Palaash Agrawal

CEO

Los Angeles, California, United States4 yrs 2 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Innovative AI-driven music production software.
Published multiple research papers in AI.
Expertise in AI applications for healthcare.

Stackforce AI infers this person is a multifaceted AI researcher and developer with a focus on healthcare and music technology.

Contact

Skills

Core Skills

Machine LearningAi DevelopmentMusic ProductionAi ResearchNatural Language ProcessingAi In HealthcareComputer VisionCognitive Science

Other Skills

Large Language Models (LLM)Deep LearningPython (Programming Language)PythonC++C (Programming Language)MatlabHTMLAutoCADSimulinkPyTorchTensorFlowLinuxGoogle Cloud Platform (GCP)Jupyter

About

www.veena.studio Music x AI. Representing India and its culture globally. Building Veena - music creation made easy, intuitive and fun for first time music makers. They call me Pandit G.

Experience

4 yrs 2 mos

Total Experience

2 yrs

Average Tenure

1 yr 6 mos

Current Experience

Veena

Chief Guy

Nov 2024 – Present · 1 yr 6 mos · Los Angeles, CA

Veena is a music editor (DAW) with an AI Assistant that autonomously handles end to end music production.
It will understand what kind of song you're trying to build, generate audio and midi, arrange, add FX, mix and master for you.
This isnt prompt-to-song. Its layered creation, guided by you. The AI will pause and ask you for your inputs. Its your sound, voice and style. Not AI generated slop!
www.veena.studio

Computer VisionLarge Language Models (LLM)Machine LearningDeep LearningPython (Programming Language)AI Development

A*star - agency for science, technology and research

AI Research Engineer

Oct 2022 – Oct 2024 · 2 yrs · Singapore

Research Areas:
1. LLMs (3 papers)
2. Cognitively Inspired AI (1 paper)
3. Synthetic Visual Datasets (1 paper)
Papers: See publications section

Large Language Models (LLM)Machine LearningDeep LearningAI ResearchNatural Language Processing

Seniorlife technologies, inc.

Software Engineer

Feb 2022 – Feb 2024 · 2 yrs · Seattle, Washington, United States

Area: AI in Healthcare, 3D Computer Vision.
Built 3D computer vision models for mobility diagnosis (for senior citizens). Including medically aligned models for.
(1) Balance. (2) Degree of Mobility. (3) Pre-fall. (4) Range of Motion (Knee/Back/Ankle).
Also worked on
(1) FDA approval. (2) HIPAA compliance. (3) Payment interface.

Computer VisionMachine LearningAI in Healthcare

Massachusetts institute of technology

Bachelor's Thesis

Oct 2021 – Jun 2022 · 8 mos · Cambridge, Massachusetts, United States

Area: Cognitive Science inspired AI
Analysed similarities between human fMRI signals and activations of deep learning models.

Cognitive ScienceAI Research

Philips

Research Intern

May 2021 – Aug 2021 · 3 mos · Bengaluru, Karnataka, India · On-site

Area: AI in Healthcare
Built lightweight classifiers and segmentation models for Tumor grading, to integrate in MRI machines.

AI in HealthcareMachine Learning

The university of texas at san antonio

Research Intern

Mar 2021 – Sep 2022 · 1 yr 6 mos · San Antonio, Texas Metropolitan Area · Remote

Area: Cognitive Science inspired AI
Paper: "Advancing Perception in Artificial Intelligence through Principles of Cognitive Science".
An AI researcher's primer on building AI models inspired by concepts of neuroscience, psychology, and linguistics.

Cognitive ScienceAI Research

Stanford university

Research Intern

Aug 2020 – Mar 2021 · 7 mos · California, United States · Remote

Area: Computer Vision
Paper: "WTM: Weighted Temporal Attention Module for Group Activity Recognition"
State-of-the-Art models for Group Activity Recognition.

Computer VisionMachine LearningAI Research

Bhaskaracharya institute for space applications and geo-informatics

Machine Learning Intern

May 2020 – Jul 2020 · 2 mos · Gandhinagar, Gujarat, India

Area: hyperspectral computer vision.
Trained models for Agricultural Boundary Segmentation of satellite images.

Machine LearningComputer Vision

Mahindra susten

Engineering Intern

May 2019 – Jun 2019 · 1 mo · Dubai, United Arab Emirates · On-site

Area: Renewable Energy / Electrical Engineering.
Didnt contribute anything, just learned.
I learned all about engineering, procurement, finances and operations of the solar energy market. This served as the basis for my paper on optimizing the derived solar power using deep learning.
Paper: "Transformer-based Time Series Prediction of the Maximum Power Point for Solar Photovoltaic Cells".