Feras Saad
Assistant Professor
Develops probabilistic programming languages and systems for probabilistic modeling and inference.
Feras Saad's lab at CMU works on probabilistic & causal inference, efficient training & inference and compilers & programming languages. 12 papers since 2023, 6 at top venues, mostly PLDI and ICML. 2 alumni. Applications close .
At a glance
- papers, 2023–2026
- 3/ year
- at T1 venues
- 50%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 2
Papers by yearfrom the lab homepage, 2023–2026
- 3 papers2026 · T1 2 · collecting
- 3 papers2025 · T1 1
- 5 papers2024 · T1 2
- 1 papers2023 · T1 1
T1 venuesOtherVenues: PLDI, ICML, SODA
Research focuspaper titles that use each topic's words
- Probabilistic & causal inference5 papers
- Efficient training & inference4 papers
- probabilistic3 papers
- Compilers & programming languages2 papers
- programming languages0 papers
Paper list
From the lab homepage.
20263 papers
- SODA (T1)Efficient Online Random Sampling via Randomness Recycling
- IEEE Transactions on Information TheoryEfficient Rejection Sampling in the Entropy-Optimal Range
- PLDI (T1)GradInf: Gradient Estimation as Probabilistic Inference
20253 papers
- CAV, Proc. International Conf. on Computer Aided VerificationFloating-Point Neural Networks Are Provably Robust Universal Approximators
- OOPSLA, Proc. ACM Program. Lang. 9Integrating Resource Analyses via Resource Decomposition
- PLDI (T1)Random Variate Generation with Formal Guarantees
20245 papers
- PLDI (T1)GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables
- AccMLBio, ICML Workshop on Efficient and Accessible Foundation Models for Biological DiscoveryLearning Generative Population Models From Multiple Clinical Datasets via Probabilistic Programming
- OOPSLA, Proc. ACM Program. Lang. 8(OOPSLA2)Programmable MCMC with Soundly Composed Guide Programs
- PLDI (T1)Robust Resource Bounds with Static Analysis and Bayesian Inference
- Nature Communications 15(7942)Scalable Spatiotemporal Prediction with Bayesian Neural Fields
20231 paper
- ICML (T1)Sequential Monte Carlo Learning for Time Series Structure Discovery
Where alumni went2 listed, 0% to industry
Industry 0Academia 1
Apply to CMUFall 2027
CMU SCS Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL / IELTS / Duolingo (F-1/J-1 non-native speakers)
- Fee
- USD 100 (USD 80 by early deadline)
Confirmed on the program page.
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Data
Checked against the lab homepage.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
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