springer

  8. 2024
  9. 2024

    Soil Categorization and Liquefaction Prediction Using Deep Learning and Ensemble Learning Algorithms

    Ghani, S., Thapa, I., Adhikari, D.K., and Waris, K.A. Transportation Infrastructure Geotechnology, Springer

  10. 2023

    Assessment of Landfill Leachate and its Surface and Sub-surface Migration: Experimental and Numerical Investigations

    Kenue, A.W., Adhikary, A., Sana, E., Pal, S., and Hussain, M. Journal of Hazardous, Toxic, and Radioactive Waste, ASCE

Conference papers and presentations: ISGSR 2025, Oslo, Norway · CSEE 2025 and ICGRE 2025, Barcelona, Spain · Geo-EnvironMeet 2025 (ASCE), Louisville, Kentucky, USA · Indian Geotechnical Conference (IGC) 2023

Full list on Google Scholar
Earlier work

Research & internships

  1. 2021 – 2022

    M.Tech. dissertation, NIT Durgapur and NIT Srinagar

    Studied the overloaded cell of Srinagar’s only engineered landfill: leachate characteristics, numerical modelling of contaminant migration with HYDRUS, and a constructed-wetland remediation design.

  2. June – July 2022

    Internee Geotechnical Engineer, Central University of Kashmir

    Supervised soil improvement with stone columns on a campus construction project and helped scrutinise geotechnical reports.

  3. Oct – Nov 2019

    Research Intern, IIT Roorkee

    Fire resistance of reinforced concrete columns under Dr. U.K. Sharma.

  4. Jan – Feb 2019

    Student Intern (World Bank sponsored), IIT Gandhinagar

    Landslide susceptibility zonation of NH44 using GIS and remote sensing.