SHARON MARIA VARGHESE

AI Researcher and Engineer specializing in Deep Learning, NLP, and Computer Vision. Experienced in translating cutting-edge AI research into scalable engineering solutions. Focused on AI-driven innovations in healthcare and music therapy. Proven expertise in AI research, software development, and technical leadership, with strong skills in architecture design and cloud computing.

Goal-Driven Music Recommendation System for Individuals with Autism Spectrum Disorder

• Designed and implemented the GOAL framework (Genre, Optimization, Acoustic Features, Lyric Themes) to provide personalized music recommendations for individuals with ASD.
• Tailored recommendations to therapeutic outcomes, including Mood Management, Sensory Load Regulation, Focus, Sleep Regulation, Communication, and Social Skills.
• Achieved 84% F1-score, 85% precision, and 83% recall, demonstrating the framework’s effectiveness in music therapy applications.

Listening to the Spectrum: Exploring Music Preferences and Associations in Autism Spectrum Disorder vs Neurotypical Communities on Reddit

• Conducted an in-depth analysis of 429 Reddit posts from ASD and neurotypical communities, uncovering key themes in music discussions. While neurotypical discussions centered on cultural and industry trends, ASD discussions highlighted music’s therapeutic role in emotional regulation and sensory load management.
• Examined 557 music tracks to evaluate their genre, valence, and lyrical themes, assessing their emotional and behavioral impact across both groups. ASD individuals exhibited a stronger preference for Pop, Electronica, and Metal, whereas neurotypicals favored Rock and Country. Lyric analysis revealed distinct thematic preferences—ASD individuals resonated more with Adventure & Exploration, Love & Connection, and Emotional Turmoil, while neurotypicals focused on Struggles & Hardships and Self-Discovery.

Cross-Cultural Comparative Study of Music Preferences and its Behavioural Effects in Non-Indian and Indian ASD Adults

• Conducted a cross-cultural comparative study on music preferences between non-Indian and Indian adults with ASD.
• Identified significant differences in music preferences and behavioral effects, with non-Indian participants favoring Rock and Western Classical music, while Indian participants preferred Indian Film and Devotional music.
• Highlighted the importance of culturally inclusive music therapy interventions.

Pilot Study of Indian ASD Children to Understand Music Preferences and its Behavioural Effects

• Conducted a pilot study to evaluate music preferences among Indian children diagnosed with ASD.
• Identified that Indian Devotional music, Nursery Rhymes, and Indian Film music were associated with positive behavioral changes.
• Highlighted music’s role in reducing anxiety (80%) and enhancing social interaction (60%) in children with ASD.

• Tailored Music Recommendations for Individuals with Autism Spectrum Disorder: A Goal-Driven Approach, Speech, Music and Mind 2024, Satellite Workshop of Interspeech (SMM24)
• Music Preferences Among Individuals with ASD - A Cross-Cultural Study, International Conferences of Music Perception and Cognition (ICMPC-23)
• Nature of Music Preferences Among Children with ASD, Society of Music Perception and Cognition (SMPC19)

• Oracle Cloud Infrastructure (OCI) 2024 Certified AI Foundations Professional – Oracle, July 2024
• Oracle Cloud Infrastructure (OCI) 2024 Certified AI Foundations Associate – Oracle, July 2024
• Audio Signal Processing for Computational Musicology – IIT Bombay, December 2019
• International Research Center for Neurointelligence (IRCN) Program – University of Tokyo, March 2019

• Reading Books
• Traveling
• Baking
• Painting
• Badminton
• Basketball

• English
• Hindi
• Telugu
• Malayalam