Pandarasamy Arjunan

39 papers Misc 3Journal 10Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	Misc	`conf`	Learning-Based Optimization of EV Routing with V2G Integration and On-the-Go Energy Harvesting. COMSNETS Risshab Srinivas Ramesh, Prasant Misra, Pandarasamy Arjunan
2026	Misc	`conf`	Privacy-Preserving Energy Anomaly Detection using Federated Deep Autoencoders. COMSNETS Bhanu Kumar, Naman Srivastava, Priyanka Nihalchandani, Pandarasamy Arjunan
2025	—	`conf`	Are Time Series Foundation models good for Energy Anomaly Detection? e-Energy Basu Hela, Praveen Prasad Handigol, Pandarasamy Arjunan
2025	—	`conf`	Mix-BEATS: Mixer-enhanced Basis Expansion Analysis for Load Forecasting. e-Energy Anuj Kumar, Harish Kumar Saravanan, Shivam Dwivedi, Pandarasamy Arjunan
2024	—	`conf`	Analyzing the Performance of Time Series Foundation Models for Short-term Load Forecasting. BuildSys Harish Kumar Saravanan, Shivam Dwivedi, Pandarasamy Arjunan
2024	—	`conf`	Analyzing the Performance of Time Series Foundation Models for Short-term Load Forecasting. BuildSys Harish Kumar Saravanan, Shivam Dwivedi, P. Praveen, Pandarasamy Arjunan
2024	—	`conf`	BD3: Building Defects Detection Dataset for Benchmarking Computer Vision Techniques for Automated Defect Identification. BuildSys Praveen Kottari, Pandarasamy Arjunan
2024	—	`conf`	Enhanced Consumer Segmentation Through Load Profile Analysis Using Autoencoder and K-Shape Clustering. EI.A (1) P. Praveen, Patil Balachandra, Pandarasamy Arjunan
2024	J	`jnl`	Generative Adversarial Network with Soft-Dynamic Time Warping and Parallel Reconstruction for Energy Time Series Anomaly Detection. CoRR Hardik Prabhu, Jayaraman K. Valadi, Pandarasamy Arjunan
2023	J	`jnl`	District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images. CoRR Subin Lin, Vasantha Ramani, Miguel Martin, Pandarasamy Arjunan, Adrian Chong, Filip Biljecki, Marcel Ignatius, Kameshwar Poolla, Clayton Miller
2023	—	`conf`	Explainable AI for Energy Prediction and Anomaly Detection in Smart Energy Buildings. BuildSys Hardik Prabhu, Jayaraman K. Valadi, Pandarasamy Arjunan
2023	—	`conf`	Explainable Occupancy Prediction Using QLattice. BuildSys Ajith N. Nair, Harshwardhan Tanwar, Pandarasamy Arjunan, Prashant Anand, Ardeshir Mahdavi
2023	—	`conf`	Paddy Doctor: A Visual Image Dataset for Automated Paddy Disease Classification and Benchmarking. COMAD/CODS Petchiammal A, Briskline Kiruba S, D. Murugan, Pandarasamy Arjunan
2023	J	`jnl`	Semantic segmentation of longitudinal thermal images for identification of hot and cool spots in urban areas. CoRR Vasantha Ramani, Pandarasamy Arjunan, Kameshwar Poolla, Clayton Miller
2022	—	`conf`	BenchSys 2022: the first ACM SIGEnergy workshop on advancements in building energy benchmarking systems. BuildSys Balaji Kalluri, Jay Dhariwal, Pandarasamy Arjunan, Prashant Anand, Chirag Deb
2022	—	`conf`	Causal 1-D convolutional neural networks based chiller fault detection and diagnosis. BuildSys Pandarasamy Arjunan, Seshadhri Srinivasan, Kameshwar Poolla
2022	—	`conf`	FATEsys 2022: the second ACM SIGEnergy workshop on fair, accountable, transparent, and ethical (FATE) AI for smart environments and energy systems. BuildSys Milan Jain, Pandarasamy Arjunan
2022	J	`jnl`	LEAD1.0: A Large-scale Annotated Dataset for Energy Anomaly Detection in Commercial Buildings. CoRR Manoj Gulati, Pandarasamy Arjunan
2022	—	`conf`	LEAD1.0: a large-scale annotated dataset for energy anomaly detection in commercial buildings. e-Energy Manoj Gulati, Pandarasamy Arjunan
2022	J	`jnl`	Longitudinal thermal imaging for scalable non-residential HVAC and occupant behaviour characterization. CoRR Vasantha Ramani, Miguel Martin, Pandarasamy Arjunan, Adrian Chong, Kameshwar Poolla, Clayton Miller
