Good day, Dr. Romi Dhakad. I'm Arjun. I've had a look through your background and your professional record. I'm interested in hearing more about your work and how you see yourself fitting in here with our faculty. Ready to start?

Ready.

Hello.

Please start by introducing your professional journey in academia.

Yeah, my myself to doctor Romil Dakar and I have done my primary schooling up to 10th class from Gwalior city which is in Madhya Pradesh. After that I have done my higher education from 12th class from indoor city which I also belong to the Madhya Pradesh. And in 2012 I get an admission for Bachelor of Engineering in Ujjain Engineering College in the branch of Mechanical Engineering.

2015 to pay honours degree having uh CEP of 77.51 uh, After that I have qualified GATE examination. Uh, based on the GATE scorecard I get a uh, an IT natural include technology Rourkela for doing my Mtech degree in the specialization of machine design and analysis. I have finished my uh Mtech in 2019, which is started in 2017 to 2019. During Mtech I got my CGPA 9.2.

And after that I have done so for some period of job and for three months I work as a lecturer for mathematics in one of the private coaching classes which is for preparation of IITJE examination. And that that job I have done for three months. After that I have done for three months as a assistant professor in the Department of Mechanical Engineering in the Mansour University, which is also.

AAM belongs to the MA mother brothers and in in the spring semester of 2019 in the month of December, I get a admission UH in the IIT IIT Roorkee for my PhD degree. And I have done my PhD in the recent year 2025 in April month. And during my PhD profession UH, I have published 4 sci general paper having uh six, six to seven.

The national conference paper and my uh, like, uh, PhD topic is related to the modeling analysis of elastomer was shock isolation system for a novel application. And uh, right now I am working as a senior scientist project position in the, uh, IIT Delhi. And I have also offered a institute post job position in IIT Kharapur. So maybe uh, next month we can join as a uh, uh, institute position in the IIT Khadapur in the.

Mechanical engineering department and which related to the domain of metamaterial and computational modeling of vibration, vibration and so isolation system for enable application or any engineering application. And along with I have also worked on the like application or neural network network for the material modeling of plasto material which is also related to the computational modeling of the elastomer material. So that is my journey from my primary educ.

Into my higher education along with the experience.

Thank you, Professor. Let’s now focus on verifying specific competencies critical to this role. Starting with one of the core areas: Computational Modelling. Can you walk me through how you would approach the computational modeling of an elastomer-based shock absorption system? Specifically, how would you deal with the material non-linearity often encountered in such systems?

Uh, uh, for non linear modeling of like lasso material, we have generally used hyper elastic material model, uh, to define its non linear elastic properties. And along with two define is like time dependent properties. Uh, uh, we use like viscoelastic models for the, uh, small deformation range like uh, general Maxwell model, Kelvin Marksman model and generalized Maxwell model. So the like hyper elastic as well as disco elastic model.

It's appropriate to model its nonlinear, elastic as well as viscoelastic properties, that is, a time independent and time-dependent properties.

Thank you, Professor. You mentioned hyperelastic and viscoelastic modeling techniques. Could you elaborate further on how you would validate the computational models you develop for such systems? Specifically, what experimental techniques or data inputs would you use for comparison?

Yeah. Uh, for validation or like hyprolastic modeling, uh, we generally use uh, uh, experiment as data such as uniexial tensile compression, uh, as well as planar test data and equaxial test data In three deformation mode, we can validate our hyper elastic model, which is used to model our Elasto material. And however sorry along with the cyber elastic.

Uh, we use like stress relaxation test data to validate a viscous Astro properties.

Understood. Using uniaxial, planar, and biaxial tests, along with stress relaxation data, is a well-rounded approach for validation. Moving to a related domain: Applying AI/ML to Materials Science. You mentioned using neural networks for modeling elastomer materials. Can you describe how you structured the neural network and curated the training data for this purpose?

Yeah. Umm, actually it uh, I have developed simple neural network to model the hyper elastic properties of one of the hyper elastic model, which is Ogden 3rd order model. So to uh, train that model, uh, we use uh, uh, uniaxial, uh, force versus displacement data, uh, along with our different coefficient of hyperlastic models and that. Result that data to train the neural network we obtain from the.

Uh, like finite elements modeling, finite element modeling, uh, having different samples of the, uh, myelastic material constant. And based on that data, I train a neural network model, which our model is consist of, uh, uh, primary, primary layer and final layer. And to, uh.

