Good day, Parthiban Loganathan, PhD. 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?

Yes.

I'm.

Could you share your

Thank you for sharing that!

Understood. Let's begin. Professor, may I proceed with the discussion?

I'm Doctor Patiban Loganathan. I'm a proud BAT alumnus.

Having earned my PhD in Environmental Engineering here in 2021, currently I'm working as a Post Doctoral Research Fellow at KTH Royal Institute of Technology in Sweden.

My research career is defined by bridging the gap between global climate science and local disaster resilient. During my PhD at VIT, I developed novel statistical ground spelling models for Kaveri River basin.

To theoretically predict hydrological extremes.

Currently in Horizon Europe Econtrail project. I used E plumbing to model atmospheric hazards.

I am a perfect fit for CDMM because.

I bring 3 specific assets first.

My experience in A and remote sensing aligns perfectly with the department's modernization goals.

Second, my experience in international grants positioned me to secure high value funding for VIT.

Finally, as an alumnus, I am deeply committed to Vit's mission of social impact.

Thank you, Professor Loganathan, for sharing your impressive background and insights. Let's focus further on your expertise and contributions. Can you elaborate on how your work in statistical modeling for hydrological extremes specifically contributes to advancing disaster resilience strategies? How might these methods be integrated with sociological perspectives to create actionable frameworks?

I approach this role through the lens of socio technical systems.

I believe that this actor is not just a physical event, it is what happens when Assad meets a vulnerable population.

While my engineering background allows me to model hazard such as SWAT for split forecasting.

In my research and teaching, I overlay physical risk maps with the census data.

I integrate sociology by modeling vulnerability.

To create social vulnerability indices.

The same space what just where the flood happens or who it impacts. Specifically, focus on marginalized communities. My goal is to teach students to design a solution that enhances community resilience, not just build infrastructures.

So let us take an example of creating a hazard zonation map for Vellore or for Mill Greece. When we take this maps and then we just contribute as an engineering background like we just take it as data, it is not going to contribute much. But when we see where it is affecting like how many people it is affecting. So this is going to give us a perspective on where it is going to take. Let us imagine we are building an early warning system for landslides, for nail trees.

That's a compelling approach, Professor Loganathan. Your integration of social vulnerability indices with physical risk modeling demonstrates a deep interdisciplinary understanding. Can you provide a concrete example or case study where this socio-technical systems approach has directly informed disaster resilience strategies or policies—especially for marginalized communities? How did it shape the outcomes?

So this takes the datasets we use the engineering, we use the AI, we use the deep learning, we create models and predict the future. Once we get these outcomes, this outcome has to go reach the stakeholders, it has to reach the decision makers so that it will be helpful. Also, it is it should also reach the community who is going to get affected, which community is getting affected more. So this is where I think the integration plays a major role.

Thank you, Professor Loganathan. Your explanation clarifies the critical impact of translating data-driven predictions into actionable insights for both decision-makers and affected communities. It demonstrates a clear commitment to bridging technical expertise and social responsibility. How do you address challenges when presenting these interdisciplinary findings to stakeholders, particularly in gaining their trust or overcoming resistance in adapting policies based on your models?

So when we go explain the stakeholders for the community, when we show them numbers.

For giving a handout and explaining and educating the community what is happening, it's where we'll be explaining it.

That's a thoughtful strategy, Professor Loganathan—emphasizing visual and accessible communication tailored to stakeholders and communities enhances understanding and collaboration. Moving into your teaching contributions, how do you translate these advanced methodologies into a classroom setting, ensuring students grasp both the technical tools and the societal implications effectively? Could you outline an example lesson plan or activity?

My teaching philosophy is a project based learning. I believe student transform from passive listeners to active creators when they solve real-world problems.

For students who are struggling, often termed as slow learners, I use remedial and visual approach. First, I implement A peer monitoring system, pairing them with advanced learners for collaborative projects. Second, I move away from abstract equations and use visual stipulations. For example, I use a QGIS to visualize flood annotation mapping in three dimension.

