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Part-time trainee intern

Steinberg Media Technologies gmbH, Hamburg, Germany

My roles involve training machine learning models with internal data. I am also briefly accustomed to plugin development and assist in prototyping research to technology.

Part-time trainee intern

Steinberg Media Technologies gmbH, Hamburg, Germany

My roles involve training machine learning models with internal data. I am also briefly accustomed to plugin development and assist in prototyping research to technology.

Visiting Lecturer

Sri Satya Sai Institute of Higher Learning, Anantapur Campus, Puttaparthi, India

Taught a part of the course on Mathematical Physics to the undergraduate students.

PhD

Queen Mary University of London, London, UK

• Deep Learning for Audio and Music
• Machine Learning
• Recording and Production Techniques
• Music Information Retrieval

Master of Science (MSc) in Physics

Pondicherry University, Puducherry, India

• Non Linear Dynamics
• Mathematical Physics (I and II)

Bachelor of Science (BSc) [Hons] in Physics

Sri Sathya Sai Institute of Higher Learning, Puttaparthi, India

• Set theory
• Multivariate Calculus
• Differentiable Equations
• Linear Algebra
• Electronics [Digital and Analog]
• Mathematical Physics (I and II)
• [Python, C, C++, Scilab]

UKRI AIM-CDT Award

UK Research and Innovation (UKRI)

Fully funded PhD for 4 years

Eshwari Bai Gold Medal

Sri Sathya Sai Institute of Higher Learning (SSSIHL)

Awarded for BSc [Hons] Physics

DST-Inspire Scholarship

Government of India

Funding for MSc and BSc for five years

PU Merit Scholarship

Pondicherry University

Merit Scholarship

South Eastern Coalfields Limited (SECL) Study Support Excellence Scholarship

South Eastern Coalfields Limited (SECL)

Study Support Excellence Scholarship for 2 years

The Role of Communication and Reference Songs in the Mixing Process: Insights From Professional Mix Engineers

Journal of the Audio Engineering Society

Effective music mixing requires technical and creative finesse, but clear communication with the client is crucial. The mixing engineer must grasp the client's expectations and preferences and collaborate to achieve the desired sound. The tacit agreement for the desired sound of the mix is established using guides like reference songs and demo mixes exchanged between the artist and the engineer.

AI for Multitrack Mixing - A Workshop

Audio Engineering Society Show NYC

This workshop explores the application of AI technologies in multitrack mixing, providing insights into the future of mixing workflows.

Adoption of AI Technology in Music Mixing Workflow: An Investigation

154th Audio Engineering Society Convention

The integration of artificial intelligence (AI) technology in the music industry is driving a significant change in the way music is being composed, produced and mixed. This study investigates the current state of AI in the mixing workflows and its adoption by different user groups.

Deep Learning for Automatic Mixing

Proc. of the 23rd Int. Society for Music Information Retrieval Conf. (ISMIR)

Mixing is a central task within audio post-production where expert knowledge is required to deliver professional quality content. This tutorial discusses deep learning approaches for automatic mixing, addressing challenges and providing insights for researchers and practitioners.

Intelligent Music Production: Music Production Style Transfer and Analysis of Mix Similarity

16th Digital Music Research Network (DMRN+ 16) Workshop

We present a poster introducing the idea of mixing style transfer as a user centric approach to AI-based mixing.

The Sound of One Hand CLAPping

Evolutionary search over VSTi synthesiser parameters using CLAP embeddings as a fitness function. Project for Timbre Hackathon 2024

• Genetic Algorithm
• CLAP