Good day, Dr. Afzal Hussain. 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?

Yeah, this is Doctor Abdulrahman here. Actually since graduation to post doc, I have completed in bioinformatics field and I am having teaching experience as well as research experience in the bioinformatics field. And I am having high impact publications in bioinformatics field as well as I have been teaching experience like Python, Biopython, machine learning fields. So which can increase the bioinformatics domain and give the knowledge to the students in the best way.

Please

Yes, good afternoon.

Thank you, Professor Abdulrahman, for sharing your background. It’s appreciated.

Professor Hussain, let's delve into the skills required for this position. I'll assess each skill area individually, so let's begin. First, regarding your expertise in Cancer Bioinformatics: could you outline your approach or methodology for identifying novel anti-cancer agents using computational systems?

Yeah. First of all, we have to go for the if the PDB structure is not available, we can get the faster sequence, we can model the protein structure. After that we are having a huge library of the drug databases like drug bank and NCI databases. We can screen all the molecules at a time very fast against the target protein. And after that we can go for the molecular simulation work. We can find out the stability of this molecule, this inhibitor inside the cavity of.

Target protein so and after that we can like analyze admit properties and other toxicity analysis.

Yeah, We can go for the Ramchandran plot analysis. We can go using the project, we can find out the residues which we model the protein structure. The residues are inside this Ramachandran plot or node. So we can if the residues are outside, we can model the residue like loop refinement and other techniques we can use to model a particular protein structure and the right way.

That was an insightful explanation, Professor. How do you ensure the protein models you generate are accurate and reliable when the PDB structure is unavailable?

Understood. Thank you for that clarification. Now, considering your teaching experience, can you explain how you approach designing and delivering both theory and laboratory bioinformatics courses for students?

Yeah, actually I have an extensive teaching experience in the bioinformatics field. I worked as an assistant professor in the top ranking university in India. So during during my class decision, I am taking an example of like real-time databases and how to use using coding. I can like I can teach the students in the best way. How can we implement the project. So this is my methodology. First we have to give the theoretical knowledge parallelly we have to give the.

So we can enhance the skills of the student using this must techniques.

Thank you, Professor. Could you elaborate on how you assess whether students have effectively grasped both the theoretical and practical aspects of your courses?

Yeah, sometimes, uh, in the, in the laboratory, we are giving a small, small, uh, a small coding, coding, coding assignments. And we can see the what kind of assignment they are able to do. We are taking the feedback from the students, they are able to do this kind of things or not. After that we are approaching, we are giving the scores and we are giving the real time data sets also to find out that.

The students are doing well or not, and we are just seeing the students that they are doing, uh, doing the in the right way or not. So like this.

Thank you for the detailed explanation, Professor. Now moving to your responsibilities for student evaluation and exam duties: could you detail the strategies you use to design fair but challenging assessments for students in bioinformatics?

Yeah, actually we are giving the logical questions to the students not like the like theory questions. We are giving the logical questions how they are handling the logical question proficiently. So according to that we can find out the the our like our teaching impact on the students and how they are solving their questions in the right way or not.

Because in the like and when I am going to join as an assistant professor in the bioinformatics field. So I am taking the questions from the different bioinformatics aspects and after that we are we are giving the like, we are giving the questions like theory plus practical. So we can see the students are doing well or not in this both the way and they are able to think logically and practically.

How do you ensure that the logical questions you set align with both the curriculum goals and the varying skill levels of your students?

Understood, Professor Hussain. Now, regarding guiding students in projects and research: can you describe your approach to mentoring students through the various phases of a research project?

Yeah, actually I'm doing extensive work in the bibliometric analysis. So we can find out so many sources, so many bibliographic data sets are there like Scopus, Web of Science. So after doing bibliometric analysis, we can find out which topic is more relevant and bus we can do the bust analysis. After that we can teach, we can say the student to find out the. Most recent article published in this. According to that we can like implement a project.

We can tease the practical skills to the students. How can they, uh, they do properly this type of research 1st and uh, whenever I am taking the feedback, I am taking the assignment, I can find out the, uh, the, uh, the uh, students are doing well or not.

Like this?

Thank you for sharing your process. How do you handle challenges when students encounter difficulties, either in defining a research problem or during the execution phase of their projects?

Yeah, actually we are having uh, during like whenever I am uh, joining as an assistant professor, we are having tie up with the different laboratories. We are having tie up with the industrial person also. And I am also expert and extensive experience in the bioinformatics field. So whenever the student is facing some problem in their project work, I can teach the students, I can enhance the skills of the student and we can also.

Also, hire the industrial person to give the extensive knowledge to the students in their project works.

Yeah.

