- Leading CV driven initiatives to enhance immersive gameplay experiences at PlayStation.
- Designed real-time post-processing enhancement algorithms, addressing blocking, blurring, and ringing artifacts, and enhancing temporal coherence in high-frame-rate gameplay, ensuring consistent visual quality for 120M+ monthly active users.
- Implemented single-step diffusion models for accelerated inference, achieving 15% gains in PSNR/PSNR-B and VMAF scores, enabling high-fidelity visual effects on constrained hardware while significantly reducing computational overhead.
- Leveraged encoder-side statistics (e.g., QP values, CTU-level features, motion vectors) to condition enhancement networks, enabling content-adaptive inference and more precise artifact suppression.
Work Experience
Jun 2025 - Present
Jul 2022 - Aug 2024
Jan 2022 - Jun 2022
Feb 2021 - Dec 2021
Sep 2024 - Present
Jul 2021 - Dec 2021
Aug 2023 - Mar 2024
Sep 2021 - Nov 2021
Jul 2020 - Oct 2020
Sep 2019 - Nov 2019
Sony Interactive Entertainment
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Jun 2025 - Present
Machine Learning Engineer
- Leading CV driven initiatives to enhance immersive gameplay experiences at PlayStation.
- Designed real-time post-processing enhancement algorithms, addressing blocking, blurring, and ringing artifacts, and enhancing temporal coherence in high-frame-rate gameplay, ensuring consistent visual quality for 120M+ monthly active users.
- Implemented single-step diffusion models for accelerated inference, achieving 15% gains in PSNR/PSNR-B and VMAF scores, enabling high-fidelity visual effects on constrained hardware while significantly reducing computational overhead.
- Leveraged encoder-side statistics (e.g., QP values, CTU-level features, motion vectors) to condition enhancement networks, enabling content-adaptive inference and more precise artifact suppression.
Pivotchain Solutions
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Jul 2022 - Aug 2024
Machine Learning Engineer
- Spearheaded the development of a scalable event monitoring system, leveraging representation learning with probabilistic anomaly scoring to flag suspicious activities in real-time, leading to a 50% reduction in containment time through optimized detection and response workflows.
- Implemented a spatiotemporal autoencoder for anomaly validation, learning normal motion patterns, and flagging deviations in security footage; significantly reduced false event escalations by 20% and improved operational trust in the system.
- Deployed models into production by packaging them into modular inference services, integrated with monitoring dashboards that generated real-time alerts, audit logs, and forensic search tools for enterprise clients.
- Integrated a vector-store backend for embedding management, enabling efficient indexing, retrieval, and similarity search of feature embeddings in video streams, making ambiguous events searchable in sub-seconds.
Qualys Inc.
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Jan 2022 - Jun 2022
Software Engineer
- Designed and automated CI/CD pipelines with containerized workflows, reducing deployment cycles from 30 → 10 minutes and enabling 200+ production releases per month.
- Implemented observability pipelines (monitoring, logging, alerting) to track latency, failure rates, and resource utilization, ensuring stability under sustained high traffic.
Validus Analytics
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Feb 2021 - Dec 2021
Machine Learning Engineer
- Trained convolutional VAEs to synthesize distribution-consistent samples, expanding a limited corpus from 50K → 150K examples while maintaining perceptual similarity (SSIM > 0.85).
- Benchmarked VQ-VAEs against Conv-VAEs for unsupervised representation learning, evaluating latent space structure, reconstruction error, and generative quality across heterogeneous datasets.
Spatiotemporal ML Lab
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Sep 2024 - Present
Applied Research Engineer
- Assisting Dr. Rose Yu at UC San Diego with various CV driven initiatives at her lab.
- Conducted research on DYffusion, a dynamics-informed diffusion model for spatiotemporal climate forecasting, focusing on improving uncertainty quantification and stochastic representation of geophysical processes.
- Implemented and evaluated an almost-fair CRPS loss function (adapted from recent literature) to address biases in standard CRPS variants, yielding a 10% gain in predictive accuracy while preserving calibrated uncertainty estimates.
- Ran large-scale distributed training of forecasting models using data-parallel strategies across multi-node GPU clusters, analyzing the effect of loss function choice, sampling strategies, and noise schedules on forecast stability and calibration.
Vishwakarma Institute
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Jul 2021 - Dec 2021
Applied Research Engineer
- Spearheaded the design of a domain-adapted summarization system for research literature, integrating a BERT encoder with fine-tuned attention layers, achieving a 50% relative gain in ROUGE compared to traditional extractive methods.
- Conducted research on transformers and multi-head self-attention mechanisms, for enhanced language modeling.
Pixstory
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Aug 2023 - Mar 2024
Machine Learning Consultant
- Developed a retrieval-augmented generation system for conversational search, combining vector similarity retrieval with LLM-based re-ranking to improve semantic relevance and reduce hallucinations.
- Accelerated query serving by implementing concurrent request handling and parallel execution across the API-database pipeline, improving throughput and reducing average response latency from 3s to 600ms.
