• PanoHair: detailed hair strand synthesis on volumetric heads 

  Verma, Shashikant; Raman, Shanmuganathan (Cornell University Library, 2025-08)

  Achieving realistic hair strand synthesis is essential for creating lifelike digital humans, but producing high-fidelity hair strand geometry remains a significant challenge. Existing methods require a complex setup for ...
• A comprehensive review of single-stage onboard chargers for light electric vehicles 

  Mir, Tanzeela; Bharadwaj, Pallavi (Institute of Electrical and Electronics Engineers, 2025-08)

  Electric vehicles (EVs) are revolutionizing the transportation landscape by replacing traditional internal combustion engine vehicles, thereby reshaping the future of mobility and playing an essential role in fostering a ...
• Asynchronous real-time learning in spiking neural network using 3-terminal resistance random access memory 

  Singh, Harshvardhan; Solanki, Nirmal; Maskeen, Jaskirat Singh; Lashkare, Sandip (Institute of Electrical and Electronics Engineers (IEEE), 2025-05)

  Spiking Neural Networks, inspired by the human brain, are promising as they attempt to solve real-life complex problems, such as pattern recognition, at low energy consumption. Resistance Random Access Memory (RRAM) crossbar ...
• Deep Bayesian optimization for high dimensional antenna design 

  Singh, Praveen; Hegde, Ravi S. (Institute of Electrical and Electronics Engineers (IEEE), 2025-04)

  We propose a novel scalable deep Bayesian optimization (BO) methodology for designing antennas with a large number of design degrees of freedom. Conventional BO approaches in antenna design has relied on Gaussian process ...
• STEP: simultaneous tracking and estimation of pose for animals and humans 

  Verma, Shashikant; Katti, Harish; Debnath, Soumyaratna; Swami, Yamuna; Raman, Shanmuganathan (Cornell University Library, 2025-03)

  We introduce STEP, a novel framework utilizing Transformer-based discriminative model prediction for simultaneous tracking and estimation of pose across diverse animal species and humans. We are inspired by the fact that ...
• MedFocusCLIP : improving few shot classification in medical datasets using pixel wise attention 

  Arora, Aadya; Namboodir, Vinay (Cornell University Library, 2025-01)

  With the popularity of foundational models, parameter efficient fine tuning has become the defacto approach to leverage pretrained models to perform downstream tasks. Taking inspiration from recent advances in large language ...
• WavShadow: wavelet based shadow segmentation and removal 

  Jain, Shreyans; Vekaria, Viraj; Gandhi, Karan; Arora, Aadya (Cornell University Library, 2024-11)

  Shadow removal and segmentation remain challenging tasks in computer vision, particularly in complex real world scenarios. This study presents a novel approach that enhances the ShadowFormer model by incorporating Masked ...
• Investigating metal dopants for lowering the contact resistance of top gold contacted monolayer MoS2 

  Kharwar, Saurabh; Sinha, Soham; Agarwal, Tarun (Cornell University Library, 2024-07)

  The interface properties between gold (Au) contacts and molybdenum disulfide (MoS2) are critical for optimizing the performance of semiconductor devices. This study investigates the impact of metal dopants (D) on the ...
• Polarized Raman analysis at low temperature to examine interface phonons in InAs/GaAs1-xSbx quantum dot heterostructures 

  Kumar, Priyesh; Deb, Sudip Kumar; Chakrabarti, Subhananda; Saha, Jhuma (Cornell University Library, 2024-09)

  An experimental study of optical phonon modes, both normal and interface (IF) phonons, in bilayer strain-coupled InAs/GaAs_(1-x)Sb_x quantum dot heterostructures has been presented by means of low-temperature polarized ...
• LIPIDS: learning-based illumination planning in discretized (light) space for photometric tereo 

  Tiwari, Ashish; Sutariya, Mihir; Raman, Shanmuganathan (Cornell University Library, 2024-09)

  Photometric stereo is a powerful method for obtaining per-pixel surface normals from differently illuminated images of an object. While several methods address photometric stereo with different image (or light) counts ...
• MERLiN: single-shot material estimation and relighting for photometric stereo 

