Neuro-AI Researcher

KushalKapoor

Building the future of neuro-inspired AI

PhD-bound researcher developing hippocampal-inspired architectures for continual learning. Bridging computational neuroscience and deep learning to create more intelligent systems.

01. About Me

Researcher at the intersection of neuroscience and AI

I'm a Computer Science student at the University of Maryland, College Park, pursuing a B.S. in Computer Science with Honors (Machine Learning), Neurotechnology, and Computational Finance.

My research centers on developing hippocampal-inspired architectures for continual learning. I'm particularly interested in how biological principles like pattern separation in the Dentate Gyrus can address catastrophic forgetting in neural networks.

Beyond research, I've worked as a Software Research Engineer at Marriott International and lead the quantitative desk at Apex Fund, where I develop AI-powered trading strategies.

I'm actively seeking PhD opportunities for Fall 2026 to continue advancing the field of neuro-inspired artificial intelligence.

Technical Skills

Deep LearningMachine LearningNLPPythonOpenAITensorflowFlutterJavaCGCPAWSJiraData ScienceLinux

Neuro-AI Research

Developing hippocampal-inspired architectures for continual learning systems

Computational Neuroscience

Bridging biological intelligence with artificial neural networks

Deep Learning

Expertise in PyTorch, TensorFlow, and large-scale model development

PhD Bound

Seeking Fall 2026 opportunities in Neuro-AI and Computational Neuroscience

Relevant Coursework

Data ScienceMachine LearningSignal ProcessingAlgorithmsfMRICellular NeuroscienceMolecular NeuroethologyNeural Circuits

01.5 Research Experience

Advancing computational neuroscience and AI

Perception and Robotics Group

Undergraduate Research Assistant

January 2025 - Present
•
College Park, MD
  • ▸Developed and published HiCL, a hippocampal-inspired continual learning algorithm with state-of-the-art retention at 5% compute
  • ▸Conducting Honors thesis research on improved evolutionary algorithms with Prof. Yiannis Aloimonos
  • ▸Attended advanced seminars and guest lectures in neuro-inspired AI, deepening interdisciplinary expertise
  • ▸Fine-tuned Atlantis to recreate underwater scenes using components from SONAR emissions and text descriptions
Continual LearningEvolutionary AlgorithmsComputer Vision

Shamma Lab

Undergraduate Research Assistant

March 2024 - November 2024
•
College Park, MD
  • ▸Worked on deciphering MEG data into words under Dr. Shibab Shamma
  • ▸Associated words as spikes and correlated with MEG data
  • ▸Trained ChatGPT to predict spikes and spoken words from neural signals
MEGNeural DecodingNLP

Genome Computing Lab in FIRE

Undergraduate Research Assistant

August 2022 - December 2023
•
College Park, MD
  • ▸Developed 3D models of nucleosome-decorated DNA fragments to investigate linker sequence effects
  • ▸Analyzed sequence-dependent DNA-protein interactions in lac repressor loops
  • ▸Managed large-scale biological data processing with Python scripts
  • ▸Presented research poster 'Linker DNA Sequence Effects on Nucleosome Orientation' at FIRE Research Day
Computational BiologyStructural BiologyData Science

Presentations

Invited Talk

HiCL: Hippocampal Inspired Continual Learning

DEVCOM ARL, University of Tennessee, Knoxville • July 2025

Presented to graduate students, lab members, and SURF students

Poster

Linker DNA Sequence Effects on Nucleosome Orientation

FIRE Research Day, University of Maryland • November 2023

04. Publications

Research contributions

Published Work

HiCL - Hippocampal Inspired Continual Learning

AAAI 2026Published

Developed a hippocampal-inspired architecture for continual learning that significantly reduces forgetting in neural networks. Engineered a DG-Gated MoE system achieving near SOTA performance at 5% computational cost.

Continual LearningNeuro-AIDeep Learning

DeceptionTime - Predicting the Movement of Shares Using Momentum Indicators

ICDC 2021 (Springer)Published

Designed a large-scale deep learning model using transpose CNNs, ESNs, and GRUs to predict stock price movement. Architecture surpassed State-of-the-Art models including Google's Inception by 10-200% on benchmarks.

Time SeriesFinancial MLDeep Learning

Preprints & Work in Progress

Generative Models for Underwater Image Reconstruction

ICRA 2026 (Submitted)

Developed a diffusion-based model to generate underwater images from backscattering, illumination, and text descriptions. Fine-tuned Atlantis for enhanced underwater scene recreation.

