I am positively inquisitive and optimistic by nature. I believe learning is an ever-enriching process, so I never stop teaching myself new things—both on the professional and personal front. Design is a service that cannot be discipline specific, but as an individual, textile design is my area of interest and expertise. I also feel a good work-life balance is important for the long run. I had been involved in a startup venture of designing and manufacturing handloom textiles in West Bengal between 2017 and 2020. This was a huge learning experience for me because we were handling everything from scratch to the final retailing of the products. In 2022 while working with Urban Ladder, Bangalore, I conducted a research on the upholstery preferences of the Indian customers. It involved travelling to 5 major cities in India and taking personal interviews with prior appointments with them to understand why people buy what they buy. The research findings were assimilated and analyzed for insights and actionables. Design Thinking and Foundation Modules excite me a lot at present and I am majorly involved with the same at RV University. I have worked in the industry for 11 years after completing my master’s degree from NID, and academia seemed to be a natural calling after a point. I am glad I have chosen this path.
Tanmoy Goswami is an Electronics and Instrumentation Engineer turned television professional whose journey into cinema has been no less cinematic.
Born in the early ’90s into a Bengali family deeply rooted in Indian classical music and Bengali literature, Tanmoy’s creative inclinations were nurtured from a young age. His early interest in painting and analog photography naturally evolved into a passion for creative writing during his college years, eventually leading him to mainstream filmmaking.
With nearly 14 years in the television industry, Tanmoy has worked with some of the most prestigious names—Viacom18, Disney Star, Zee, and more. He has been involved in over 25 soap operas and 3,000+ episodes, serving as a writer, director, and creative producer. He also briefly held the position of Senior Manager – Station Programming at Radio Mirchi.
Tanmoy has also actively contributed to academia, mentoring aspiring filmmakers through hands-on workshops and innovative teaching methodologies. He has served as a visiting faculty in the department of Media Science & Journalism , Brainware University, Kolkata ( 2021-2024) and in the department of Film and Television , Inspiria Knowledge Campus ( 2020 – 2021) , Siliguri , West Bengal and a in a number of film schools across India as well.
Prof. (Dr.) Shailja Beniwal is currently designated in School of Law (SOL) with a rich academic background spanning Criminal Science and law, Forensic Science, Cyber Law and Psychology accreditation expertise with extensive research and teaching experience, she brings 16 years of commitment to higher education.
As a regular visiting Faculty training in Police Academy India, Dr. Beniwal imparts training to Police Officers – ASP (IPS), Dy.SP and Public Prosecutors on Criminal Laws and Criminal Justice.
With maintaining her culture of excellence, she bridges the gap between enforcement agencies and academia, fostering collaborations and nurturing the next generation for career in Criminal Justice.
Dr. Beniwal has held prominent academic leadership roles as overall Discipline in-charge and Self-Defense training with her high performance culture and creativity.
Dr. Beniwal has a strong research intellect in Criminal Laws, Positive Criminology and Criminal Psychology. She has presented her research at various international platforms in UN Convention Geneva Switzerland, Sweden, Norway, Australia and New Zealand as a best paper presenter, seasoned keynote speaker, chairperson and reviewer for esteemed journals.
As an accomplished author, Dr. Beniwal has published her research papers in reputed academic journals and five books on Criminal Laws and Environment Science. She also writes for national print media extensively on Environment and community concern issues.
Dr. Rashmi S
Professor, School of Computer Science and Engineering
RV University, Bengaluru
Dr. Rashmi S is an academician and researcher with over two decades of experience in teaching, research, and academic leadership. She holds a Ph.D. in Computer Science and Engineering with a specialization in Cloud Computing and has contributed significantly to higher education through her commitment to research, innovation, and academic excellence.
Before joining RV University, she served as the Head of the Department of Computer Science and Engineering (Data Science), where she led several academic initiatives aimed at enhancing research culture, fostering interdisciplinary collaboration, and strengthening industry engagement. In her leadership capacity, she has also served as Chairperson of the Board of Studies (BOS) and Board of Examiners (BOE), actively contributing to curriculum design, academic governance, and examination reforms. She has also served as a research coordinator and member of academic committees, contributing to the overall academic governance and research initiatives of the department.
Dr. Rashmi is a recognized Ph.D. research supervisor and currently guides multiple doctoral scholars in emerging domains of computing. Her research interests include Cloud Computing, Artificial Intelligence, Data Science, Internet of Things, Blockchain, and Cybersecurity. She has authored and co-authored many papers in reputed national and international journals indexed in Scopus and SCI, and has contributed several book chapters published by leading academic publishers.
Her research contributions also extend to innovation and applied technologies, with patents filed in the fields of artificial intelligence, healthcare, and assistive technology. She has presented papers at various national and international conferences and has received accolades, including a Best Paper Award for her research on advanced image analysis techniques.
In addition to her academic and research achievements, Dr. Rashmi has been actively involved in industry–academia collaborations, establishing Centres of Excellence and promoting experiential learning through partnerships with technology organizations. She has also coordinated faculty development programs, symposia, and workshops focusing on emerging trends in computing and data-driven technologies.
An IEEE Senior Member, Dr. Rashmi continues to contribute as a reviewer, session chair, and member of organizing committees for national and international conferences. Through her dedication to academic leadership, research, and innovation, she remains deeply committed to empowering students and fostering excellence in the field of Computer Science and Engineering.
My academic journey has always been driven by curiosity about people at work — what motivates them, how they perform, and how organizations can support them better. Currently, I serve as an Assistant Professor in the area of Human Resource Management and Organizational Behavior. I hold a Ph.D. from the National Institute of Technology, Tiruchirappalli (NIT Trichy), where my research focused on understanding the performance dynamics of gig workers within the growing platform economy.