So, if I understand correctly, you utilized finite element simulations to generate diverse datasets with varying hyperelastic material constants and then trained a neural network based on this synthetic force versus displacement data. To ensure robustness, how did you evaluate the accuracy and generalization of your trained model against experimental or unseen data?

Uh, my.

Take your time, Professor. How did you ensure the accuracy and reliability of your trained neural network model?

Hello.

Yeah.

Yeah, nuclear technical issue. I have disconnected for some time. Yeah, I am explaining the neural networks. So I have trained my neural networks, uh, based on the Unix CL, uh, tensile and compression test data along with the different, uh, hyprolastic constant for 3rd order model. That data I have prepared from finite elements modeling, uh, by using the random samples of the, uh, different. Material constant of different type. Elastic Material constant of Ogden metal based on.

Training of their data, our final union metro network, uh, constraint different neutral neurons in the different hidden layer. And after that I have validated their data from the experimental test data of our developed neural network yeah.

Thank you for clarifying. Validating the neural network with experimental test data after training it on FEM-generated data sounds rigorous. Let's now focus on your teaching capabilities. Could you explain how you would structure a theoretical and laboratory course on computational modeling for advanced engineering students? For example, how would you balance theory and hands-on applications?

Uh, can you repeat? Actually, I don't get it. Your question, can you repeat it?

Of course, Professor. How would you structure a course on computational modeling for advanced engineering students? Specifically, how would you balance teaching theoretical concepts with hands-on laboratory applications?

Yeah, I think you are asking in the sense of means how to balance our teaching with the computational MA modeling. Uh, am I right?

Should I explain in that manner?

Yeah.

Yeah, tell me.

Uh, actually, uh, can you one, one more time repeat, uh, your last question?

Certainly, Professor. How would you structure a course on computational modeling for advanced engineering students? Specifically, how would you balance teaching the theoretical concepts with practical, hands-on laboratory applications?

Yeah. Uh, actually, uh, in teaching point of view, like, uh, we have journal use of many theoretical concept and, uh, many theoretical methods, uh, like finite element modeling methods, we have used in the, uh, theoretical point of view, like, uh, one of the structure, that structure we have divided into different number of element and we have found, uh, stiffness of each element and find the global stiffness of overall structure and.

Some boundary conditions related to the our practical application. Suppose we have a cantilever beam and if we want like find the deflection and slope of that cantilever beam, then that cantilever beam theoretically we can find why the formula of strength of material based on the elasticity along with for proper visualization, we can also model that cantilever beam in the computational software using the computational.

Such as the licenses software and software using the finite element method and apply some boundary condition like one end is fixed of the cantilever beam and apply some load at the other free end or any point on the cantilever beam. Then we can also see how that cantilever beam is subjected to that load hand due to that load, how that cantilever beam is deflected and how much is surface generated and how it is vibrating.

These all things we can also done in the computational modeling, uh, applying the theoretical concepts and we can validate our computational modeling result with a theoretical result by applying that we have opted by applying the simple theory of the strength of material to find a safe slope and deflection for the point load. Uh, in that manner, we can relate our theoretical concept with the live computational concept.

Thank you, Professor. Your explanation effectively ties theoretical concepts like elasticity and strength of materials to practical computational modeling through tools like finite element software. Next, let us discuss your experience in student evaluation. Can you describe how you have previously assessed student performance in both theoretical subjects and laboratory-based courses?

Uh, I have a previous experience so of teaching of subject like strength of material. And, uh, also, uh, I have teach like chorizo machine, mas machine, the subject, uh, but before, like, uh, when I have teach for three months and also I have, uh, teach for some period of engineering mechanics that subject, I have a experience for future.

Understood, Professor. You have experience teaching theoretical subjects like strength of materials and engineering mechanics. How did you assess the students in those courses—did you use written exams, assignments, or any practical demonstrations?

Yeah. Uh, like, uh, for, for the focus of student and for complete knowledge of the student, uh, we need to, uh, like conduct, like Smith theoretical classes along with the assignment and practical demonstration of, uh, uh, some of the, uh, practical application that we have teach in the theoretical classes. And also we can assign some project for small problem to uh.

Deeply understand the knowledge of theoretical subject means how students get our concept and how it is available to applied strategical concept to the practical application, uh, on the basis of project basis. And we can also give some projects related to the, uh, finite element modeling, uh, finite element modeling, umm, and we can validate that, uh, project on the theoretical point of view in that manner means we can do all three, uh, portions simultaneously.

