Assist Prof Dr. Sourav Da, Indian Institute of Technology Hyderabad, India
Dr. Das, a Structural Engineering Ph.D. graduate from The University of British Columbia, specializes in advanced methodologies for structural reliability and design. His postdoctoral research at the University of Waterloo focuses on pioneering AI-based digital twins and multi-fidelity simulations for high-rise timber buildings. His expertise spans structural dynamics, uncertainty quantification, and AI, with notable contributions in high-dimensional multi-objective optimization and reliability assessment using Physics-Informed Neural Networks. His impactful work, published in leading journals and supported by prestigious grants such as those from NSERC, reflects his significant role in advancing structural engineering and AI. As a dedicated educator and reviewer, Dr. Das also contributes to the academic community through teaching and mentoring in complex engineering subjects.
Professional Profile:
Suitability for the Award
Assist. Prof. Dr. Sourav Das is an exceptional candidate for the Research for Best Researcher Award. His strong educational background, combined with his cutting-edge research in structural engineering and reliability-based design, make him a standout in his field. His work on incorporating artificial intelligence in structural reliability analysis and his contributions to earthquake engineering and vibration control are particularly noteworthy and align with the award’s emphasis on innovative and impactful research.
Academic and Research Excellence:
Dr. Das holds a Ph.D. in Structural Engineering from The University of British Columbia, where his thesis focused on “Surrogate Assisted Reliability Analysis and Probabilistic Design of Structures under Uncertainty.” This demonstrates his deep expertise in advanced methodologies for structural reliability and design.
His postdoctoral research at the University of Waterloo involves cutting-edge projects such as AI-based digital twins and multi-fidelity simulation for high-rise timber buildings, reflecting his commitment to pioneering research in structural engineering and AI applications.
Innovative Contributions:
Dr. Das’s research interests span structural dynamics, uncertainty quantification, AI, and earthquake engineering, showcasing a broad and impactful approach to tackling complex engineering challenges.
His work on high-dimensional multi-objective optimization using deep learning and reliability assessment of stochastic systems using Physics-Informed Neural Networks represents significant advancements in structural engineering and artificial intelligence.
Publication and Impact:
His journal publications in high-impact journals such as Engineering Applications of Artificial Intelligence and Reliability Engineering & System Safety highlight his contribution to advancing the field. Notably, his work on reliability-based optimization and SMA-based control structures has garnered attention and citations, reflecting the relevance and impact of his research.
Dr. Das has also been actively involved in reviewing for reputable journals, further underscoring his standing in the research community.
Awards, Funding, and Scholarships:
Dr. Das has received prestigious scholarships and funding, including the Natural Sciences and Engineering Research Council of Canada (NSERC) and Forestry Innovation Investment, which support his innovative research and contributions.
His multiple scholarships, including those from UBC and the Indian government, demonstrate recognition of his academic excellence and potential.
Teaching and Professional Experience:
Dr. Das’s experience as a Teaching Assistant and Assistant Professor includes teaching complex subjects such as structural analysis, earthquake engineering, and solid mechanics, highlighting his dedication to education and mentoring.
His role in guiding thesis work and participation in professional activities as a reviewer further reflects his engagement with the academic and professional community.
Publication Top Notes:
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Title: Reliability-Based Optimization of Nonlinear Energy Sink with Negative Stiffness and Sliding Friction
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Title: Optimization of SMA-Based Damped Outrigger Structure Under Uncertainty
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Title: Robust Design Optimization for SMA-Based Nonlinear Energy Sink with Negative Stiffness and Friction
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Title: State-of-the-Art Review of Design of Experiments for Physics-Informed Deep Learning
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Title: Vibration Control of Horizontal Axis Offshore Wind Turbine Blade Using SMA Stiffener