Bandlimited field reconstruction from samples obtained on a discrete grid with unknown random locations. - Ankur Mallick; Animesh Kumar (ICASSP, 2016)

Bandlimited Field Reconstruction from Samples Obtained at Unknown Random Locations on a Grid. - Ankur Mallick; Animesh Kumar (CoRR, 2016)

Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication. - Ankur Mallick; Malhar Chaudhari; Gauri Joshi (CoRR, 2018)

Fast and Efficient Distributed Matrix-vector Multiplication Using Rateless Fountain Codes. - Ankur Mallick; Malhar Chaudhari; Gauri Joshi (ICASSP, 2019)

Rateless Codes for Distributed Computations with Sparse Compressed Matrices. - Ankur Mallick; Gauri Joshi (ISIT, 2019)

Deep Probabilistic Kernels for Sample-Efficient Learning. - Ankur Mallick; Chaitanya Dwivedi; Bhavya Kailkhura; Gauri Joshi; Thomas Yong-Jin Han (CoRR, 2019)

Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication. - Ankur Mallick; Malhar Chaudhari; Utsav Sheth; Ganesh Palanikumar; Gauri Joshi (Proc. ACM Meas. Anal. Comput. Syst., 2019)

Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning. - Ankur Mallick; Chaitanya Dwivedi; Bhavya Kailkhura; Gauri Joshi; Thomas Yong-Jin Han (CoRR, 2020)

Rateless Codes for Distributed Non-linear Computations. - Ankur Mallick; Sophie Smith; Gauri Joshi (ISTC, 2021)

Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation. - Divyansh Jhunjhunwala; Ankur Mallick; Advait Gadhikar; Swanand Kadhe; Gauri Joshi (NeurIPS, 2021)

Deep kernels with probabilistic embeddings for small-data learning. - Ankur Mallick; Chaitanya Dwivedi; Bhavya Kailkhura; Gauri Joshi; Thomas Yong-Jin Han (UAI, 2021)

Rateless Sum-Recovery Codes For Distributed Non-Linear Computations. - Ankur Mallick; Gauri Joshi (ITW, 2022)

Matchmaker: Data Drift Mitigation in Machine Learning for Large-Scale Systems. - Ankur Mallick; Kevin Hsieh; Behnaz Arzani; Gauri Joshi (MLSys, 2022)

Probabilistic Methods for Mitigating Uncertainties in Large-Scale Computing and Machine Learning - Ankur Mallick (2023)

Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing. - Dujian Ding; Ankur Mallick; Chi Wang 001; Robert Sim; Subhabrata Mukherjee; Victor Rühle; Laks V. S. Lakshmanan; Ahmed Hassan Awadallah (ICLR, 2024)

Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling. - Kunal Jain; Anjaly Parayil; Ankur Mallick; Esha Choukse; Xiaoting Qin; Jue Zhang; Íñigo Goiri; Rujia Wang; Chetan Bansal; Victor Rühle; Anoop Kulkarni; Steve Kofsky; et al. (CoRR, 2024)

EcoAct: Economic Agent Determines When to Register What Action. - Shaokun Zhang; Jieyu Zhang 001; Dujian Ding; Mirian Hipolito Garcia; Ankur Mallick; Daniel Madrigal; Menglin Xia; Victor Rühle; Qingyun Wu; Chi Wang 001 (CoRR, 2024)

Ensuring Fair LLM Serving Amid Diverse Applications. - Redwan Ibne Seraj Khan; Kunal Jain; Haiying Shen; Ankur Mallick; Anjaly Parayil; Anoop Kulkarni; Steve Kofsky; Pankhuri Choudhary; Renée St. Amant; Rujia Wang; Yue Cheng 001; Ali Raza Butt; et al. (CoRR, 2024)

Performance Aware LLM Load Balancer for Mixed Workloads. - Kunal Jain; Anjaly Parayil; Ankur Mallick; Esha Choukse; Xiaoting Qin; Jue Zhang; Íñigo Goiri; Rujia Wang; Chetan Bansal; Victor Rühle; Anoop Kulkarni; Steve Kofsky; et al. (EuroMLSys, 2025)

Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale. - Shashwat Jaiswal; Kunal Jain; Yogesh Simmhan; Anjaly Parayil; Ankur Mallick; Rujia Wang; Renée St. Amant; Chetan Bansal; Victor Rühle; Anoop Kulkarni; Steve Kofsky; Saravan Rajmohan (CoRR, 2025)

Exploring How LLMs Capture and Represent Domain-Specific Knowledge. - Mirian Hipolito Garcia; Camille Couturier; Daniel Madrigal Diaz; Ankur Mallick; Anastasios Kyrillidis; Robert Sim; Victor Rühle; Saravan Rajmohan (CoRR, 2025)

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search. - Dongge Han; Menglin Xia; Daniel Madrigal Diaz; Samuel Kessler; Ankur Mallick; Xuchao Zhang; Mirian del Carmen Hipolito Garcia; Jin Xu; Victor Rühle; Saravan Rajmohan (CoRR, 2025)

BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute. - Dujian Ding; Ankur Mallick; Shaokun Zhang; Chi Wang 001; Daniel Madrigal; Mirian del Carmen Hipolito Garcia; Menglin Xia; Laks V. S. Lakshmanan; Qingyun Wu; Victor Rühle (CoRR, 2025)

Tetris: Efficient Intra-Datacenter Calls Packing for Large Conferencing Services. - Rohan Gandhi; Ankur Mallick; Ken Sueda; Rui Liang (CoRR, 2025)