Dhwanit Agarwal, PhD

Machine Learning Engineer

San Jose, California, United States4 yrs 5 mos experience
Highly StableAI Enabled

Key Highlights

  • Holds 12+ AI patents contributing to significant revenue.
  • Published 7+ research papers in AI and Computational Sciences.
  • Expert in generative AI and multimodal models.
Stackforce AI infers this person is a SaaS expert specializing in AI-driven content generation and machine learning solutions.

Contact

Skills

Core Skills

Machine LearningComputer VisionAi ResearchNumerical AnalysisScientific ComputingData ScienceSoftware DevelopmentWeb Development

Other Skills

Generative searchvisual searchautocompleteLLMsVLMsdiffusiontext + images + videos generationVLM and diffusion modelsvLLMML and GenAI solutionsbusiness intelligence solutionspipeline building solutionsno-code platformspersonalized AI agentsdeep learning architectures

About

I work at the intersection of AI, Computer Vision, and Generative Content Creation — building systems that help machines see, understand, and generate. At Adobe Firefly, I focus on text-guided visual content generation and editing, combining research and engineering to push the boundaries of what's possible with GenAI. I hold 12+ AI patents and have published 7+ research papers across AI and Computational Sciences. Several of these patents are actively used by Adobe, contributing to multi-million dollar product revenues. My background blends mathematical rigor, scientific computing, and deep learning, shaped by a PhD in Computational Science from UT Austin and a Gold Medal in Mathematics from IIT Kanpur. As an active part of the research community, I regularly serve as a peer reviewer at venues including ECCV, WACV, KDD, AAAI, ICPP, CHIL and journals like Journal of Computational Physics, Journal of Supercomputing, Physical Review Fluids, and more. I also enjoy speaking at tech talks, judging hackathons, and mentoring students and early-career professionals. Whether it’s navigating the tech industry, exploring academic paths, or thinking through career and financial decisions, I focus on personalized, real conversations — not just lists or canned advice. If you’re organizing a tech event, need a peer reviewer, or are a reporter looking for insight into GenAI trends, feel free to reach out: dhwanit16@gmail.com. Core Focus Areas: ->Computer Vision & GenAI: Specializing in text-to-image generation and editing ->Multimodal AI & LLMs: Research + engineering across visual-linguistic models ->Numerical Analysis & Scientific Computing: Solving high-dimensional problems using ML and simulation ->Machine Learning Tools: PyTorch, Scikit-learn, R, CUDA, OpenMP, MPI, C++, Python, Matlab ->High-Performance Computing: Parallelized scientific simulations, GPU acceleration I’m always open to meaningful collaborations, technical discussions, and helping make AI more accessible through content and conversation.

Experience

4 yrs 5 mos
Total Experience
4 yrs
Average Tenure
5 mos
Current Experience

Coupang

Staff Machine Learning Engineer

Jan 2026Present · 5 mos · Mountain View, CA · Hybrid

  • Generative search, visual search and autocomplete. Post training LLMs, VLMs, diffusion
Generative searchvisual searchautocompleteLLMsVLMsdiffusion+2

Adobe

2 roles

Sr. Machine Learning Engineer / Tech Lead

Promoted

Jan 2022Jan 2026 · 4 yrs · San Jose, CA

  • Leading marketing quality content (text + images + videos) generation for Adobe GenStudio. Training VLM and diffusion models to evaluate, generate and fix visual content in an agentic fashion. Deploying them in an optimized fashion using vLLM.
  • 13+ patents and 7 papers related to Firefly, GenStudio, Acrobat AI Assistant and other topics in Comp Science. More to come as we work towards building GenAI for enterprises ...
  • CVPR paper: https://ui.adsabs.harvard.edu/abs/2023arXiv230305031R/abstract
  • CVPRW paper: One shot target and shape aware video editing using diffusion
  • Expert in ML and GenAI solutions like (controllable) image generation, prompt rewriting using LLM/VLMs, video generation, lipsync models using LatentSync, document cleaning using tesseract/ Restormer, on-brand models using custom LoRA/DoRA, custom scoring/eval models using large VLMs, business intelligence solutions like Snowflake and pipeline building solutions like Databricks, infrastructure solutions like RunAI, Modal, AWS/Azure, Baseten, strategy related to model moat, ML/LLM observability platforms like Arize, TrueEra, Datadog, industry trends in GenAI native SaaS related to upcoming startups like OpenAI, Anthropic, Midjourney, Runway, Hedra, BlackForestLabs, Morphic, HeyGen, ElevenLabs etc. I also pioneered the usage of personalized AI agents and do research on the no-code platforms which can help build superfast agents for your own use case. These include tools like n8n, Zapier and MindStudio. I also regularly delve into enterprise usage of no-code/low-code app builders like Lovable, Retool, v0 and Replit. I am also into analyzing the GenAI distribution platforms like Fal.ai/ Replicate, and comparing them with Firefly. I am also involved in continuous evaluation ai-dev-tools like Cursor, Windsurf, MS copilot and coupling Claude Code with Cursor/Windsurf etc.
text + images + videos generationVLM and diffusion modelsvLLMML and GenAI solutionsbusiness intelligence solutionspipeline building solutions+3

Data Scientist

Jan 2021Jan 2021 · 0 mo · San Jose, California, United States

  • State-of-the art deep learning architectures for multimodal translation (text assisted image manipulation).
deep learning architecturesmultimodal translationimage manipulationMachine LearningComputer Vision

Simons foundation

Computational Scientist

Jun 2020Aug 2020 · 2 mos · Manhattan, New York, United States

  • Fast boundary integral solvers for PDEs. Wrote parallel high order solver for solving Laplace Beltrami PDE.
boundary integral solversPDEsparallel high order solverNumerical AnalysisScientific Computing

Adobe

Machine Learning Engineer

Jan 2014Jan 2014 · 0 mo · Bangalore

  • Part of a team of 3 that developed a novel and a complete framework named EnTwine for
  • identity resolution in online social networks and consequently creating a unified user prole
  • by aggregating user information across networks
  • Developed a new method for prior feature analysis using statistical methods instead of domain
  • knowledge and heuristics
  • Introduced a clustering step and provide two alternate ways to do it: one is a slight mod-
  • ification of an existing clustering method called canopy clustering and other being a novel
  • clustering algorithm in order to reduce space complexity of this step, both using results from
  • the feature analysis step
  • Hence providing a two phase solution to the identity resolution problem, first phase being
  • candidate selection and the other being user identification
  • Developed a new method based on Poisson Binomial Distribution and output probabilities of
  • the classifier in the EnTwine framework to get an estimate of matching users
identity resolutionstatistical methodsclustering algorithmsMachine LearningData Science

Purplle.com

Software Engineer

May 2013Jun 2013 · 1 mo · Mumbai Area, India

  • Designed and implemented the mobile application for Purplle.com Salon and Spa Finder
  • Part of team of 2 that designed and implemented the entire modular schema of the following features , using MVC architecture in Codeigniter Framework of PHP
  • Completed Project Entailed Working on the following features –Venue Listing Refinement(Filtering), Reviews Module, Venue Tagging module and Automated Ad Tracking Module
  • Optimization of MySQL Database using the best practices(Indexing, Slow Query optimization etc)
  • Developed ERP module for Automated Ad tracking System and Venue Tagging
mobile application designMVC architectureMySQL optimizationSoftware DevelopmentWeb Development

Education

Indian Institute of Technology, Kanpur

Bachelor of Science (BS) — Mathematics

The University of Texas at Austin

Doctor of Philosophy - PhD — Computational and Applied Mathematics

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