arXiv subjects

Anurag Gupta

Publications and source records attributed to Anurag Gupta.

At least 19 recordsLinked to original sources

arXiv2026

APEX-SWE

We introduce the AI Productivity Index for Software Engineering (APEX-SWE), a benchmark for assessing whether frontier AI models can execute economically valuable software engineering work. Unlike existing evaluations that focus on narrow, well-defined tasks, APEX-SWE assesses two novel task types that reflect real-world software engineering: (1) Integration tasks (n=100), which require constructing end-to-end systems across heterogeneous cloud primitives, business applications, and infrastructure-as-code services, and (2) Observability tasks (n=100), which require debugging production failures using telemetry signals such as logs and dashboards, as well as unstructured context. We evaluated eleven frontier models for the APEX-SWE leaderboard. Claude Opus 4.6 leads the APEX-SWE leaderboard with 40.5% Pass@1, followed by Claude Opus 4.5 at 38.7%. Our analysis shows that strong performance is primarily driven by epistemic discipline, defined as the capacity to distinguish between assumptions and verified facts. It is often combined with systematic verification prior to acting. We open-source the APEX-SWE evaluation harness and a dev set (n=50).

cs.SE↗

arXiv2026

MedTutor: A Retrieval-Augmented LLM System for Case-Based Medical Education

The learning process for medical residents presents significant challenges, demanding both the ability to interpret complex case reports and the rapid acquisition of accurate medical knowledge from reliable sources. Residents typically study case reports and engage in discussions with peers and mentors, but finding relevant educational materials and evidence to support their learning from these cases is often time-consuming and challenging. To address this, we introduce MedTutor, a novel system designed to augment resident training by automatically generating evidence-based educational content and multiple-choice questions from clinical case reports. MedTutor leverages a Retrieval-Augmented Generation (RAG) pipeline that takes clinical case reports as input and produces targeted educational materials. The system's architecture features a hybrid retrieval mechanism that synergistically queries a local knowledge base of medical textbooks and academic literature (using PubMed, Semantic Scholar APIs) for the latest related research, ensuring the generated content is both foundationally sound and current. The retrieved evidence is filtered and ordered using a state-of-the-art reranking model and then an LLM generates the final long-form output describing the main educational content regarding the case-report. We conduct a rigorous evaluation of the system. First, three radiologists assessed the quality of outputs, finding them to be of high clinical and educational value. Second, we perform a large scale evaluation using an LLM-as-a Judge to understand if LLMs can be used to evaluate the output of the system. Our analysis using correlation between LLMs outputs and human expert judgments reveals a moderate alignment and highlights the continued necessity of expert oversight.

cs.CL↗

arXiv2024

Bio-optical characterization using Ocean Colour Monitor (OCM) on board EOS-06 in coastal region

In ocean colour remote sensing, radiance at the sensor level can be modeled using molecular scattering and particle scattering based on existing mathematical models and gaseous absorption in the atmosphere. The modulation of light field by optical constituents within the seawater waters results in the spectral variation of water leaving radiances that can be related to phytoplankton pigment concentration, total suspended matter, vertical diffuse attenuation coefficients etc. Atmospheric correction works very well over open ocean using NIR channels of ocean colour sensors to retrieve geophysical products with reasonable accuracy while it fails over sediment laden and/or optically complex waters. To resolve this issue, a combination of SWIR channels or NIR-SWIR channels are configured in some ocean colour sensors such as Sentinel- OLCI, EOS- 06 OCM etc. Ocean Colour Monitor (OCM)-3 on board EOS -06 was launched on Nov 26, 2022. It has 13 bands in VNIR (400-1010 nm range) with ~1500 km swath for ocean colour monitoring. Arabian Sea near Gujarat coast is chosen as our study site to showcase the geophysical products derived using OCM-3 onboard EOS-06.

physics.ao-ph↗

arXiv2024

Non-Invasive Qualitative Vibration Analysis using Event Camera

This technical report investigates the application of event-based vision sensors in non-invasive qualitative vibration analysis, with a particular focus on frequency measurement and motion magnification. Event cameras, with their high temporal resolution and dynamic range, offer promising capabilities for real-time structural assessment and subtle motion analysis. Our study employs cutting-edge event-based vision techniques to explore real-world scenarios in frequency measurement in vibrational analysis and intensity reconstruction for motion magnification. In the former, event-based sensors demonstrated significant potential for real-time structural assessment. However, our work in motion magnification revealed considerable challenges, particularly in scenarios involving stationary cameras and isolated motion.

cs.NE↗

arXiv2024

Eclipse Attack Detection on a Blockchain Network as a Non-Parametric Change Detection Problem

