Hanieh Hashemi @Haanie_h
Senior ML engineer @Apple. Passionate about privacy preserving ML and responsible AI. PhD from @USC. Ex research intern @AIatMeta and @Samsung Semi New York, NY Joined March 2024-
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We’re hiring! Join us in building the future of privacy at Apple. 🔹 Senior ML Engineer: lnkd.in/giyX_gbF 🔹 Senior iOS Engineer: lnkd.in/gsk__M5T Know someone great? I’d love to refer them.
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Hanieh Hashemi retweeted
We have a summer internship position on our team at Apple! If you’re passionate about differential privacy and other privacy-preserving techniques in ML, and eager to make a real-world impact, I’d love to see your CV!
Hanieh Hashemi retweeted
Today is Celebrating Women in Math Day! It's is the birthday of the late Maryam Mirzakhani who was the first women awarded the Fields Medal (2014). In celebration two new EvenQuads games have been released: Many Quads & Odd Quads. Check them out here: awm-math.org/publications/p…
Hanieh Hashemi retweeted
In the penultimate talk of day 1, Audra McMillan presents on private and federated heavy hitters.
Hanieh Hashemi retweeted
#icml2024 workshops list is up: icml.cc/virtual/2024/e…
Hanieh Hashemi retweeted
Apple announces MM1 Methods, Analysis & Insights from Multimodal LLM Pre-training In this work, we discuss building performant Multimodal Large Language Models (MLLMs). In particular, we study the importance of various architecture components and data choices. Through
Hanieh Hashemi retweeted
Congratulations to the 2024 cohort of AIML @Apple Scholars! machinelearning.apple.com/updates/apple-…
Hanieh Hashemi retweeted
Is Cosine-Similarity of Embeddings Really About Similarity? Netflix cautions against blindly using cosine similarity as a measure of semantic similarity between learned embeddings, as it can yield arbitrary and meaningless results. 📝arxiv.org/abs/2403.05440
Excited to see incredible keynote and Tutorial sessions 🤩 If you are interested to learn more about differentially private federated analytics, be sure to attend our team’s paper presentation on : “Differentially Private Heavy Hitter Detection using Federated Analytics”!
Excited to see incredible keynote and Tutorial sessions 🤩 If you are interested to learn more about differentially private federated analytics, be sure to attend our team’s paper presentation on : “Differentially Private Heavy Hitter Detection using Federated Analytics”!
Exciting news: #Apple has launched its first open-source framework for private federated learning! 🎉 A fantastic opportunity for researchers to explore and simulate their ideas in this field. #AI #ML #privacy #federated
Exciting news: #Apple has launched its first open-source framework for private federated learning! 🎉 A fantastic opportunity for researchers to explore and simulate their ideas in this field. #AI #ML #privacy #federated
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