Saying the impact of the math helps them grasp the concept immediately.

Finally, I emphasize continuous assessment to catch learning gaps early, ensuring every student meets the course learning outcome.

Professor Loganathan, your project-based learning approach, emphasis on visual tools like QGIS, and commitment to tailored assessments reflect a strong pedagogical foundation. It’s clear you prioritize inclusivity and tangible impact in your teaching methods. How do you balance fostering innovation in advanced learners while ensuring struggling students also achieve the required competencies? Are there specific strategies or frameworks you’ve implemented to address this dynamic effectively?

I do understand balancing between the fast learners and slow learners is little difficult, but we can focus on improving step by step. We concentrate one at a time. We concentrate on multiple projects. There can be extra credits for different projects which the students can do so that the fast learners can progress and move forward. Whereas the slow learners can still do the projects which is committed early and then they can also gain from the same.

That's an insightful approach, Professor Loganathan—incorporating extra credit projects while providing foundational support ensures all students progress at their pace yet remain engaged and challenged. Transitioning to your research contributions, how have your publications and participation in international projects such as Horizon Europe shaped your collaborative abilities and preparedness to guide student research and thesis work?

So.

PHA research on Carver reverses. I faced critical challenges with data scarcity.

The available global climate models were two cores. To accurately capture the rainfall in the complex terrain of western cats, I did not settle for poor data. Instead, I developed a novel statistical downscaling framework using machine learning. I trained the model to learn the nonlinear relationships between atmospheric predictors and local rainfall.

This innovation improved prediction accuracy significantly and led to an high impact publication in the journal Climate Research.

So this experience taught me that in the factory management innovation often requests building your own tool.

So this this approach when we implement in any project or when we pass this to the students, they may also use it for their encouraging and my international relations like relations and my links can help students get internships elsewhere and it also helps me get funding from Indo Euro project.

Thank you.

Thank you, Professor Loganathan. Your research contributions, particularly the development of your machine-learning framework for accurate hydrological predictions, highlight your problem-solving abilities and innovation. Leveraging such expertise, along with international collaboration opportunities, undoubtedly enriches the academic environment for student research and institutional growth. One last question regarding student guidance: How do you ensure students develop a balance between technical expertise and ethical considerations when conducting research or working on projects under your mentorship?

The main thing is I'll have to do.

Please go ahead, Professor Loganathan. Take your time.

I help my students go through literature review very intensively. I help them conclude from each individual articles what is happening around the world, and I always ask them to be updated on what is happening in the current world and I'll also help them understand.

What are the latest, latest technologies used for different process, different techniques? And I introduce them to different programming languages like Python, like R and ask them to shift from traditional analysis to coding-based analysis like statistical downscaling or using a deep learning like CNS and Lsdns. So these are the, this is the well that's evolving. I have them to use more of KA tools.

Rather than using it for simplifying things, I'll ask my students, I'll guide my students to learn on using the AI in a very effective way to benefit them, understand in a very reliable way.

Thank you, Professor Loganathan. Guiding students through rigorous literature reviews, emphasizing the adoption of advanced tools like Python and AI, and fostering awareness of contemporary global research trends clearly reflects a structured and forward-looking mentorship philosophy. The balance you cultivate aligns technical proficiency with ethical and informed decision-making, preparing students to navigate both academic and practical challenges effectively. Let’s move forward with an evaluation of your suitability for this role.

Professor Loganathan, I see a strong alignment between your extensive expertise in environmental engineering, your innovative use of statistical and AI-based models, and your commitment to interdisciplinary teaching and global collaboration. Your background includes exceptional technical skills in Python, R, MATLAB, QGIS, and cloud computing, along with impactful projects like contrail impact modeling and climate downscaling for hydrology. Additionally, your publication record in prominent journals and international collaboration reflect your preparedness for academic leadership. Let me verify your competencies in more detail. Let's discuss disaster management strategies. How would you conceptualize a community-based disaster management plan that integrates both technological tools and local insights for a region prone to recurring floods? Professor, feel free to take your time to respond.