2022	J	`jnl`	Paddy Doctor: A Visual Image Dataset for Paddy Disease Classification. CoRR Petchiammal A, Briskline Kiruba S, D. Murugan, Pandarasamy Arjunan
2022	—	`conf`	The way forward for building energy benchmarking in India. BuildSys Balaji Kalluri, Jay Dhariwal, Pandarasamy Arjunan, Prashant Anand, Chirag Deb
2022	—	`conf`	Trimming outliers using trees: winning solution of the large-scale energy anomaly detection (LEAD) competition. BuildSys Chun Fu, Pandarasamy Arjunan, Clayton Miller
2022	—	`conf`	XENIA: eXplainable ENergy informatics and attributes for building energy benchmarking. BuildSys Kevin Joshi, Arnab Jana, Pandarasamy Arjunan, Krithi Ramamritham
2022	—	`conf`	eptk: energy prediction toolkit. BuildSys Hardik Prabhu, Pandarasamy Arjunan
2021	J	`jnl`	Explainable AI for Chiller Fault-Detection Systems: Gaining Human Trust. Computer Seshadhri Srinivasan, Pandarasamy Arjunan, Baihong Jin, Alberto L. Sangiovanni-Vincentelli, Zuraimi Sultan, Kameshwar Poolla
2021	—	`conf`	FATEsys 2021: the first ACM SIGEnergy workshop on fair, accountable, transparent, and ethical (FATE) AI for smart environments and energy systems. BuildSys Milan Jain, Pandarasamy Arjunan
2021	—	`conf`	Operational characteristics of residential air conditioners with temporally granular remote thermographic imaging. BuildSys Pandarasamy Arjunan, Gregory Dobler, Kyungmin Lee, Clayton Miller, Filip Biljecki, Kameshwar Poolla
2020	J	`jnl`	The ASHRAE Great Energy Predictor III competition: Overview and results. CoRR Clayton Miller, Pandarasamy Arjunan, Anjukan Kathirgamanathan, Chun Fu, Jonathan Roth, June Young Park, Chris Balbach, Krishnan Gowri, Zoltán Nagy, Anthony Fontanini, Jeff Haberl
2019	J	`jnl`	EnergyStar++: Towards more accurate and explanatory building energy benchmarking. CoRR Pandarasamy Arjunan, Kameshwar Poolla, Clayton Miller
2016	—	`conf`	Collect, compare, and score: a generic data-driven anomaly detection method for buildings. e-Energy (Posters) Haroon Rashid, Pandarasamy Arjunan, Pushpendra Singh, Amarjeet Singh
2015	—	`conf`	E-Adivino: A Novel Framework for Electricity Consumption Prediction Based on Historical Trends. e-Energy Shubham Saini, Pandarasamy Arjunan, Amarjeet Singh, Ullas Nambiar
2015	—	`conf`	Multi-User Energy Consumption Monitoring and Anomaly Detection with Partial Context Information. BuildSys Pandarasamy Arjunan, Harshad D. Khadilkar, Tanuja Ganu, Zainul M. Charbiwala, Amarjeet Singh, Pushpendra Singh
2015	J	`jnl`	OpenBAN: An Open Building ANalytics Middleware for Smart Buildings. EAI Endorsed Trans. Scalable Inf. Syst. Pandarasamy Arjunan, Mani B. Srivastava, Amarjeet Singh, Pushpendra Singh
2015	—	`conf`	SensorAct: A Decentralized and Scriptable Middleware for Smart Energy Buildings. UIC/ATC/ScalCom Pandarasamy Arjunan, Manaswi Saha, Haksoo Choi, Manoj Gulati, Amarjeet Singh, Pushpendra Singh, Mani B. Srivastava
2013	—	`conf`	Experiences with Occupancy based Building Management Systems. ISSNIP Nipun Batra, Pandarasamy Arjunan, Amarjeet Singh, Pushpendra Singh
2012	Misc	`conf`	Fine-grained resource (electricity) management in buildings. COMSNETS Pandarasamy Arjunan
2012	—	`conf`	SensorAct: a privacy and security aware federated middleware for building management. BuildSys@SenSys Pandarasamy Arjunan, Nipun Batra, Haksoo Choi, Amarjeet Singh, Pushpendra Singh, Mani B. Srivastava
2011	—	`conf`	MELOS: a low-cost and low-energy generic sensing attachment for mobile phones. NSDR Abhishek Bhardwaj, Pandarasamy Arjunan, Amarjeet Singh, Vinayak S. Naik, Pushpendra Singh

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.