Computer VisionDiffusion ModelsRobotics

AlphaSynuclein to Parkinson's Predictor

In Preparation

Predictive modeling for Parkinson's disease progression using protein structure analysis.

Computational BiologyHealthcare AI

Avellaneda-Stoikov Model with Dentate Gyrus Integration

In Preparation

Enhanced market-making model incorporating pattern separation inspired by the Dentate Gyrus for improved predictive modeling.

Quantitative FinanceNeuro-AI

02. Experience

Professional journey

Professional Experience

Marriott International

Software Research Engineer (Flex), Loyalty Engineering

June 2024 - December 2024
•
Bethesda, MD
  • ▸Worked under the Loyalty Operations Team and Marriott Design Labs at Marriott International
  • ▸Streamlined productivity of the Loyalty IT team through a Jira Ticket assistant, running searches on past Jira tickets and providing recommendations to solve tickets, overall increasing the productivity of the team by 20% and reducing ticket resolution time by 50%
  • ▸Collaborated with Viam and Marriott Design Labs to build a Rover for improving Waste Management in Marriott offices and hotels through auto circulation
  • ▸Developed a proposition to build a self-learning tool to speed up data transfers for new hotel acquisitions for past reservations by 50%
  • ▸As part of the RMRC team, worked in Knowledge transfer and Personal Risk to help the Loyalty Engineering transition during layoffs
AI/MLSoftware EngineeringRoboticsNLP

Apex Fund

Analyst, Quantitative

August 2023 - Present
•
College Park, MD
  • ▸As part of the Apex Fund's Quantitative division, started helping develop strategies, build infrastructure to eventually leading own desk and strategy with 4 junior analysts
  • ▸Worked on a strategy to trade Oil Futures based on Soccer trades made by owners of clubs with significant business in the Oil Production industry
  • ▸Solely responsible for building the infrastructure of the club, from a database to an event driven Backtester to ease development of all future strategies
  • ▸Developing a version of the Avellaneda-Stoikov Market Making model, improved by adding a layer of pattern separation by adding a network similar to the Dentate Gyrus, to introduce predictive modelling
Quantitative FinanceMachine LearningStrategy DevelopmentInfrastructure

Teaching Experience

University of Maryland, College Park

Department of Computer Science

Undergraduate Teaching Assistant - CMSC 216 - Introduction to Computer Systems

August 2023 - May 2024
•
College Park, MD
  • ▸Worked under Dr. Ilchul Yoon and Dr. Christopher Kauffman to teach CMSC 216, Introduction to Computer Systems
  • ▸Handled over 1000 students and taught 5 sections of 40 people each, and graded assignments and exams for students
  • ▸Was voted one of the best TAs from a Staff size of 40 under Dr. Kauffman
  • ▸Pre-emptive offer from Dr. Christopher Kauffman to be a part of his teaching staff for CMSC 216 for Spring 2026
TeachingComputer SystemsC ProgrammingLinux

03. Projects & Hackathons

Award-winning innovations

Blindspot

Bitcamp 2023 - 1st Place Winner

Created a prototype of image-recognition glasses for the visually impaired using YOLO object detection algorithm with optimized parameters and facial recognition.

Computer VisionYOLOHardware Integration

ThoughtWheels

TreeHacks 2024 - Top 10/500 Projects

Smart wheelchair controlled by brain waves for people with severe mobility impairment. Designed signal processing algorithms for EEG signals from Muse 2 and developed robotic control system.

BCISignal ProcessingRobotics

MediChain

HackMIT 2024 - Best Blockchain Hack

Blockchain-based platform for secure patient data management. Integrated blockchain with Neo4j knowledge graphs for tamper-proof storage and decentralized medical records.

BlockchainHealthcareNeo4j

05. Get in Touch

Let's collaborate

I'm actively seeking PhD opportunities in Neuro-AI and Computational Neuroscience for Fall 2026.

Whether you're interested in discussing research collaborations, PhD opportunities, or just want to connect, I'd love to hear from you.

Connect

GitHubkushalkapoor25
LinkedInkushalkapoor
Emailkushalk@umd.edu

© 2025 Kushal Kapoor. All rights reserved.

Designed and built with passion for advancing neuro-inspired artificial intelligence