Mohit Daga

I’ll be on the post-doc job market starting April 2026. If you have any pointers please drop a line to me at mdaga@kth.se or mohitdaga05@gmail.com. 

Working papers and pre-prints

• Thin Trees via k-Respecting Cut Identities
  under submission, subsumes the k-respecting identities note (ArXiv: 2210.13320)
  arxiv link, updated 14th October 2025
• Thin Trees beyond Laminar Families, coming soon

Research Themes

• Theme 1: Min-Cuts, applications in distributed computing, and approximation algorithms
  Leveraging graph cut techniques in the design and analysis of distributed protocols, and exploring applications in approximation algorithms, and structures like thin-trees.
• Theme 2: Local Information and Statistical Inference
  Using local observations to infer global structure and parameters.
• Theme 3: Systems Under Dynamic Stress
  Modeling local computing processes as dynamical systems under load.

Accepted / Published

• Error Bounds for Network Scale-Up Methods
  with Sergio Díaz-Aranda, Juan Marcos Ramirez, Mohit Daga, Jaya Prakash Champati, Jose Aguilar, Rosa E. Lillo, Antonio F. Anta
  ACM SIGKDD 2025
  [arXiv link / ACM]
  Applies local inference and probabilistic methods to error quantification in networked sampling.
• Distributed Small Cuts using Semigroups
  with John Augustine
  26th Int’l Conference on Distributed Computing and Networking (ICDCN 2025)
  [arxiv-link / ACM]
  Explores algebraic representations for distributed detection of sparse cuts.
• Distributed Edge Connectivity in Sublinear Time
  with Danupon Nanongkai, Monika Henzinger, Thatchaphol Saranurak
  ACM STOC 2019
  [arxiv link / ACM]
  Introduces first sublinear-time algorithms for certifying edge-connectivity in distributed settings.
• Methods and Systems for Assigning Resources to a Task
  with Manoj Gupta, Koyel Mukherjee, Shailesh Vaya
  US Patent US20170017522A1
  Patented work from Xerox Research India: FPTAS-based resource allocation in crowdsourced BPMN.
• 2-SiMDoM: A 2-Sieve Model for Detection of Mitosis in Multispectral Breast Cancer Imagery
  with Ardhendu S. Tripathi, Atin Mathur, Manohar Kuse, Oscar C. Au
  IEEE ICIP 2013
  IEEE Link
  Deep learning before its time: multispectral mitosis detection using sparse feature sieves.

Supervision: Master's Theses (KTH)

• Johan Ericsson:Gamma Random Variable Generation on GPUs
• Joakim Fjellborg:Off-road Vehicle Routing on GPUs
• Markus Newton Hedlin:Benchmarking Communication Protocols
• Anton Cakste:Unsupervised User Embeddings from Digital Logs
• Marcus Nordstedt:Cross-Lingual Readability via mBERT
• Valentin A. Laurent:TrOCR for Spanish Transfer
• Daniela Eklund:LLMs for Fitness Log Parsing
• Gabriel Christensson:Urban Traffic Condition Classification

• KDD 2025, Toronto, CA – Oral presentation
• ICDCN 2025, Hyderabad, IN – Oral presentation
• HALG 2019 in Copenhagen -- Poster Presentation
• ACM STOC 2019, Phoenix AZ, USA – Oral presentation
• HALG 2018 in Amsterdam – Participant
• FOCS 2018, Paris, FR – Participant
• Shonan Meeting on Distributed Graph Algorithms (Tokyo, Japan) – Invited Talk
• Hawaii Workshop on Parallel Algorithms and Data Structures (Hawaii, USA) – Invited Delegate

• Research Engineer, KTH Royal Institute of Technology (2021–present)
  Supervision of Master Theses.
• Research Intern, IMDEA Institute, Spain (Networks, May–Jul 2023) and (Softwares, Oct 25 - Jan 2026)
  Hosted by Prof. Antonio F. Anta and Dr. Jaya Champati. Supported by KTH Foundation Grant.
• Research Intern, CyStar Labs, IIT Madras, Chennai, India (Oct 24 - Mar 25)
  Hosted by John Augustine. Supported by KTH Foundation Grant.
• Research Intern, Xerox Research India (Summer 2015)