Education, Licensure and Certification
Ph.D.
Computer Science and Engineering
University of Michigan, Ann Arbor
1989
M.S.E.
Computer Engineering
University of Michigan, Ann Arbor
1986
B.Tech.
Electrical Engineering
Indian Institute of Technology
1984
Biography
Areas of Expertise
Accomplishments
Vilas Distinguished Achievement Professor
University of Wisconsin, Madison
2017
Electrical and Computer Engineering’s Outstanding Assistant Professor Mentor Award
2025
Affiliations
- Institute of Electrical and Electronics Engineers : Fellow
- Association of Computing Machinery (ACM)
Social
Media Appearances
Foxconn Plans to Make 'Digital Infrastructure Hardware' in Wisconsin — What's That?
PBS Wisconsin online
2021-05-10
Parmesh Ramanathan is a professor of electrical and computer engineering at the University of Wisconsin-Madison whose research centers on improving wireless networks and electric grids through new technologies. He said digital infrastructure hardware can include any number of products that support contemporary digital needs, which increasingly depend on internet-connected devices relaying information back and forth via vast off-site collections of servers called data centers.
Patents
Encrypted Digital Circuit Description Allowing Singal Delay Simulation
US Patent 9,960,910
2018
Migrating applications across a group of personal mobile devices based on battery usage
US Patent 9,513,696
2016
Encrypted Digital Circuit Description Allowing Circuit Simulation
US Patent 9,390,292
2016
Research Grants
Chromatin and epigenetic engineering with synthetic genome regulators
National Science Foundation
October 2019–September 2024
Harnessing mobile ad hoc networks to improve vulnerable road user safety
Federal Highway Administration
October 2018–September 2024
NeTS:SHF:Medium:Collaborative Research: Integrated Design and Optimization of MillimeterWave Multi-Beam MIMO Networks for Gigabit Mobile Access
National Science Foundation
June 2017–May 2023
Selected Publications
MIQA: An Application Agent for Immersive Content Delivery Over Millimeter Waves
IEEE Transactions on Mobile ComputingZongshen Wu, Chin-Ya Huang, Parameswaran Ramanathan
2024
The highly directional nature of the millimeter wave (mmWave) beams causes several challenges in using that spectrum to meet the communication demands of immersive applications. The mmWave beams are especially susceptible to misalignments and blockages caused by user movements. As a result, mmWave channels are vulnerable to large quality fluctuations, which in turn, degrades the end-to-end performance of immersive applications. In this paper, we propose a reinforcement learning (RL) based application-layer plugin that works in conjunction with the QUIC protocol to combat the challenges of mmWave networks. The plug-in called Millimeter wave based Immersive QUIC Agent (MIQA) uses the RL model to help modulate the sending rate along with the congestion control scheme of QUIC.
Hidden modes of DNA binding by human nuclear receptors
Nature CommunicationsDevesh Bhimsaria, José A Rodríguez-Martínez, Jacqui L Mendez-Johnson, Debostuti Ghoshdastidar, Ashwin Varadarajan, Manju Bansal, Danette L Daniels, Parameswaran Ramanathan, Aseem Z Ansari
2023
Human nuclear receptors (NRs) are a superfamily of ligand-responsive transcription factors that have central roles in cellular function. Their malfunction is linked to numerous diseases, and the ability to modulate their activity with synthetic ligands has yielded 16% of all FDA-approved drugs. NRs regulate distinct gene networks, however they often function from genomic sites that lack known binding motifs. Here, to annotate genomic binding sites of known and unexamined NRs more accurately, we use high-throughput SELEX to comprehensively map DNA binding site preferences of all full-length human NRs, in complex with their ligands. Furthermore, to identify non-obvious binding sites buried in DNA–protein interactomes, we develop MinSeq Find, a search algorithm based on the MinTerm concept from electrical engineering and digital systems design.
Measuring millimeter wave based link bandwidth fluctuations during indoor immersive experience
IEEE Networking LettersZongshen Wu, Chin-Ya Huang, Parameswaran Ramanathan
2022
This letter presents the results of motion-tracking synchronized millimeter wave (mmWave) link bandwidth fluctuations while a user is engaged in immersive augmented/virtual reality applications. Our system, called MITRAS, supports extensive exploration of human-induced impacts on mmWave link bandwidth during immersive experience. MITRAS adopts the packet train measurement application to track link bandwidth fluctuations. Meanwhile, the user movements are tracked using an Oculus Quest 2 headset. Through investigating the impacts of human movements on link bandwidth fluctuations, we further propose a link state prediction model to shed light on higher layer protocol design for immersive applications over mmWave links.
Active and machine learning-based approaches to rapidly enhance microbial chemical production
Metabolic EngineeringPrashant Kumar, Paul A Adamczyk, Xiaolin Zhang, Ramon Bonela Andrade, Philip A Romero, Parameswaran Ramanathan, Jennifer L Reed
2021
In order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic models (e.g., kinetic/stoichiometric models of metabolism)—requiring many experimental datasets for their parameterization—while experimental methods may require screening large mutant libraries to explore the design space for the few mutants with desired behaviors. To address these limitations, we developed an active and machine learning approach (ActiveOpt) to intelligently guide experiments to arrive at an optimal phenotype with minimal measured datasets. ActiveOpt was applied to two separate case studies to evaluate its potential to increase valine yields and neurosporene productivity in Escherichia coli.
Fault Tolerant Lanczos Eigensolver via an Invariant Checking Method
Journal of Electronic TestingFelix Loh, Kewal K Saluja, Parameswaran Ramanathan
2021
An extensive survey of the literature shows that the Lanczos eigensolver is a popular iterative method for approximating a few maximal eigenvalues of a real symmetric matrix, particularly if the matrix is large and sparse. In recent years, graphics processing units (GPUs) have become a popular platform for scientific computing applications, many of which are based on linear algebra, and are increasingly being used as the main computational units in supercomputers. This trend is expected to continue as the number of computations required by scientific applications reach petascale and exascale range. In this paper, building on our earlier work , we investigate in detail the error checking mechanism for the Lanczos eigensolver. We identify a low cost invariant for efficient error checking, and through mathematical analysis determine the efficiency of our mechanism when used by the Lanczos eigensolver.
