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Mohit Tawarmalani

Mohit Tawarmalani

· Executive Associate Dean of Strategy, Research, and Innovation Allison & Nancy Schleicher Chair Professor

Purdue University · Quantitative Methods

Active 1999–2026

h-index29
Citations5.4k
Papers13142 last 5y
Funding$827k

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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Research topics

  • Engineering
  • Mathematics
  • Computer Science
  • Statistics
  • Chemistry
  • Physics
  • Materials science
  • Computer network
  • Pulp and paper industry
  • Petroleum engineering

Selected publications

  • Systematic Analysis Reveals Thermal Separations Are Not Necessarily Most Energy Intensive

    Joule · 2020 · 45 citations

  • Advances in distillation: Significant reductions in energy consumption and carbon dioxide emissions for crude oil separation

    Joule · 2022 · 29 citations

  • PCF

    2020 · 24 citations

    Senior authorCorresponding

    Recently, traffic engineering mechanisms have been developed that guarantee that a network (cloud provider WAN, or ISP) does not experience congestion under failures. In this paper, we show that existing congestion-free mechanisms, notably FFC, achieve performance far short of the network's intrinsic capability. We propose PCF, a set of novel congestion-free mechanisms to bridge this gap. PCF achieves these goals by better modeling network structure, and by carefully enhancing the flexibility of…

  • Cogeneration Improves Separation Efficiency

    Industrial & Engineering Chemistry Research · 2024-10-18 · 10 citations

    article

    For most distillation systems, the heat pump (HP) compressor, upgrading the heat from the condenser’s lower temperature to the reboiler’s higher temperature, uses electrical energy that is only a fraction of the reboiler heat, thereby making such processes highly efficient. However, the electricity utilized to power the HP compressor is typically dissipated as waste heat in cooling water. Here, we propose a novel strategy termed “Separation Cogeneration” whereby most of the electrical energy sup…

  • Transferable Neural WAN TE for Changing Topologies

    2024-07-31 · 7 citations

    articleOpen accessSenior author

    Recently, researchers have proposed ML-driven traffic engineering (TE) schemes where a neural network model is used to produce TE decisions in lieu of conventional optimization solvers. Unfortunately existing ML-based TE schemes are not explicitly designed to be robust to topology changes that may occur due to WAN evolution, failures or planned maintenance. In this paper, we present HARP, a neural model for TE explicitly capable of handling variations in topology including those not observed in…

Recent grants

Frequent coauthors

  • Rakesh Agrawal

    Purdue University West Lafayette

    42 shared
  • Nikolaos V. Sahinidis

    Georgia Institute of Technology

    33 shared
  • Jean‐Philippe P. Richard

    University of Minnesota

    18 shared
  • Sanjay Rao

    Purdue University West Lafayette

    13 shared
  • Gautham Madenoor Ramapriya

    11 shared
  • Radhakrishna Tumbalam Gooty

    11 shared
  • Tony Joseph Mathew

    Purdue University West Lafayette

    10 shared
  • Taotao He

    8 shared

Education

  • PhD Industrial Engineering, Mechanical and Industrial Engineering

    University of Illinois Urbana-Champaign

    2001
  • MS Industrial Engineering, Mechanical and Industrial Engineering

    University of Illinois Urbana-Champaign

    1997
  • BTech Mechanical Engineering, Mechanical Engineering

    Indian Institute of Technology Delhi

    1993

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