- Optimized database and data pipelines for metadata (6M+ JSON records), restructuring queries and indexing strategies to reduce retrieval times and support real-time analytics workloads.
AI For Rural
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Sep 2021 - Nov 2021
Software Development Consultant
- Implemented efficient data preprocessing and visualization pipelines for insightful data handling, intuitive data exploration, and pattern analysis.
- Developed REST APIs and integrated them with various data sources, enabling real-time data updates and reducing data retrieval time by 40% for critical information.
Exa Mobility
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Jul 2020 - Oct 2020
Content Creator
- Pioneered innovative strategies in researching and crafting website content alongside esteemed senior colleagues, resulting in a remarkable surge of approximately 20% in website traffic.
- Collaborated dynamically with the marketing and content team to conceptualize and produce captivating infographics, proposals, and blog posts tailored for both B2B and B2C technology audiences.
- Orchestrated a creative revolution, spearheading the revitalization of the mobile application through imaginative content enhancements and comprehensive overhauls.
Shinobi Brands
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Sep 2019 - Nov 2019
Content Creator
- Innovatively identified and rectified deficiencies within the content development support structure, optimizing workflow processes for enhanced efficiency.
- Collaborated synergistically with strategic planners, business stakeholders, and fellow creatives to ideate, conceptualize, and bring to life compelling brand narratives.
Work Experience
- Spearheaded the development of a scalable event monitoring system, leveraging representation learning with probabilistic anomaly scoring to flag suspicious activities in real-time, leading to a 50% reduction in containment time through optimized detection and response workflows.
- Implemented a spatiotemporal autoencoder for anomaly validation, learning normal motion patterns, and flagging deviations in security footage; significantly reduced false event escalations by 20% and improved operational trust in the system.
- Deployed models into production by packaging them into modular inference services, integrated with monitoring dashboards that generated real-time alerts, audit logs, and forensic search tools for enterprise clients.
- Integrated a vector-store backend for embedding management, enabling efficient indexing, retrieval, and similarity search of feature embeddings in video streams, making ambiguous events searchable in sub-seconds.
- Designed and automated CI/CD pipelines with containerized workflows, reducing deployment cycles from 30 → 10 minutes and enabling 200+ production releases per month.
- Implemented observability pipelines (monitoring, logging, alerting) to track latency, failure rates, and resource utilization, ensuring stability under sustained high traffic.
- Trained convolutional VAEs to synthesize distribution-consistent samples, expanding a limited corpus from 50K → 150K examples while maintaining perceptual similarity (SSIM > 0.85).
- Benchmarked VQ-VAEs against Conv-VAEs for unsupervised representation learning, evaluating latent space structure, reconstruction error, and generative quality across heterogeneous datasets.
- Assisting Dr. Rose Yu at UC San Diego with various CV driven initiatives at her lab.
- Conducted research on DYffusion, a dynamics-informed diffusion model for spatiotemporal climate forecasting, focusing on improving uncertainty quantification and stochastic representation of geophysical processes.
- Implemented and evaluated an almost-fair CRPS loss function (adapted from recent literature) to address biases in standard CRPS variants, yielding a 10% gain in predictive accuracy while preserving calibrated uncertainty estimates.
- Ran large-scale distributed training of forecasting models using data-parallel strategies across multi-node GPU clusters, analyzing the effect of loss function choice, sampling strategies, and noise schedules on forecast stability and calibration.
- Spearheaded the design of a domain-adapted summarization system for research literature, integrating a BERT encoder with fine-tuned attention layers, achieving a 50% relative gain in ROUGE compared to traditional extractive methods.
- Conducted research on transformers and multi-head self-attention mechanisms, for enhanced language modeling.
- Developed a retrieval-augmented generation system for conversational search, combining vector similarity retrieval with LLM-based re-ranking to improve semantic relevance and reduce hallucinations.
- Accelerated query serving by implementing concurrent request handling and parallel execution across the API-database pipeline, improving throughput and reducing average response latency from 3s to 600ms.
- Optimized database and data pipelines for metadata (6M+ JSON records), restructuring queries and indexing strategies to reduce retrieval times and support real-time analytics workloads.
- Implemented efficient data preprocessing and visualization pipelines for insightful data handling, intuitive data exploration, and pattern analysis.
- Developed REST APIs and integrated them with various data sources, enabling real-time data updates and reducing data retrieval time by 40% for critical information.
- Pioneered innovative strategies in researching and crafting website content alongside esteemed senior colleagues, resulting in a remarkable surge of approximately 20% in website traffic.
- Collaborated dynamically with the marketing and content team to conceptualize and produce captivating infographics, proposals, and blog posts tailored for both B2B and B2C technology audiences.
- Orchestrated a creative revolution, spearheading the revitalization of the mobile application through imaginative content enhancements and comprehensive overhauls.
- Innovatively identified and rectified deficiencies within the content development support structure, optimizing workflow processes for enhanced efficiency.
- Collaborated synergistically with strategic planners, business stakeholders, and fellow creatives to ideate, conceptualize, and bring to life compelling brand narratives.