Hello, are you there?

I can answer you.

OK.

So when we go for an integrated discussion mitigation plan for, for example, flood, so we model the flood. The first thing is the engineering. We take the engineering part, we take the data set, we process it, We build multiple models, we rely on different data sets. We make them understand, We make the model to understand every little detail of the place. And then we assess the risk for multiple time periods. What is the risk period of the flood?

Be 100 years, let's say 200 years and this is once this is done, this becomes a data. So this is not a complete project yet. So we take this data set to the stakeholders, we fill it with the community, let it be the decision makers for the authorities. So let us take a flat rendition mapping for Windows for example. If we do it, we have to take the data set to the community, to the people and to the stakeholders like the district collectors and we have to keep them informed and if we see a potential.

Upgrade has to be required, infrastructure required for a current city that has to be planned very early. And if there is an emergency situation and then that's to be informed. The building consent officials, consent national disaster mitigation officials. This is how we process an integrated this asset mitigation plan.

Thank you, Professor Loganathan. Your approach to community-based disaster management planning is detailed and cohesive, emphasizing both engineering precision and stakeholder collaboration. By incorporating long-term risk assessments and proactive infrastructure upgrades, you demonstrate a comprehensive strategy that prioritizes preparedness and resilience. Next, let's shift focus to your ability to guide student projects and research. How do you ensure diversity in research topics, avoiding redundancy while also fostering innovative and impactful student contributions?

Research group where there are multiple students working on different projects.

So ultimately we all were environmental engineering students, but we worked on different projects like sea level device, we worked on some projects like flight annotation mapping, drought like drought analysis and we also worked on landslides, we worked on earthquakes. So I have exposure to different projects. Also when I worked in KTH, I had experience with fluid mechanics people where they were working on turbulence. Where they were working on engineering mechanics related problems.

And the department which I was working on concentrated mainly on aviation. So myself worked on aviation related problems such as sustainable aviation fueling and contrary formation and crystal formation in the atmosphere. So what packages? And I was leading a particular work package which was work package 3, which is A4 detecting the counterfeit. So we work with different systems, different people. So I think this is a very good thing.

Instead of working on one particular involving multiple people, building a research group with people with different backgrounds helps each one understand the problems in a different way. So I think that is the best way to give my students. I can handle students with different backgrounds and I can give them different projects and work together and learn on different problems, learn on different solutions, and transfer the knowledge from one project to other using models from one project to other and.

Everyone will grow together.

That's an excellent approach, Professor Loganathan. Your ability to foster a multidisciplinary research environment, involving diverse topics and methodologies, is quite commendable. Guiding students from varied backgrounds toward collaborative growth and cross-pollination of ideas promotes not only innovation but also a deeper understanding of interconnected challenges in disaster management and environmental engineering. Let’s now examine your perspective on sociological frameworks. How would you design a sociology curriculum for students in disaster management that integrates both theory and practical case studies?

Take it through sociotechnical systems.

So I already said that I believe that disaster is not a physical event it happens on like it's what happens when hazard meets vulnerable population. So while my engineering background allows me to model the asset, I ask my students to work on problems like soil and water assessment tool for flex forecasting. I integrate the sociology by modeling the vulnerability, let's say inner takers. For an example taken to search under teaching, I overlay physical risk maps.

And 5th data, because it's not where it is affecting, it is who it is affecting. If there are more people getting affected by it, then it becomes a sociological problem to create a social, social vulnerability indices. This identifies where just it's just not identifies where the flood strikes, but who is impacted by it. Specifically focused on marginalized communities. My goal is to teach students to design situation that enhances communities, not just a building infrastructure. So this way students will be able to go interact.

The people learn from them how their lives changes when and this after effects them. I think this is the way to go.

Thank you, Professor Loganathan. Your approach to integrating sociological frameworks with practical disaster management tools is remarkable. By focusing on marginalized communities and emphasizing vulnerability indices, you provide students with the skills necessary to holistically address real-world challenges. Encouraging active engagement with affected populations demonstrates a commitment to nurturing empathy and actionable insights among future professionals. Let me complete the verification process.