This paper introduces a novel non-parametric change detection algorithm to identify eclipse attacks on a blockchain network; the non-parametric algorithm relies only on the empirical mean and variance of the dataset, making it highly adaptable. An eclipse attack occurs when malicious actors isolate blockchain users, disrupting their ability to reach consensus with the broader network, thereby distorting their local copy of the ledger. To detect an eclipse attack, we monitor changes in the Fréchet mean and variance of the evolving blockchain communication network connecting blockchain users. First, we leverage the Johnson-Lindenstrauss lemma to project large-dimensional networks into a lower-dimensional space, preserving essential statistical properties. Subsequently, we employ a non-parametric change detection procedure, leading to a test statistic that converges weakly to a Brownian bridge process in the absence of an eclipse attack. This enables us to quantify the false alarm rate of the detector. Our detector can be implemented as a smart contract on the blockchain, offering a tamper-proof and reliable solution. Finally, we use numerical examples to compare the proposed eclipse attack detector with a detector based on the random forest model.

cs.CR↗

arXiv2023

Fermi surface and band structure of BiPd from ARPES studies

We present a detailed electronic structure study of the non-centrosymmetric superconductor BiPd based on our angle resolved photoemission spectroscopy (ARPES) measurements and Density Functional Theory (DFT) based calculations. We observe a high intensity distribution on the Fermi surface (FS) of this compound resulting from various electron and hole like bands which are present in the vicinity of the Fermi energy (E$_f$). The near E$_f$ states are primarily composed of Bi-6p with a little admixture of Pd-4d$_{x^2-y^2/zy}$ orbitals. There are various spin-orbit split bands involved in the crossing of E$_f$ making a complex FS. The FS mainly consists of multi sheets of three dimensions which disfavor the nesting between different sheets of the FS. Our comprehensive study elucidates that BiPd could be a s-wave multiband superconductor.

cond-mat.supr-con↗

arXiv2023

Multiple-stopping time Sequential Detection for Energy Efficient Mining in Blockchain-Enabled IoT

What are the optimal times for an Internet of Things (IoT) device to act as a blockchain miner? The aim is to minimize the energy consumed by low-power IoT devices that log their data into a secure (tamper-proof) distributed ledger. We formulate a multiple stopping time Bayesian sequential detection problem to address energy-efficient blockchain mining for IoT devices. The objective is to identify $L$ optimal stops for mining, thereby maximizing the probability of successfully adding a block to the blockchain; we also present a model to optimize the number of stops (mining instants). The formulation is equivalent to a multiple stopping time POMDP. Since POMDPs are in general computationally intractable to solve, we show mathematically using submodularity arguments that the optimal mining policy has a useful structure: 1) it is monotone in belief space, and 2) it exhibits a threshold structure, which divides the belief space into two connected sets. Exploiting the structural results, we formulate a computationally-efficient linear mining policy for the blockchain-enabled IoT device. We present a policy gradient technique to optimize the parameters of the linear mining policy. Finally, we use synthetic and real Bitcoin datasets to study the performance of our proposed mining policy. We demonstrate the energy efficiency achieved by the optimal linear mining policy in contrast to other heuristic strategies.

cs.CR↗

arXiv2023

Controlling Transaction Rate in Tangle Ledger: A Principal Agent Problem Approach

Tangle is a distributed ledger technology that stores data as a directed acyclic graph (DAG). Unlike blockchain, Tangle does not require dedicated miners for its operation; this makes Tangle suitable for Internet of Things (IoT) applications. Distributed ledgers have a built-in transaction rate control mechanism to prevent congestion and spamming; this is typically achieved by increasing or decreasing the proof of work (PoW) difficulty level based on the number of users. Unfortunately, this simplistic mechanism gives an unfair advantage to users with high computing power. This paper proposes a principal-agent problem (PAP) framework from microeconomics to control the transaction rate in Tangle. With users as agents and the transaction rate controller as the principal, we design a truth-telling mechanism to assign PoW difficulty levels to agents as a function of their computing power. The solution of the PAP is achieved by compensating a higher PoW difficulty level with a larger weight/reputation for the transaction. The mechanism has two benefits, (1) the security of Tangle is increased as agents are incentivized to perform difficult PoW, and (2) the rate of new transactions is moderated in Tangle. The solution of PAP is obtained by solving a mixed-integer optimization problem. We show that the optimal solution of the PAP increases with the computing power of agents. The structural results reduce the search space of the mixed-integer program and enable efficient computation of the optimal mechanism. Finally, via numerical examples, we illustrate the transaction rate control mechanism and study its impact on the dynamics of Tangle.