Before my doctoral studies, I earned an MBA in HR and OB from Kakatiya University, Warangal, and a B.Tech in Mining Engineering from IIT (BHU) Varanasi. This combination of technical and management education has helped me develop a balanced perspective that connects analytical thinking with human behavior.
My research has been published in Scopus and ABDC-listed journals, including Global Knowledge, Memory and Communication. I have presented my work at several national and international conferences, such as those organized by the National Academy of Psychology (NAOP) and NIT Trichy. I was also a visiting research scholar at the University of Missouri, Columbia (USA) under the SPARC project, where I explored how HRM practices impact gig workers’ well-being.
My academic interests include Digital HR, Talent Management, Job Design, Work Engagement, and Employee Performance. As a teacher and researcher, I strive to make learning meaningful by connecting theory with practice.
With a strong foundation in data science and applied artificial intelligence, I have been deeply engaged in exploring the intersection of analytics, automation, and intelligent systems. My work has involved developing AI-driven solutions for domains ranging from demand forecasting and business optimization to generative AI and autonomous research systems.
Before transitioning into academia, I worked on several data-centric projects that combined research and industry practices — from building predictive models and deep learning pipelines to integrating large language models (LLMs) for automation and decision support. My academic background includes a Master’s in Data Science, where I focused on bridging theoretical understanding with real-world problem-solving across image recognition, natural language processing, and multimodal analytics.
My current areas of research interest include generative AI, machine learning, and intelligent automation, with an emphasis on creating adaptive systems that enhance human decision-making, interpretability, and creativity. I am also interested in explainable AI (XAI) and its role in ensuring transparency and trust in deep learning models.
I have co-authored a publication titled “PCNN-based grape leaf disease detection using MobileNetV2 and ViT with XAI,” presented at the 5th International Conference on Data Science, Computation, and Security (IDSCS 2024) and published in Lecture Notes in Networks and Systems (Springer, SCOPUS Q4).
With a strong foundation in data science and applied artificial intelligence, I have been deeply engaged in exploring the intersection of analytics, automation, and intelligent systems. My work has involved developing AI-driven solutions for domains ranging from demand forecasting and business optimization to generative AI and autonomous research systems.
Before transitioning into academia, I worked on several data-centric projects that combined research and industry practices — from building predictive models and deep learning pipelines to integrating large language models (LLMs) for automation and decision support. My academic background includes a Master’s in Data Science, where I focused on bridging theoretical understanding with real-world problem-solving across image recognition, natural language processing, and multimodal analytics.
My current areas of research interest include generative AI, machine learning, and intelligent automation, with an emphasis on creating adaptive systems that enhance human decision-making, interpretability, and creativity. I am also interested in explainable AI (XAI) and its role in ensuring transparency and trust in deep learning models.
I have co-authored a publication titled “PCNN-based grape leaf disease detection using MobileNetV2 and ViT with XAI,” presented at the 5th International Conference on Data Science, Computation, and Security (IDSCS 2024) and published in Lecture Notes in Networks and Systems (Springer, SCOPUS Q4).
I’m Pranjul Shukla, a Computer Science professional driven by an enduring passion to explore and teach the answers born out of curiosity and logic. Having completed my Master of Computer Applications (MCA), I have developed strong expertise across Artificial Intelligence, Machine Learning, Deep Learning, and core programming languages such as C, C++, DSA and Python with core CS subjects.
My academic and project journey reflects my love for connecting theory with application. Notably, I developed a Driver Drowsiness Detection System that integrates CNN, OpenCV, and dlib—a project demonstrating both analytical depth and real-world relevance. I have also contributed to projects involving data analysis and intelligent automation, each designed to transform technical understanding into practical innovation.
As an educator, I strive to make Computer Science a subject of reasoning, not memorization. I take pride in simplifying complex concepts for students and inspiring them to approach technology as a language of problem-solving. My teaching focuses on helping learners build clarity, confidence, and creativity—qualities essential for future innovators.
Beyond teaching, I actively explore research in AI-based systems and continuously refine my pedagogy through student feedback, interdisciplinary learning, and emerging technologies. My ultimate goal is to nurture minds that think critically, code logically, and innovate meaningfully, bridging the gap between academic concepts and real-world impact.
Dr. Rekha Satish is a dedicated and passionate Mathematics educator with 18 years of teaching experience and over 3 years of corporate exposure. She earned her Ph.D. in Applied Mathematics (Fluid Dynamics) from REVA University, Bengaluru, where her research focused on the theoretical modeling and analysis of complex fluid flow systems. She also holds an M.Phil. in Mathematics from Bharathidasan University, Trichy, and an M.Sc. in Mathematics from Bangalore University.
Her teaching philosophy focuses on creating an engaging and approachable learning experience in Mathematics by simplifying complex concepts and connecting them to real-life applications. She strives to cultivate curiosity, confidence, and a genuine appreciation for the subject, inspiring students to view Mathematics not as a challenge but as a powerful and enjoyable tool for problem-solving.
Hello, I am Mythreyi S N. I am working as an Assistant Professor in the School of Computer Science and Engineering at RV University, Bengaluru. I have completed my Master of Computer Applications (MCA) from Jyothi Nivas College, Bengaluru. My areas of interest include Artificial Intelligence, Machine Learning, and Data Science. I have 2 years of teaching experience and am deeply committed to fostering a learning environment that bridges theoretical concepts with practical applications. My teaching philosophy focuses on encouraging critical thinking, innovation, and problem-solving among students to prepare them for the evolving landscape of technology. I aspire to contribute meaningfully to the field of computer science education through continuous learning and dedicated academic engagement.