  Tiwari, Ashish; Ikehata, Satoshi; Raman, Shanmuganathan (Cornell University Library, 2024-09)

  Photometric stereo typically demands intricate data acquisition setups involving multiple light sources to recover surface normals accurately. In this paper, we propose MERLiN, an attention-based hourglass network that ...
• IoT wearable sensors for automatic boxing punch recognition and classification based on upper limb biomechanics 

  Manoharan, Saravanan; Warburton, John; Hegde, Ravi S.; Srinivasan, Ranganathan; Srinivasan, Babji (MDPI, 2024-07)

  Identifying punch types as part of punch kinematic analysis is a key component for both coaches and players, providing critical insights into the variety and effectiveness of punches, which are essential for refining overall ...
• Leveraging eBPF and AI for ransomware nose out 

  Sekar, Arjun; Kulkarni, Sameer G.; Kuri, Joy (Cornell University Library, 2024-06)

  In this work, we propose a two-phased approach for real-time detection and deterrence of ransomware. To achieve this, we leverage the capabilities of eBPF (Extended Berkeley Packet Filter) and artificial intelligence to ...
• Rapid multi-objective inverse design of antenna via deep neural network surrogate-driven evolutionary optimization 

  Singh, Praveen; Panda, Soumyashree S.; Dash, Jogesh Chandra; Riscob, Bright; Pathak, Surya K.; Hegde, Ravi S. (Institute of Electrical and Electronics Engineers (IEEE), 2024-06)

  Antenna synthesis is becoming increasingly challenging given the tight requirements for C-SWAP (cost, size, weight and power) reduction while maintaining stringent electromagnetic performance specifications. While recent ...
• Quantifying spatial domain explanations in BCI using earth mover's distance 

  Rajpura, Param; Cecotti, Hubert; Meena, Yogesh Kumar (Cornell University Library, 2024-05)

  Brain-computer interface (BCI) systems facilitate unique communication between humans and computers, benefiting severely disabled individuals. Despite decades of research, BCIs are not fully integrated into clinical and ...
• Towards optimising EEG decoding using post-hoc explanations and domain knowledge 

  Rajpura, Param; Meena, Yogesh Kumar (Cornell University Library, 2024-05)

  Decoding EEG during motor imagery is pivotal for the Brain-Computer Interface (BCI) system, influencing its overall performance significantly. As end-to-end data-driven learning methods advance, the challenge lies in ...
• Controlling delegations in liquid democracy 

  Alouf-Heffetz, Shiri; Inamdar, Tanmay; Jain, Pallavi; More, Yash Hiren; Talmon, Nimrod (Cornell University Library, 2024-03)

  In liquid democracy, agents can either vote directly or delegate their vote to a different agent of their choice. This results in a power structure in which certain agents possess more voting weight than others. As a result, ...
• Arbitrary scale super-resolution assisted lunar crater detection in satellite images 

  Tewari, Atal; Khanna, Nitin (Cornell University Library, 2024-02)

  Craters are one of the most studied planetary features used for different scientific analyses, such as estimation of surface age and surface processes. Satellite images utilized for crater detection often have low resolution ...
• Non-toxic fabrication of fluorescent carbon nanoparticles from medicinal plants/sources with their antioxidant assay 

  Singh, Parul; Dan, Aniruddha; Kannan, Padma Priya; Dhanka, Mukesh; Bhatia, Dhiraj; Saha, Jhuma (Cornell University Library, 2024-01)

  This research work showcases a non-toxic approach to synthesize carbon nanoparticles (CNPs) from various medicinal plants namely Syzygium cumini, Holy basil, Azadirachta indica A, Psidium guajava, Mangifera indica, and ...
• Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space 

  Rajpura, Param; Cecotti, Hubert; Meena, Yogesh Kumar (Cornell University Library, 2023-12)

  This review paper provides an integrated perspective of Explainable Artificial Intelligence techniques applied to Brain-Computer Interfaces. BCIs use predictive models to interpret brain signals for various high-stake ...

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