Aaditya Singh

Product Engineer

New York, New York, United States5 yrs 2 mos experience

Most Likely To Switch

Key Highlights

7+ years in AI research and algorithmic trading.
Expert in ultra-low latency trading systems.
Published researcher in federated learning.

Stackforce AI infers this person is a Fintech expert specializing in AI-driven trading systems and machine learning applications.

Contact

Skills

Core Skills

C++PythonMachine LearningDeep LearningSoftware DevelopmentApi DevelopmentData AnalysisData ScienceMobile DevelopmentFederated LearningComputer VisionData Processing

Other Skills

Android DevelopmentCUDACascading Style Sheets (CSS)Dimensionality ReductionGo (Programming Language)HTMLJavaJavaScriptLinuxMXNetMongoDBOCamlOpenCVPillow/PILPyTorch

About

Quantitative Developer at Interactive Brokers with 7+ years of experience in AI research, algorithmic trading, and high-performance systems. Dual MS graduate from Georgia Tech in Computer Science and Quantitative Finance. Currently building ultra-low latency trading systems and ML-powered risk management frameworks processing billions in daily volume. Previously developed AI systems at Adobe AI Lab and led computer vision projects at Skylark Drones. Core expertise: C++, Python, algorithmic trading, options pricing, machine learning, and real-time financial data processing. Published researcher in federated learning with speaking engagements at industry conferences. Passionate about the intersection of AI and quantitative finance. Always open to discussing innovative applications of machine learning in financial markets.

Experience

Interactive brokers

2 roles

Quantitative Developer

Jan 2024 – Present · 2 yrs 2 mos · New York, New York, United States

C++Python

Quant Developer Intern

Jun 2023 – Aug 2023 · 2 mos · New York, United States · On-site

C++Python

Georgia institute of technology

Graduate Teaching Assistant

Jan 2023 – May 2023 · 4 mos

Worked with Prof. Zsolt Kira (https://www.cc.gatech.edu/~zk15/) on continual learning and federated learning. TA'ed for CS-7643(Deep Learning) during Spring 23.

CUDAMXNetPyTorchMachine LearningDeep Learning

Indian institute of technology, madras

Post-baccalaureate Researcher @ RISE Lab

Sep 2021 – Mar 2022 · 6 mos

Implemented Restless Multi-Armed Bandits (RMAB) to address dynamic resource allocation problems in maternal and child health interventions. RMABs outperformed traditional static allocation models by adapting to evolving healthcare needs, which led to a 61.37% improvement in targeting high-risk patients
This project was a part of AI for social good under prof Balaraman Ravindran.

PyTorchPythonScikit-LearnMachine LearningData Science

University of florida

Researcher @ Bioinformatics Lab

May 2021 – May 2022 · 1 yr

Designed and developed algorithm for supervised dimensionality reduction
CST performed 5% better than (SOTA) tSNE & UMAP on NCBI cancer datasets
CST was able to identify "AGER" and "IL6" propagation on Cancer PPI networks

Riemannian manifold approximationfuzzy singular setsDimensionality ReductionData AnalysisMachine Learning

Indian institute of technology, delhi

Researcher @ LowCode Systems Lab

Sep 2020 – Mar 2021 · 6 mos · Delhi, India

Developed Unikernels for android using QEMU and KVM with Prof Abhilash Jindal
Studied security and isolation of unikernals and measured performance of unikernal application on device

C++JavaAndroid DevelopmentOCamlSoftware DevelopmentMobile Development

Adobe

2 roles

Member of Technical Staff

Promoted

Aug 2020 – Aug 2022 · 2 yrs

(ACPL) Adobe Content Platform Library
Worked on Adobe’s cloud document syncing and collaboration-platform(ACPL)
Reduced the 2x(30ms) time and 5x memory footprint of CRUD API’s
(ETHOS) Adobe Sevice Platform
Implemented client dashboards and cluster diagnostic tool in ETHOS platform
Improved cluster resource utilization by 5% and overall API throughput

C++JavaJavaScriptRuby on RailsGo (Programming Language)Software Development+1

Researcher @ AI Lab

May 2019 – Aug 2019 · 3 mos · Bengaluru Area, India

Designed FEDPER privacy preserved personalization in Federated Learning (250+ citations)
Solved the problem of statistical heterogeneity in Federated Learning by having separate personalized client Layers
Increased average client model accuracy by 40%, Oral at AISTATS ’20

C++PythonPyTorchCUDAMachine LearningFederated Learning

University of sydney

Research Intern @ Genetics Lab

Dec 2018 – Jan 2019 · 1 mo · Sydney, Australia

Compared state-of-art convolutional neural network architectures with Computer Vision algorithms for parasitic cell segmentation
Used regression based methods for classification of nacre
Used data augmentation, dropout and early stopping techniques to prevent overfitting on the training set data. Used R packages like tidyverse and magick to visualize the dataset effectively.
Research Areas: Computer Vision, Deep Learning, Image Semantic Segmentation,

PythonPillow/PILScikit-ImageOpenCVTensorFlowComputer Vision+1

Skylark drones

Research Development Software Engineer

May 2018 – Jul 2018 · 2 mos · Bengaluru Area, India

Developed homographic transformation algorithm for geotagging image pixels
Reduced 2x data storage using adaptive frequency decomposition for images

PythonMongoDBLinuxJavaScriptOpenCVSoftware Development+1

International relations cell, iit kharagpur

Student Member

Jul 2017 – Dec 2017 · 5 mos · IIT Kharagpur

Structured www.international.iitkgp.ac.in and administered 6 international guest lectures including 1 by Chairman of Nobel Prize Committee
Organized seminars on SAP(300+ students), International Internships(450+students) and MS-PhD(300+ students); Streamlined GIAN process
Liaised with OIR in the signing of 3 Exchange MoU's and 20+ Inter - Institute MoU's; Co - membered FTP to secure 26 International Internships

HTMLCascading Style Sheets (CSS)JavaScript