Haris Vikalo
Professor
Works on machine learning and signal processing, including federated learning and computational methods for genomics.
Haris Vikalo's lab at UT Austin works on trustworthy & safe ML, signal processing & information theory and speech enhancement & signal processing. 31 papers since 2023, 14 at top venues, mostly NeurIPS and ICLR. 6 PhD students. 13 alumni, most often to Qualcomm and Google. Applications close .
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 45%
- PhD students
- 6
- MS students
- 0
- alumni listed
- 13
Papers by yearfrom the lab homepage, 2023–2026
- 12 papers2026 · T1 6 · collecting
- 7 papers2025 · T1 2
- 6 papers2024 · T1 5
- 6 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, ICLR, ICML, AAAI, CVPR
Research focuspaper titles that use each topic's words
- federated learning10 papers
- Signal processing & information theory1 paper
- Speech enhancement & signal processing1 paper
- Trustworthy & safe ML0 papers
- computational methods0 papers
Paper list
From the lab homepage.
202612 papers
- FLICSAdaptive Evolutionary Clustering for Federated Learning under Nonstationary Client Distributions
- NeurIPS (T1)CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization
- ICML (T1)FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA
- IEEE ICMLCNJoint Model Onloading and Offloading for Hierarchical Multi-Task Inference
- NeurIPS (T1)Long-Lived AI Agents Age Too: They Quietly Decay After Deployment
- IEEE AccessManaging task offloading in viewport prediction via reinforcement learning
- IEEE ICMLCNOptimal Resource Allocation for ML Model Training and Deployment under Concept Drift
- FLICSPRISM-AMC: Replay-Free Continual Learning for Automatic Modulation Classification
- ICLR (T1)Quantized Gradient Projection for Memory-Efficient Continual Learning
- CVPR WorkshopTraining-Free Layout-to-Image Generation with Marginal Attention Constraints
- TMLR (T1)Transformers as Implicit State Estimators: In-Context Learning in Dynamical Systems
- NeurIPS (T1)When Is Rank-1 Steering Cheap? Geometry, Granularity, and Budgeted Search
20257 papers
- TAC (T1)Accelerated distributed stochastic non-convex optimization over time-varying directed networks
- IEEE Journal of Selected Topics in Signal ProcessingFederated Learning at Scale: Addressing Client Intermittency and Resource Constraints
- SPAWCFederated self-supervised learning for automatic modulation classification in heterogeneous settings
- PLoS Computational BiologyNextVir: Enabling classification of tumor-causing viruses with genomic foundation models
- ICASSP (T1)Super capacity SRS design for 5G and beyond using channel in-painting
- IEEE Networking LettersViewport prediction via adaptive edge offloading
- Journal of Computational BiologyXVir: A transformer-based architecture for identifying viral reads from cancer samples
20246 papers
- AAAI (T1)Fed-QSSL: A framework for personalized federated learning under bitwidth and data heterogeneity
- NeurIPS (T1)Heterogeneity-guided client sampling: Towards fast and efficient non-IID federated learning
- CVPR (T1)Mixed-precision quantization for federated learning on resource-constrained heterogeneous devices
- INFOCOM (T1)Optimization of offloading policies for accuracy-delay tradeoffs in hierarchical inference
- ICML (T1)Recovering labels from local updates in federated learning
- Pattern RecognitionReducing communication in federated learning via efficient client sampling
20236 papers
- IEEE Open Journal of Intelligent Transportation SystemsAutomotive RADAR sub-sampling via object detection networks: Leveraging prior signal information
- CVPR WorkshopFederated learning in non-IID settings aided by differentially private synthetic data
- IEEE Journal of Selected Topics in Signal ProcessingFederated learning under intermittent client availability and time-varying communication constraints
- Journal of Computational BiologyGraph-based reconstruction and analysis of disease transmission networks using viral genomic data
- ICLR (T1)The best of both worlds: Accurate global and personalized models through federated learning with data-free hyper-knowledge distillation
- Bioinformatics AdvancesXHap: Haplotype assembly using long-distance read correlations learned by transformers
Where alumni went13 listed, 71% to industry
Industry 5Academia 2
Most often to
- Qualcomm
- Microsoft
Also to
- Korea University
- USC
Apply to UT AustinFall 2027
Computer Science PhD
- Round
- Single round (Dec 15)
- Opens
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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