Mansoor Rahimat Khan

R&D Marine Lab Setup

Beatoven.ai

Beatoven.ai is a AI powered music creator tool which helps content creators compose original soundtracks for their content. We are backed by Capital2B and Entrepreneur First.

Finalists at TechCrunch Disrupt 2022, Meet The Drapers and Music Ally SI:X

Co-founder & CEO

Entrepreneur First

Cohort member at Entrepreneur First which is the world’s leading talent investor/venture capital with a less than 1% acceptance rate. EF supports individuals to build technology companies and is backed by LinkedIn, Paypal, and Google DeepMind founders.

Founder in Residence

Great Learning

Responsible for Product Development for AIML Online and Blended programs in collaboration with UT Austin and Bootcamp program in collaboration with Massachusetts Institute of Technology(MIT). Also responsible for product for B2B engagements with Samsung, Soc-Gen and JPMC. Built several hackathons within the organisation which scaled to almost 10000 learners. (Acquired by Byju's for 600mn$)

Senior Data Scientist

ToneTag

- Built a music recognition/audio fingerprinting algorithm from scratch and did a POC on the same.
- Built my own data over sound transfer algorithm using beats, patent has been published for the same.

Research Analyst - Deep Learning for Audio Applications (Amazon Funded Startup)

Georgia Institute of Technology

Flag Football Referee, Georgia Tech Campus Recreation Center

Student and Researcher at the Georgia Tech Center for Music Technology(GTCMT: http://www.gtcmt.gatech.edu/) in the Music Informatics Lab. Built an audio classification system to classify sounds into five categories of Human, Urban, Music, Effects and Nature.

Graduate Student - Machine Learning for Audio Applications

Indian Institute of Technology, Bombay

Project
- Perceptual Discrimination of Tone Quality Associated with Sitar Jawari

Abstract
-A critical factor in the richness of a sitar’s sound is the Jawari, which refers to the bridge on the instrument’s sound plate. The actual extent of contact of the strings with the curved surface of the bridge is known to significantly influence the perceived tone quality. Expert musicians use their auditory skills to guide the process of jawari (filing the bridge) to achieve the desired sound quality between the two extremes of Band (closed) and Khula (Open). Based on field recordings of isolated strokes collected at the Kala Academy, Goa, this study aims to study the reliability of perceived differences between the two categories of Jawari in sitar. We present the results of a subjective experiment where multiple recordings of first 3 strings of 13 sitars were presented to 7 experts to identify the jawari. Based on annotations by experts it was observed that the experts’ comments were largely in agreement with each other about the type of Jawari of individual strings. Further, observations of the acoustic signal spectra computed from recordings of the string pluck indicate significant differences between the two types of jawari.

Technology:
- Python, Music Technology Libraries from Essentia( www.essentia.upf.edu)

Project Consultant - Machine Learning for Audio Applications

Edelweiss Financial Services

Project
-Trading of Eurodollar Short Term Interest Rates Futures Markets

Description
• Provided liquidity in Eurodollar(Chicago Mercantile Exchange), Short Sterling and Euribor Short Term Interest Rates(STIRs)(Intercontinental Exchange) futures contract generating avg. daily roundtrips of 500
• Made trading decisions using strategies that involved a mix of Technical/Fundamental analysis, studying Price Action together with strategies like calendar spread, butterfly, condor, etc. to meet weekly profit targets

Technology:
- Stellar, Bloomberg

Achievements:
- Consistently listed as the Top 10 performers for three months based on Profit & Loss, trading techniques, risk managed etc.
- One of the Top 10 net P&L achievers for three consecutive months, securing the 3rd position in one particular month based on the net profits earned
- Achieved 500% increase in clip size from the initial value based on consistency in trading performance and P&L

Junior Analyst - Global Derivatives Trader

Worked in the Digital Audio Processing Lab,(DAPLAB), at the Electrical Department of IIT Bombay.Worked on Studying the acoustics of the instrument Sitar using signal processing techniques and Fret Classification Algorithms.

Research Intern

IEEE

Managing the registrations of the delegates at the conference

Student Onsite Volunteer - HiPC World Conference

IEEE HIPC World Conference, 2014

Providing the delegates with their passes against their registrations for the conference as well as general management of the conference

Student Onsite Volunteer

I'm a professional sitar player & music tech entrepreneur with 19 years of experience in the live music and recording industry. I come from one of the most reputed music families from India which has been dedicated to music for the past 7 generations and shaped the modern day sitar (Gwalior-Indore-Dharwad Gharana of Sitar). I’m also a Forbes 30 under 30 Asia honoree 

I'm an alumni of the Georgia Tech center for music technology and have worked across several startups in tech and product roles with several publications and patents in deep learning for audio applications to my credit.

Taplio

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