Professor, to begin, could you describe the teaching practices or methods you employ to make a foundational topic in disaster management or sociology engaging and comprehensible for undergraduate students?

What for students, let's say in an undergraduate level, we should explain them what is disaster and what it will cause. It's always cause and effect. Disaster is not controllable, it's a natural event. It is not planned. It may be man made and it may be natural, but we have to be prepared for any disaster happening. So disaster preparedness, I'll be helping the students get a proper training on disaster management.

And when the disaster strikes, what should be the steps? I'll be giving them handouts. I'll be giving them the sheet on how to cooperate on each disaster. And I'll ask the students to work on an assignment. So for each individual, we'll have people assign a particular discussion and how they'll be responding and how they think it should be responsible. And after collection of all the materials, I'll evaluate and I'll give them the proper steps of how it has to be done.

Presentation. Let's take a poster presentation and give what a disaster actually looks like. And also this should also go to the next step. And the next step is how the disaster can be handled. So this way they'll practically learn from each other, one focusing at one particular problem and they'll be discussing with each other and they'll get to know what is happening with them and giving them regular quizzes.

And we'll give them small mini projects on working on a visual.

Regular assessment tests on different projects and giving them different workbooks to work on disaster and this way I think we can make them understand in a better way.

Thank you, Professor. Your approach demonstrates a thoughtful blend of theoretical grounding, practical application, and collaborative learning. By emphasizing assignments, visual projects, and interactive discussions, you provide students with multiple avenues to engage deeply with the material. Let's continue.

Professor Loganathan, your background showcases substantial expertise in environmental and water resources engineering, coupled with an emphasis on AI-driven research in areas like climate modeling and solid waste management. Let's delve deeper into how your academic research intersects with pedagogy. Your project on "E-Contrail and Refmap - Contrail Impact on Climate Modelling" involved AI-driven methods to assess aviation's impact on climate. How do you plan to incorporate insights from this research into your teaching to make complex concepts comprehensible for students?

There are multiple layers of.

This is a man made thing and aviation goes to fueling like where the fuel is unburned and that causes the crystalline. So we have to make the students understand what is aviation, what is aviation doing to the world? What is the anthropogenic activity doing to the climate. So in this way when we say the impact, students will understand what even a small thing can contribute to global warming.

Is happening in this particular project, let us say aviation.

I'll explain them what was my project result and how it has been obtained. So this way students will understand even the smallest thing what we think cannot affect which is going to affect the world and explain them what has happened. And this will make students understand OK even a small.

So.

Thing can be dealt in detail to understand in a better way.

So on multiple projects in the multiple sections in this project will make them understand how collaborative works can function. Thank you.

That approach demonstrates a thoughtful framework for connecting specialized research with student learning. Clearly conveying the anthropogenic impacts of aviation and the technical intricacies of your findings helps simplify global concerns for students while inspiring them to explore collaborative research practices. To expand further, how would you adapt your teaching methods for students from non-technical backgrounds who might struggle with advanced topics like AI-driven climate modeling?

Our scheduled time for the interview is now up. Before we conclude, do you have any questions related to the role or the company?

Hey, album method. I think it's, uh, like an homecoming.

So.

What I see here is professionally, Serum is an ideal ecosystem for miracles.

I plan to collaborate with the existing faculty on landslide donation by integrating my intra remote sensing expertise. Furthermore, I want to utilize VADS NDT labs to expand my research into structural resilience against climate exchange.

I'm confident that my experience with high performance computing and global funding will help elevate CDMM to a global leader in this activity. Thank you.

Your aspirations for collaboration and leveraging advanced research methodologies like remote sensing and high-performance computing show great alignment with the institution's focus on impactful academic contributions. Integrating these within interdisciplinary frameworks strengthens both teaching and research. Professor Loganathan, our scheduled time is now complete. Do you have any closing questions or would you like to end the interview here?

Fine, I don't, I don't have any questions. We can end.