cs.NI↗

arXiv2022

Singular Points and Singular Curves in von Kármán Elastic Surfaces

Mechanical fields over thin elastic surfaces can develop singularities at isolated points and curves in response to constrained deformations (e.g., crumpling and folding of paper), singular body forces and couples, distributions of isolated defects (e.g., dislocations and disclinations), and singular metric anomaly fields (e.g., growth and thermal strains). With such concerns as our motivation, we model thin elastic surfaces as von K{á}rm{á}n plates and generalize the classical von K{á}rm{á}n equations, which are restricted to smooth fields, to fields which are piecewise smooth, and can possibly concentrate at singular curves, in addition to being singular at isolated points. The inhomogeneous sources to the von K{á}rm{á}n equations, given in terms of plastic strains, defect induced incompatibility, and body forces, are likewise allowed to be singular at isolated points and curves in the domain. The generalized framework is used to discuss the singular nature of deformation and stress arising due to conical deformations, folds, and folds terminating at a singular point.

math-ph↗

arXiv2022

Defects and Metric Anomalies in Föppl-von Kármán Surfaces

A general framework is developed to study the deformation and stress response in F{ö}ppl-von K{á}rm{á}n shallow shells for a given distribution of defects, such as dislocations, disclinations, and interstitials, and metric anomalies, such as thermal and growth strains. The theory includes dislocations and disclinations whose defect lines can both pierce the two-dimensional surface and lie within the surface. An essential aspect of the theory is the derivation of strain incompatibility relations for stretching and bending strains with incompatibility sources in terms of various defect and metric anomaly densities. The incompatibility relations are combined with balance laws and constitutive assumptions to obtain the inhomogeneous F{ö}ppl-von K{á}rm{á}n equations for shallow shells. Several boundary value problems are posed, and solved numerically, by first considering only dislocations and then disclinations coupled with growth strains.

cond-mat.soft↗

arXiv2022

Some Consequences of the Distributional Stress Equilibrium Condition

We derive two consequences of the distributional form of the stress equilibrium condition while incorporating piecewise smooth stress and body force fields with singular concentrations on an interface. First we obtain the local equilibrium conditions in the bulk and at the interface, the latter including conditions on the interfacial stress and stress dipole. Second we obtain the necessary and the sufficient conditions on the divergence-free non-smooth stress field for there to exist a stress function field such that the equilibrium is trivially satisfied. In doing so we allow the domain to be non-contractible with mutually disjoint connected boundary components. Both derivations illustrate the utility of the theory of distributions in dealing with singular stress fields.

math-ph↗

arXiv2022

AutoTSG: Learning and Synthesis for Incident Troubleshooting

Incident management is a key aspect of operating large-scale cloud services. To aid with faster and efficient resolution of incidents, engineering teams document frequent troubleshooting steps in the form of Troubleshooting Guides (TSGs), to be used by on-call engineers (OCEs). However, TSGs are siloed, unstructured, and often incomplete, requiring developers to manually understand and execute necessary steps. This results in a plethora of issues such as on-call fatigue, reduced productivity, and human errors. In this work, we conduct a large-scale empirical study of over 4K+ TSGs mapped to 1000s of incidents and find that TSGs are widely used and help significantly reduce mitigation efforts. We then analyze feedback on TSGs provided by 400+ OCEs and propose a taxonomy of issues that highlights significant gaps in TSG quality. To alleviate these gaps, we investigate the automation of TSGs and propose AutoTSG -- a novel framework for automation of TSGs to executable workflows by combining machine learning and program synthesis. Our evaluation of AutoTSG on 50 TSGs shows the effectiveness in both identifying TSG statements (accuracy 0.89) and parsing them for execution (precision 0.94 and recall 0.91). Lastly, we survey ten Microsoft engineers and show the importance of TSG automation and the usefulness of AutoTSG.

cs.SE↗

arXiv2022

Sustainable AI: Environmental Implications, Challenges and Opportunities

This paper explores the environmental impact of the super-linear growth trends for AI from a holistic perspective, spanning Data, Algorithms, and System Hardware. We characterize the carbon footprint of AI computing by examining the model development cycle across industry-scale machine learning use cases and, at the same time, considering the life cycle of system hardware. Taking a step further, we capture the operational and manufacturing carbon footprint of AI computing and present an end-to-end analysis for what and how hardware-software design and at-scale optimization can help reduce the overall carbon footprint of AI. Based on the industry experience and lessons learned, we share the key challenges and chart out important development directions across the many dimensions of AI. We hope the key messages and insights presented in this paper can inspire the community to advance the field of AI in an environmentally-responsible manner.

cs.LG↗

arXiv2021

Principal Agent Problem as a Principled Approach to Electronic Counter-Countermeasures in Radar