Thank you,

Yeah, whenever we are delivering A bioinformatics concept. So during the session, during my lecture, I am just putting different, different small query in front of the students and I want to take the right answer. I'm just assuming the right answer from the students. Then I am giving assignment also to the student and finding out and evaluating the students proficiency. Are they able to understand the concept or not. According to Ted, I am just continuing my class.

Let's discuss effective communication and structured teaching. Can you describe how you ensure clarity and engagement when presenting complex bioinformatics concepts to a diverse student audience?

Actually we are making a evolution program. We are just giving the, we are just delivering the complex problem and we are just taking, we are just seeing the students are able to perform or not and we can also take the extra classes if they are not able to perform well. So according to that the merging evolutions we can enhance the knowledge and we can deliver the best lectures, best practical knowledge to the students.

Thank you, Professor Hussain. When you notice students struggling to grasp certain complex subjects, how do you adjust your teaching methods to better meet their needs?

Understood. Moving on to research publications: can you highlight a specific publication of yours in a reputed journal and explain how it contributes to the field of cancer bioinformatics?

In the cancer bioinformatics field, I am having high impact publications in the European general of medicinal chemistry which is the impact factor in like 6 point something and it is having Q1 publication and arrive in general of medical chemistry also is having 6 impact factor publications and I am having around 40 plus publication which is high-infect journals and I'm continuing publication and which is relevant only the cancer because my.

Is cancelled, so I'm working on that.

Thank you, Professor. Could you elaborate on one of your research findings in these publications and its implications for advancing cancer treatment or understanding?

Yeah, we can see several uh, publications on the cancer, uh, inhibitor finding out in my PS3 I worked on to find out different agonists, we can find out different inhibitor against the cancer target proteins. So after that, uh, we are using different kinds of library. We are doing extensive molecular simulation works to find out the most. Potent inhibitor against the cancer protein as well as.

I worked on next generation sequence data analysis to find out the differential gene expression between tumor and non tumor cells. So like via this I can perform well. I performed well to find out the inhibitor to finding out different types of drugs molecules, novel drugs molecule against the cancer protein to inhibit it.

Yeah.

Actually, I worked, uh, during my, like, uh, during my GRF junior research fellowship, I worked on the cancer proteins in the, it is funded by the department of biotechnology. So we have established different, we have find out different cancer molecules. After that, I completed PSD in bioinformatics where I were designed so many molecules against the cancer. It is funded by UGC. And after that I have written a project which is funded by Indian Council of Medical Research.

Thank you, Professor Hussain. Now, regarding your experience in industry projects or consultancy: could you share an example of a project or consultancy you were involved in and its relevance to cancer bioinformatics?

Take we are we are writing the proposal and we are getting the grant and now I am working in the the National University of Malaysia which QS ranking 1/26 and I'm extensively working in this and we are having collaborating with different universities and they are granting projects because of our skills.

So we are.

Thank you, Professor Hussain. Given your extensive experiences, how do you ensure that collaboration with industrial partners or research institutions leads to meaningful outcomes, both academically and practically?

Yeah, in academic year, practically the collaboration is very important. Academically we can go for the workshop, we can write publications together. So the publication goes high. The impact to which we are getting for the publications, we will get the high impact publication in this area. Because nowadays the genders need the collaboration, collaborative work, different fundings they want and different collaborations. So it will give the impact of the.

Publication and industry also we can tie up with the industry likes in the bioinformatics we are working on the in silicover we can tie up with the industrial person to do the clinical work. So if the transparency of the work is very needed for developing the community.

Professor, to begin, could you describe a foundational concept or course in cancer genomics that you particularly enjoy teaching, and why?

Yeah, in the cancer bioinformatics, I can teach the cancer G.

Transcriptomics, proteomics, angios and Ai-driven technologies because nowadays like whenever I am working on the field of cancer bioinformatics, we need a best method to find out the cancer like.

Few clinical trials, so yeah.

Yes.

Thank you for sharing that. It seems like you're focused on integrating advanced technologies in cancer

Yes, we are integrating different technology, cancer genomics, transcriptomics, proteomics, we are merging together.

That’s a vital and interdisciplinary approach, Professor. Let us delve deeper into your research experience. Your PhD focused on computational studies on protein targets involved in cancer progression and the in-silico identification of novel anti-cancer agents. Could you elaborate on one key challenge you faced during this research and how you overcame it?

Yeah, during this research, because the so many, uh, compound libraries are there, the key challenge is how to import, how to, uh, like how to evaluate all the cancerous proteins.

Answer library, how to go for the molecular simulations work, So the extensive molecular simulations work. So during this we need a big computers, we can say the workstations do well during the studies, yeah.

I see, the scale of computational resources and the extensive evaluation of compound libraries must have been demanding. How did you tailor your computational workflows or utilize available tools to manage these large datasets efficiently? Specifically, were there particular software or strategies that proved instrumental?