Like uh, theoretical concept as well as our assignment, practical assignment and numerical assignment and project based study of some specific problem.

Thank you, Professor. Combining theoretical instruction, assignments, practical demonstrations, and project-based evaluations is a comprehensive approach to assessing students’ understanding and application of concepts. Moving forward, could you describe how you have guided student research or projects in the past? What steps did you follow to mentor students effectively?

Yeah, to guide the student in the visa's point of view. So first we have selected some uh, topics, uh, practical application topics, which is related to our, uh, related to the subject means that that's where I have teach in the classes. And based on that, based on the application of that theory, uh, I have assigned some research project to the student, uh, including the analytical modeling. Of debt problem along with your finite element, finite element modeling and if it's finite element modeling is validated with analytical modeling, then we will guide 2 students to conduct some prototype testing on that project. So in that manner like analytical as well as finite element modeling in the final phase, experiment testing, audit project on that problem or any project. So this is the way to guide guide the student in the research field.

Thank you, Professor. Guiding students through analytical modeling, computational validation, and eventually prototype testing establishes a well-structured research methodology. On to another critical skill: Communication. How do you ensure that your teaching approach is structured, clear, and engaging for students of varying levels of understanding?

I'm sorry, I don't get your point. Can you repeat?

Of course, Professor. How do you ensure that your teaching approach is clear, well-structured, and engaging, especially for students who might have different levels of understanding?

Yeah, uh means uh, our approach is to 1st, uh, teach, insert, teach the student to the basics of the theoretical subject. Because uh, the practical problem is solved via solved based on the basics of theory. So first we need to explain umm, basics of all the theory uh, related to the core branches or core subject. And UH-2 test means how student is gated our theoretical point. So uh assign.

Medical problem, uh, by giving some small, small, uh, problem which is related to the practical application. And based on that sorry point, uh, student try to solve that numerical problem. If it able to solve this numerical problem, then they define definitely, uh, apply that theory concept for the different practical application problem. Because, uh, every practical application problem is, uh, depend on the basics of. Basics of the core subject.

So first tease the seriop core subject and apply that theory for resolving of numerical problems and based apply that numerical problem to some practical applications problem based on the like analytical modeling and also numerical modeling as well as in the final stage we can demonstrate.

The core subject. So that is the approach that I have lived to teach that student.

By developing some small small types of experiment to clearly understand.

Thank you, Professor. Your approach to building a foundation with theoretical basics, progressing through problem-solving, and culminating in practical demonstrations is both structured and effective for engaging students at different levels of understanding. Let’s now discuss your research publications. Could you briefly highlight the focus areas of your four SCI journal papers and how they contribute to advancements in computational modeling or materials science?

Yeah. Uh, in our four SCI papers, I have mostly developed like optimum design of elastomer based, uh, sock isolation system for a particular novel application. So do I have, I have study, I have done case study by using the five elastomer material, uh, which are known by polychloropine, never hydrogenated nitrile, butyl rubber and natural rubber.

Along with polyurethane and Salvatore. So based on these five elastomer material by considering its nonlinear elastic properties with disclosure properties, I have optimally optimum design, uh, that stock isolation system for a particular case study of naval applications. So in that in our research, I have done analytical modeling as well as computational modeling of elastomer material. For circle load application.

And I have conduct some material testing material experimental test on the elastomer material to model a cyber elastic and viscoelastic property and allow me to biliary is hyper elastic and viscoelastic model to its experimental uniaxial, tensile and compressive test data, equiaxial test data along with your planar and static relaxation test data. And my last recent publication is related to the. Development of deep neural network.

App development to deepen neutral network for hypoelastic modeling of low damping elastomer material. So that model is specifically developed for the organ 3rd order model. In that paper I have generated the data set based on the computational modeling using the finite element software. That is Abacus and after that I have validate our developed neural network model with the experimental.

Uniaxial tensile and compression test data, and along with UH, I have also validated that model for UH dimension, geometrical independent and temperature independent properties by using its corresponding experimental test. So my 4th SCI general papers included analytical modeling as well as computational modeling and some experimental material testing.

Hypolastic material modeling and optimum design of ISOC isolation system for a particular novel application. So these are my basically domain that I have focused in four SCI general papers.

Data and including of our deep neural network application for.

