Ashutosh Madhukar Kulkarni
Biographic Data
| ID | 10254706 |
|---|---|
| NAME | Ashutosh Madhukar Kulkarni |
| GIVEN NAMES | Ashutosh Madhukar |
| FAMILY NAME | Kulkarni |
| SIGNATURE | KULKARNI A M |
| AFFILIATIONS | International Institute of Information Technology |
| VERIFIED | No |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Interactive Mixed-Reality Installations Combining Physical Materials With Advanced Digital Projection Techniques
Interactive mixed-reality (MR) installations represent a radically different variant of convergence of material objects with the latest methods of digital projection that creates immersive and interactive experiences in art. The current paper is an outline of the design and installation of MR installations that can harmoniously blend the material or tangible component of wood, metal, cloth and transparent media with the interactive dynamic projec…
Ai-Powered Music Therapy for Education
The artificial intelligence (AI) has offered new possibilities to improve the sphere of music therapy as the means of adaptive support within the educational settings. The traditional music therapy methods are useful but very stagnant and cannot be scaled and personalized. This paper suggests an adaptive music therapy program that will be driven by AI and will help individuals regulate their emotions, maintain engagement, and be ready to learn in…
Predictive Analytics for Employability in Creative Fields
The field of employability assessment is getting revolutionized by predictive analytics in creative industries because it can be used to assess skills, portfolios, and career paths based on data. The creative labor markets (design, visual arts, media, and digital content production) can be described by their heterogeneous skills, subjective quality standards, and quickly changing demand trends, which renders the conventional methods of employabil…
Machine Learning for Predicting Audience Preferences in Dance
Artificial intelligence and performing art intersect to provide new opportunities to study human emotion, creativity and aesthetic experience. In this paper, I have introduced a generalized machine learning model to predict the audience preferences in the field of dance by applying the multimodal information visual, audio, and physiological to one analytical system. The CNNLSTMTransformer fusion model is based on the proposed CNN-LSTM-Transformer…
Augmented Reality in Media-Based Learning Environments
Augmented Reality (AR) has become a revolutionary technology in the educational field, and it fills the gap between the physical and the digital learning environment. This paper describes the application of AR to the learning context using media, with a focus on its ability to improve interactivity, immersion, and contextual learning. AR promotes both constructivist and experiential learning methods by integrating multimedia elements like text, a…
Neural Networks for Classifying Indian Folk Motifs
In this paper, I have outlined a hybrid neural network model of automated classification of Indian folk motifs within the different regional traditions, such as Madhubani, Warli, Kalamkari, and Pattachitra. Introduced was a culturally authentic curated collection of 5000 high-resolution images created by ethical digitization and by human experts. The suggested model uses a Convolutional Block Attention Module (CBAM) in addition to a ResNet-50 bac…
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Machine Learning for Predicting Audience Preferences in Dance
Artificial intelligence and performing art intersect to provide new opportunities to study human emotion, creativity and aesthetic experience. In this paper, I have introduced a generalized machine learning model to predict the audience preferences in the field of dance by applying the multimodal information visual, audio, and physiological to one analytical system. The CNNLSTMTransformer fusion model is based on the proposed CNN-LSTM-Transformer…
Augmented Reality in Media-Based Learning Environments
Augmented Reality (AR) has become a revolutionary technology in the educational field, and it fills the gap between the physical and the digital learning environment. This paper describes the application of AR to the learning context using media, with a focus on its ability to improve interactivity, immersion, and contextual learning. AR promotes both constructivist and experiential learning methods by integrating multimedia elements like text, a…
Neural Networks for Classifying Indian Folk Motifs
In this paper, I have outlined a hybrid neural network model of automated classification of Indian folk motifs within the different regional traditions, such as Madhubani, Warli, Kalamkari, and Pattachitra. Introduced was a culturally authentic curated collection of 5000 high-resolution images created by ethical digitization and by human experts. The suggested model uses a Convolutional Block Attention Module (CBAM) in addition to a ResNet-50 bac…
Interactive Mixed-Reality Installations Combining Physical Materials With Advanced Digital Projection Techniques
Interactive mixed-reality (MR) installations represent a radically different variant of convergence of material objects with the latest methods of digital projection that creates immersive and interactive experiences in art. The current paper is an outline of the design and installation of MR installations that can harmoniously blend the material or tangible component of wood, metal, cloth and transparent media with the interactive dynamic projec…
Ai-Powered Music Therapy for Education
The artificial intelligence (AI) has offered new possibilities to improve the sphere of music therapy as the means of adaptive support within the educational settings. The traditional music therapy methods are useful but very stagnant and cannot be scaled and personalized. This paper suggests an adaptive music therapy program that will be driven by AI and will help individuals regulate their emotions, maintain engagement, and be ready to learn in…
Predictive Analytics for Employability in Creative Fields
The field of employability assessment is getting revolutionized by predictive analytics in creative industries because it can be used to assess skills, portfolios, and career paths based on data. The creative labor markets (design, visual arts, media, and digital content production) can be described by their heterogeneous skills, subjective quality standards, and quickly changing demand trends, which renders the conventional methods of employabil…
Augmented reality (2 works) · Augmented Reality Applications (2 works) · Creativity (2 works) · Emotion and Mood Recognition (2 works) · Neuroscience and Music Perception (2 works) · Visualization (2 works) · Aesthetic Perception and Analysis (1 work) · Analytics (1 work) · Art, Technology, and Culture (1 work) · Artificial neural network (1 work)