Yeah, yeah. Actually I am working using different software. I use PIMO, I use Auto Dog, I use Mastro Schrodinger software. I use the open source grommets tools to like merging all the datasets and finding out the best result among this.

Understood. Merging datasets effectively and using a combination of proprietary and open-source tools clearly highlights your strategic approach. Now, transitioning to pedagogy, considering this level of complexity in cancer bioinformatics research, how would you adapt these advanced concepts and workflows for students at the undergraduate level to ensure clarity and engagement?

Actually in this, in this world, we are like, uh, according to my experience, we are moving towards the AI driven bioinformatics approach. So we can develop the different, uh, machine learning model based on the data sets. And during the training and test session, we can find out which particular machine learning model is doing well. According to that, we are taking the new data sets and we are evaluating that, we are comparing that.

Our model is doing in the right way or not and after that we are getting the final result and we can do the cross check analysis, cross validations of our data set. So we can move towards like this.

Interesting. So, you're integrating AI-driven approaches and machine learning into bioinformatics, which is both modern and impactful. For undergraduate students, how would you simplify this methodology to introduce the foundational principles of machine learning in bioinformatics while keeping it practically engaging for them? How would you structure such a course or module?

Actually I am working in the bank as an assistant professor in bioinformatics in lovely professional university. During that time also I am just taking the classes of machine learning and artificial intelligence. I'm giving the practical knowledge inside the campus, inside my cabin. I'm just giving that how to do a small small practical example of the Python programming. After that we are taking the small set of.

The data set, we are just evaluating our machine learning model based on the data set. So likewise, I am giving the practical knowledge during uh simultaneously with the theoretical knowledge to the students to develop the skills, how to use the tools and techniques, how to implement the techniques for the better, uh, for getting the result and enhance their knowledge.

It’s commendable that you’re integrating hands-on practical sessions with theoretical knowledge, using Python and small datasets to engage students with machine learning in bioinformatics. That approach likely helps bridge the gap between abstract concepts and real-world application effectively. Before we move on, how do you ensure that students with diverse academic backgrounds or varying levels of programming proficiency succeed in your classes?

Hence which background they are coming and they are MA. We are just looking for their their knowledge in the mathematics. Also because the programming needs mathematics, we are giving the calculations to the students and we can see how the students are performing well in the mathematics. After that we are just.

Actually we are just looking for the.

Uh, writing some commands. We are giving another example, another exercise to the students to, to, to do coding on the basis of our giving example. If they are doing well, it's good. If they are not doing well, we are just giving the assignments to the student so they can enhance their knowledge likewise.

It's excellent that you're assessing their foundational mathematics and guiding them through incremental tasks, from basic exercises to assignments. This structured approach ensures that all students, regardless of their starting point, have the opportunity to bridge their skill gaps. I’ll note your emphasis on combining conceptual understanding with practical application for student success. Now let’s proceed.

Yes.

Thank you, Professor Hussain. Let’s delve into your research prospects. Could you outline a three-year research roadmap focusing on your work in Cancer Bioinformatics, particularly how you envision it contributing to institutional research goals and advancing scientific understanding in this domain?

So because of that we are just I worked on the different cancer proteins and finding out the difference inhibitor using bioinformatic extensia approach and I used the next generation sequencing data analysis, worked on the cancer target gene expression analysis. But now I am thinking to merge all the.

Sorry to interrupt, we're down to the last 5 minutes.

Techniques like genomics, proteomics, transcriptomics and after that we can give the good idea, we can find out the biomarkers so we can inhibit the cancer protein and it is also giving the transparency how to do it.

Actually because of this we are having different kinds of data, different kinds of data, some sometimes the data is missing, so we have to replace with the mean value, we have to normalize the data, we have to scalar the data. After that we have to generate the different type of machine learning model. So I am just trying to tease the student how to use this tech needs this normal techniques nowadays. How can we model the structure and how can we? We fill up the gaps of the missing value. We have to preprove how to preprocess the data.

That's a promising direction, Professor Hussain. As you aim to integrate genomics, proteomics, and transcriptomics for biomarker discovery, how do you plan to scale your lab to mentor junior researchers and ensure a steady output of quality publications while pursuing such an ambitious goal?

Which is very important whenever we are combining those different genomics, transcriptome and proteomics techniques.

Actually during my PhD and postdoctoral after that I am selected in different laboratories like in Russia, in uh, Saudi Arabia, I have worked in assistant professor, I worked in the lovely professional university and I am now I am working in the National University of Malaysia, which is QS ranking 126. So I am working with different professor, different laboratories so we can work together to give high impact publications.