Yeah. Uh, I, I have involved uh, in my peer master's degree, one of the project, uh, which is the, one of the like research in BNRS industry, uh, for a finite element modeling of uh, rotor dynamic bearing and also our PSD work that I have related to the optimum design of elastone material, which is. Uh, primary objective of one of the project, which is sponsored by the DRD organization.

Thank you, Professor. Your contributions, covering optimal design, experimental validation, computational modeling, and neural network advancements for elastomer materials, demonstrate a strong depth in computational modeling and materials science. One final question: Have you been involved in any industry projects or consultancy work related to your research? If

Uh, and, uh, recently I have work on one of the DRDO project in the IIT Delhi, uh, which is also related to the design of low frequency metamaterial based vibrations of calculations system, uh, using artificial intelligence. So I have worked with three umm project. That project is funded by the Defense Organization of India. So I have experiment of that three project on working of that three project, Yeah.

Professor, to begin, could you share which specific computational modeling topic or course you find most rewarding to teach, and why?

Uh, do the analysis of vibration and shock analysis like in that way we can focus on the computational modeling.

Understood, Professor. It sounds like you emphasize teaching finite element modeling with a strong focus on practical applications, particularly in vibration and shock analysis for mechanical structures. Thank you for sharing. Let's proceed.

Thank you.

Dr. Dhakad, I’d like to discuss how your academic research connects with your teaching capability. Let’s focus on one of your projects: the "Design of Elastomer-based Shock Absorption System." Could you explain how you would teach key concepts from this research to undergraduate students, particularly those unfamiliar with this field?

Yeah. First, uh, I can teach like, uh, means how to model, uh, practical elastomer material means, however, uh, theoretical theories of, uh, uh, theoretical theory of strength of material is applied for elastic application and how we can extend its theoretical application to its non-linear elastic range. And, uh, based on that understanding, umm, we can.

Our

Umm, go for our research. Practical application research means how their theoretical theory and theoretical concept began use. To model our practical elastomer material and how we can use that elastomer material, uh, to manufacture, to made a component which is responsible for shock mitigation as well as, uh, vibration mitigation. So step-by-step, first we can teach theoretical concept of based on the elastic story. And after that we can, uh, try to extend that elastic knowledge to nonlinear elastic knowledge. And I can give some.

Guide guidance or some? Ideas to the student how these nonlinear elastic or elastic story used to model our practical elastomer material or any material like elastic material is mild material and how that material is used for practical application for soft loading as well as vibration loading. So these are some basics that I can teach to the student from the beginning of theoretical theory to the end of practical applications so.

If we if I can go step by step like suratical theories and it's a finite element modeling and computational modeling and it's a application of practical point, then I thought a student can easily understand the concept of computational modeling.

And theoretical concept to apply practical application.

Thank you, Professor. That approach of starting with theoretical foundations and gradually moving towards finite element modeling and practical applications certainly demonstrates a structured methodology for effective teaching. A follow-up: For students grappling with the complexities of finite element modeling in nonlinear elastic materials, how would you ensure comprehension and engagement, especially if they have limited background knowledge in advanced computational methods?

Yeah. Uh, in that case we can try to, uh, explain simple non linear elastic model. Uh, that model is, uh, advancement of, uh, elastic theory. So we can try to relate how elastic story is extended to non linear elastic story and, uh, how to, uh, use some, uh, computational software and.

Net element software and two application of debt theories and how to apply debt theories and its computational application to the practical point of view. So by conducting some visualize by conducting some computational modeling of particular problem and step-by-step explaining how that model B can generated, how we can apply our theoretical concept to develop that.

Model and by giving some example of by applying some load and give the demonstration of visualization means how it is deformed, how stress has generated and how deflection has occurred. So in that manner means based on the visualization of computational model maybe student get some idea and get some knowledge of theoretical concept that can be applied for completion model.

Understood. Demonstrating computational modeling through step-by-step examples and visualizations is an excellent approach to connect theoretical concepts to practical understanding. Taking this one step further: how do you envision integrating findings from your advanced research, such as this shock absorption system, into designing projects or assessments that encourage creative problem-solving for students?

Sorry umm what you are trying to asking?

Can you repeat?

Certainly, Professor. How would you use insights from your research on the shock absorption system to design student projects or assessments? Specifically, how would you encourage students to apply creative problem-solving in developing their own solutions for similar real-world challenges?