Electronic countermeasures (ECM) against a radar are actions taken by an adversarial jammer to mitigate effective utilization of the electromagnetic spectrum by the radar. On the other hand, electronic counter-countermeasures (ECCM) are actions taken by the radar to mitigate the impact of electronic countermeasures (ECM) so that the radar can continue to operate effectively. The main idea of this paper is to show that ECCM involving a radar and a jammer can be formulated as a principal-agent problem (PAP) - a problem widely studied in microeconomics. With the radar as the principal and the jammer as the agent, we design a PAP to optimize the radar's ECCM strategy in the presence of a jammer. The radar seeks to optimally trade-off signal-to-noise ratio (SNR) of the target measurement with the measurement cost: cost for generating radiation power for the pulse to probe the target. We show that for a suitable choice of utility functions, PAP is a convex optimization problem. Further, we analyze the structure of the PAP and provide sufficient conditions under which the optimal solution is an increasing function of the jamming power observed by the radar; this enables computation of the radar's optimal ECCM within the class of increasing affine functions at a low computation cost. Finally, we illustrate the PAP formulation of the radar's ECCM problem via numerical simulations. We also use simulations to study a radar's ECCM problem wherein the radar and the jammer have mismatched information.

eess.SP↗

arXiv2021

Positive disclination in a thin elastic sheet with boundary

An isolated positive wedge disclination deforms an initially flat elastic sheet into a perfect cone when the sheet is of infinite extent and is elastically inextensible. The latter requires the elastic stretching strains to be vanishingly small. In this paper, rigorous analytical and numerical results are obtained for the disclination induced deformed shape and stress field of a bounded F{ö}ppl-von K{á}rm{á}n elastic sheet with finite extensibility, while emphasising the deviations from the perfect cone solution. In particular, the Gaussian curvature field is no longer localised as a Dirac singularity at the defect location whenever elastic extensibility is allowed and is necessarily negative in large regions away from the defect. The stress field, similarly, has no Dirac singularity in the presence of elastic extensibility. However, with increasing Young's modulus of the sheet, while keeping the bending modulus and the domain size fixed, both of these fields tend to develop a Dirac singularity. Noticeably, in this limiting behaviour, inextensibility eludes the bounded elastic sheet due to persisting regions of non-trivial Gaussian curvature away from the defect. Other results in the paper include studying the effect of specific boundary conditions (free, simply supported, or partially clamped) on the Gaussian curvature field away from the defect and on the buckling transition from the flat to a conical solution.

cond-mat.soft↗

arXiv2021

Point Singularities in Incompatible Elasticity

The equations of stress equilibrium and strain compatibility/incompatibility are discussed for fields with point singularities in a planar domain. The sufficiency (or insufficiency) of the smooth maps, obtained by restricting the singular fields to the domain away from the singularities, in completely characterizing the equations of equilibrium and compatibility/incompatibility over the entire domain, is established and illustrated with examples. The uniqueness of the solution to the stress problem of incompatible linear elasticity, allowing for singular fields, is proved. The uniqueness fails when the problem is considered solely in terms of the restricted maps. As applications of our framework, a general stress solution, in response to point supported body force and defect fields, is derived and a generalized notion of the force acting on a defect is developed.

math.AP↗

arXiv2021

Revisiting the topological classification of defects in crystals

A general theory of topological classification of defects is introduced. We illustrate the application of tools from algebraic topology, including homotopy and cohomology groups, to classify defects including several explicit calculations for crystals in $\mathbb{R}^2$, $S^2$, 2-dimensional cylinder, 2-dimensional annulus, and 2-tori. A set of physically motivated assumptions is formulated in order to justify the classification process and also to expose certain inherent inconsistencies in the considered methodology, particularly for crystal lattices.

math-ph↗

arXiv2020

Accessing topological surface states and negative MR in sculpted nanowires of Bi2Te3 at ultra-low temperature

Milling of 2D flakes is a simple method to fabricate nanomaterial of any desired shape and size. Inherently milling process can introduce the impurity or disorder which might show exotic quantum transport phenomenon when studied at the low temperature. Here we report temperature dependent weak antilocalization (WAL) effects in the sculpted nanowires of topological insulator in the presence of perpendicular magnetic field. The quadratic and linear magnetoconductivity (MC) curves at low temperature indicate the bulk contribution in the transport. A cusp feature in magnetoconductivity curves (positive magnetoresistance) at ultra low temperature and at magnetic field, less than 1T represent the WAL indicating the transport through surface states. The MC curves are discussed by using the 2D Hikami Larkin Nagaoka theory. The crossover interplay nature of positive and negative magnetoresistance observed in the MR curve at ultra low temperature. Our results indicate that transport through topological surface states (TSS) in sculpted nanowires of Bi2Te3 can be achieved at mK range and linear MR observed at 2 K could be the coexistence of electron transport through TSS and contribution from the bulk band.

cond-mat.mtrl-sci↗