Understood. Providing students with strong foundations in data preprocessing and machine learning is indeed crucial. On the subject of amplifying your research impact, how do you plan to leverage international collaborations to boost citation metrics and elevate the global visibility of your work in Cancer Bioinformatics?

Thank you for sharing that, Professor Hussain. I believe we have covered this section comprehensively. Let us proceed.

Yes.

Traditional lectures like we are coming and we are giving the theoretical knowledge but but in my perspective, I will give the theoretical plus during the session. Practical knowledge is also there giving the practical assignment, giving the practical assignment, practical logical assignment and we can ask the student they are performing well or not. If they are not performing well, we are taking the extra time to give to the student to make it.

Professor, could you explain in detail how you would implement an active learning model, such as a flipped classroom, for a large-enrollment course? Please specifically address how you would design this approach without relying on traditional lecture slides.

Accessible.

Actually, I will give the assignment to the student. I'm making different different groups of the student. I am giving the giving the problem and I'm trying to find out the solution. So because if they are like working in the group, they can communicate with each other, they can enhance knowledge. If some students doesn't know something, they can interact with each other and they can also enhance their knowledge, their practical knowledge. So I just I'm just increasing the knowledge of all the student notes that only the higher student.

Understood, Professor. While combining theoretical and practical components is valuable, could you elaborate on how you would apply this strategy specifically within the framework of a flipped classroom for a large-enrollment course? For instance, how would you distribute learning resources beforehand, and what specific activities would you conduct during class time to actively engage students?

Practical plus theoretical knowledge.

I see, Professor. Thank you for that explanation. Now, how would you design appropriate evaluation tools for this method to measure the actual competency of the students? Specifically,

Yeah.

Yeah, I will give you a practical knowledge plus theoretical knowledge. And I'm getting the giving the marks based on the practical and theoretical knowledge and calculate that the students is getting more impractical or they are getting more theoretical.

Understood, Professor. Thank you for sharing your perspective on student evaluation. Let's proceed.

Yeah, for the before they would.

Professor Hussain, considering your extensive background in computational studies in Cancer Bioinformatics and your role in significant research projects, I want to focus now on your approach to institutional contribution and building metrics for accreditation. Could you systematically outline how you would improve the "Research per Faculty" metric of a department to meet high accreditation standards?

Within the faculty.

Yeah, I have written different projects and I'm getting funding. I have received the funding from the different institute in the Malaysia also USM University. I like I was selected in the India also IGIVI was selected as the scientist force. So I am just writing the project based on the novel methodology and I am getting a chance to enhance my knowledge in this period.

Yeah.

Yeah, I am making the timelines of the projects like if I am putting I'm giving time to the project for sending the Funding Agency and getting the projects and how to run the project in the in the time voice. So I am just putting the timeline and based on the timeline I'm working on that.

Thank you, Professor. How do you balance the administrative workload of securing funding and managing projects with maintaining high-quality research output in your field of Cancer Bioinformatics? Could you share some specific practices or approaches?

Thank you for sharing that, Professor. Lastly, can you provide an example of your experience leading an internal committee or task force that directly contributed to the success of a quality audit or accreditation in your previous roles?

Yeah, in the previous I worked in assistant professor and lovely professional university. So every week we are communicating things and the PhD evaluations meeting so and the difference like how curriculum development and different types of projects development and discussing about the pattern so.

Likewise, we are just developing all the things.

Thank you, Professor Hussain. I appreciate the specific examples you’ve provided about your roles and contributions. Let us move forward.

First of all, I will talk with the students. First of all, it won't happen. But if this is happening, we are just taking the like we are just making an committee and according to the committee, we just talked with the students. What is the problem he or she is facing? According to Tech, we are like you're putting the comments and after that comments we are like, again, we are evaluating the student. If the some same problem is coming, then we can take other chances like. We will involve his or her family and we will talk with them because we don't want to, uh, put the pressure on the student. We just want to work for the students.

Professor, let's begin with a scenario for discussion. Imagine you are faced with an allegation from a student who accuses you of grading bias. This accusation arises while the institution is simultaneously under pressure to meet its pass-percentage goals. How would you handle this situation?

Yeah, if, if I am like, whenever we are teaching the student, we should engage ourselves with all the students, not the specific students. Sometimes the students think that they are talking with us more and we are not talking with me. So we should we should should interact with all the students inside the class and we just listen them. The main property of the main characteristic of the professor should be to listen properly for the to the from the students so we can.

Understood, Professor. But how would you ensure that your actions maintain both fairness to the student and uphold institutional standards, especially in the context of grading integrity?

Like we can, we can solve, solve the problems of this students, yeah.

Thank you. Lastly, imagine a situation where, during a public committee meeting, your viewpoint on an important policy issue directly conflicts with the leadership's stance. How would you handle this professional disagreement in the forum?

Time is up! Ending the interview now.