Work with thought leaders and academic experts in computer vision

Digital Fellow / August, 2020 — Present

Senior Adviser, National AI Institute / January, 2020 — Present

Adjunct Associate Research Scholar / February, 2022 — Present

Principal Member of Technical Staff / January, 2021 — Present

Technical Program Manager / December, 2016 — November, 2020

Research Associate Professor / March, 2015 — September, 2016

Machine Learning Researcher / April, 2023 — Present

Analyzing local Representations of self-supervised vision transformers. Based on this work we published the following paper: https://arxiv.org/pdf/2401.00463.pdf; ◦ Foundation Model for Aerial Imagery; ◦ Aerial Vision-and-Dialog Navigation.

Staff Machine Learning Engineer / November, 2022 — March, 2023

Gesture Recognition: • The goal is to develop a system that can accurately classify and recognize different gestures as they happen, without any delay; • The number of gestures can be very high; • Both static and dynamic gestures should be detected.

Staff Machine Learning Engineer / January, 2022 — November, 2022

Worked on creating real-time state-of-the-art video segmentation/matting technology.

Senior Machine Learning Engineer II / January, 2020 — January, 2022

State of the art image segmentation pipeline

Image Processing Machine Learning Scientist/Engineer / May, 2019 — January, 2020

Audio Dereverberation; Image Segmentation

Principal Scientist / June, 2020 — Present

• Team lead in deep learning and computer vision projects for several government customers (DOD, DOE, etc.). • $2.5M+ captured in 8 SBIR/STTR grants captured including 2 Phase 2’s. • 3-4 projects occur at once, each with 4-6 team members including 1-2 subcontractors. • Computer vision projects: o Missile detection using infrared imagery and bio-inspired computing (technologies: U-Net, Siamese net, Keras). o Contraband detection with hyperspectral imaging and neuromorphic computing (technologies: spectral spatial ResNet, BrainChip, Keras). o UAV detection using multispectral/hyperspectral imaging (technologies: spectral spatial ResNet, Keras). • Other projects: o Network cybersecurity with deep learning using GPUs and neuromorphic computing (technologies: BrainChip, Intel Loihi, Keras). o Verification and validation of deep learning systems; time series prediction, adversarial attacks and hardening (technologies: LSTM, fast gradient sign method, Keras).

RESEARCH ASSISTANT / August, 2022 — Present

My research experience includes semantic segmentation of aerial imagery, synthetic image generation, multispectral image analysis, audio classification using sound event detection and optimizing ML workflows with GPU clusters.

Data Science Intern / June, 2021 — August, 2021

Set up a PostGRES server and SQL database for a financial trading system. Used this data to create a pipeline for an algorithmic trading toolkit.Developed a module to assess portfolio performance and associated risks. Performed backtesting to evaluate different trading strategies.

Research Scientist / 2018 — Present

Postdoctoral Researcher

Scientific Staff / 2015 — 2020

Early Stage Researcher / 2015 — 2019

Postdoctoral Researcher / November, 2024 — December

Leading research on multimodal learning combining speech vision and language for scalable AI systems. Designing and evaluating methods to improve fine-grained reasoning in large language and vision-language models.

Computer Vision Project Assistant / January, 2021 — October, 2024

Developed self-supervised and unsupervised learning techniques to improve neural network robustness to distribution shifts at test time. Conducted extensive research on LLMs and multimodal VLMs resulting in multiple publications at NeurIPS ICCV and CVPR.

Research Scientist Intern / May, 2024 — August, 2024

Designed multimodal learning methods integrating vision audio and language signals. Prototyped and evaluated models for cross-modal understanding in real-world scenarios.

Assistant Professor / October, 2020 — Present

Director Computer vision

Visiting Asisitant Professor / August, 2019 — May, 2021

Assistant Professor / June, 2021 — Present

Intern / June, 2019 — September, 2019

Worked on developing the Invoice Tracking System using the .NET framework and C# programming language. The organization later employed the invoice tracking system. • Developed a prototype for the IT website of Chevron. • Contributed to the development of an HR pay system using the.NET framework and the C# programming language. • Participated in brainstorming sessions about project requirements and meetings about ongoing projects at the company.

Apprenticeship / November, 2017 — December, 2017

• Developed a web-based task management system using PHP and MySQL to track and manage work requests.

Graduate Research Assistant / August, 2023 — Present

recision-tuning an LLM model to proficiently identify and extract textual content from various document types, including Passports, Transcripts, and Driver's Licenses, facilitating accurate information extraction.