Mohit Tawarmalani
· Executive Associate Dean of Strategy, Research, and Innovation Allison & Nancy Schleicher Chair ProfessorPurdue University · Quantitative Methods
Active 1999–2026
Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.
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
Joule · 2022 · 29 citations
2020 · 24 citations
Senior authorCorrespondingRecently, 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
articleFor 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 authorRecently, 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
NSF · $226k · 2012–2016
NSF · $396k · 2017–2022
NSF · $204k · 2009–2013
Frequent coauthors
- 42 shared
Rakesh Agrawal
Purdue University West Lafayette
- 33 shared
Nikolaos V. Sahinidis
Georgia Institute of Technology
- 18 shared
Jean‐Philippe P. Richard
University of Minnesota
- 13 shared
Sanjay Rao
Purdue University West Lafayette
- 11 shared
Gautham Madenoor Ramapriya
- 11 shared
Radhakrishna Tumbalam Gooty
- 10 shared
Tony Joseph Mathew
Purdue University West Lafayette
- 8 shared
Taotao He
Education
- 2001
PhD Industrial Engineering, Mechanical and Industrial Engineering
University of Illinois Urbana-Champaign
- 1997
MS Industrial Engineering, Mechanical and Industrial Engineering
University of Illinois Urbana-Champaign
- 1993
BTech Mechanical Engineering, Mechanical Engineering
Indian Institute of Technology Delhi
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