```html Tamar Glaser | Senior Principal ML Engineer & Researcher

About Me

Results-oriented AI/Machine Learning leader with a proven track record of driving innovation through holistic problem-solving, spanning foundational research down to user-facing production systems. Expert in identifying, defining, and mitigating complex AI risks with a delicate blend of deep technical skill, scalable systems architecture, and strategic deployment paradigms.

Core Expertise

Machine Learning Computer Vision Technical Leadership Responsible AI & Safety Generative AI Alignment Multimodal Systems Transformer Models System Architecture Design Image Processing Algorithms

Professional Experience

Senior Principal Engineer, Machine Learning
Harman International
2024 - Present
  • Spearheading the design and development of an innovative, multimodal content representation and recommendation system integrated into a user-facing product.
  • Leading end-to-end machine learning pipelines, training architecture, and robust modular core systems.
  • Driving the implementation of state-of-the-art transformer-based models and conducting original foundational research to close modern edge case gaps.
Senior Machine Learning Engineer / Researcher
Meta Platforms, Inc.
2022 - 2024
  • Owned cross-functional technical tracks for Responsible AI, automated content moderation, and algorithmic safety.
  • Built a state-of-the-art Generated Content Detection framework reaching a 91% minimum precision-recall benchmark across diverse commercial generation models.
  • Led proactive safety mitigation for Multi-modal LLMs, designing end-to-end guardrails to significantly drop adversarial downstream output risks.
  • Implemented key algorithmic parity mechanisms reducing baseline bias in generative text-to-sticker spaces.
Computer Vision & Deep Learning Researcher
Alibaba DAMO Academy (Machine Intelligence Israel Lab)
2018 - 2021
  • Developed novel attention deep learning frameworks optimizing automatic web-scale user photo album event classification and content parsing.
  • Architected a custom automatic event tracking engine, enhancing overall parsing accuracy metrics (F1 score) by over 50%.
Computer Vision Algorithms Developer
Elbit Systems, ISTAR Division
2010 - 2018
  • Engineered classical and deep-learning target tracking, image registration, and object detection systems operating across multi-wavelength visual data streams.

Selected Publications & Peer Review

Fine-Grained Erasure in Text-to-Image Diffusion-based Foundation Models
K. Thakral, T. Glaser, T. Hassner, M. Vatsa, R. Singh
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025
Continual Unlearning for Foundational Text-to-Image Models without Generalization Erosion
K. Thakral, T. Glaser, T. Hassner, M. Vatsa, R. Singh
Under Review: IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2025
The Llama 3 Herd of Models
A. Dubey, A. Jauhri, ..., T. Glaser, ..., R. Ganapathy
arXiv preprint, 2024
Navigating Text-To-Image Generative Bias Across Indic Languages
S. Mittal, A. Sudan, R. Singh, M. Vatsa, T. Glaser, T. Hassner
European Conference on Computer Vision (ECCV), 2024
On responsible machine learning datasets emphasizing fairness, privacy and regulatory norms with examples in biometrics and healthcare
S. Mittal, K. Thakral, R. Singh, ..., T. Glaser, T. Hassner
Nature Machine Intelligence, 2024
PETA: Photo Albums Event Recognition using Transformers Attention
T. Glaser, E. Ben-Baruch, G. Sharir, N. Zamir, A. Noy, L. Zelnik-Manor
International Conference on Pattern Recognition (ICPR), 2022
You Only Need a Good Embeddings Extractor to Fix Spurious Correlations
R. Mehta, V. Albiero, L. Chen, I. Evtimov, T. Glaser, Z. Li, T. Hassner
Responsible Computer Vision (RCV) Workshop, ECCV, 2022 (Oral Presentation)
Incorporating temporal context in bag-of-words models
T. Glaser, L. Zelnik-Manor
ICCV Workshops, 2011 (Oral Presentation)

Professional Activities & Chairs

Co-Organizer & Program Chair
2023 - 2024

Organized the Workshop and Challenge on DeepFake Analysis and Detection (DFAD) in conjunction with CVPR 2024 (Seattle) and ICCV 2023 (Paris), facilitating benchmarks and research tracks around responsible generative modeling.

Education

M.Sc. in Electrical Engineering (Honors)
Technion - Israel Institute of Technology
GPA: 4.0

Focus area: Computer Vision research thesis; Full Academic Scholarship.

B.Sc. in Electrical Engineering & B.A. in Physics (Dual Degree)
Technion - Israel Institute of Technology
Honors

Graduated through the highly selective IDF "Psagot" excellence track track.

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