جست‌وجوی استاد و پژوهشگر

Karthik P. N.مشاهده پروفایل

استادیار

• Probability Theory
• Detection and Estimation Theory
• Markov Decision Processes
• +۶ مورد دیگر

Karthik P. N. is an Assistant Professor in the Department of Artificial Intelligence at the Indian Institute of Technology Hyderabad (IIT Hyderabad). He previously served as a Research Fellow at the Institute of Data Science, National University of Singapore (NUS), and completed his Ph.D. and Master of Science (Engineering) at the Department of Electrical Communication Engineering, Indian Institute of Science (IISc), Bengaluru, under the guidance of Prof. Rajesh Sundaresan. Earlier, he worked as a Project Assistant in Prof. Chandra R. Murthy's lab at IISc and earned a Bachelor of Engineering in Electronics and Communications from R V College of Engineering, Bengaluru. Ph.D., Electrical Communication Engineering, IISc Bengaluru M.Sc. (Engineering), IISc Bengaluru B.E., Electronics and Communications, R V College of Engineering His research focuses on Probability Theory, Detection and Estimation Theory, Markov Decision Processes , and Multi-armed Bandits , with applications in Federated Learning, Differential Privacy, Reinforcement Learning, Information Theory , and Statistics . Recent work explores optimal strategies for best arm identification in restless bandits and privacy-preserving machine learning. He has received high instructor ratings for courses like Stochastic Processes and Programming for AI , and was honored with the Faculty Teaching Excellence Award 2025 at IIT Hyderabad. His Google Scholar articles highlight advances in 3D point cloud security, railway accident prevention, and vision-language model robustness . Scientific awards include the Faculty Teaching Excellence Award 2025 and First place in the INAE Kanpur Chapter 100 Seconds Competition (2021) . He collaborates with researchers like Prof. Vincent Y. F. Tan and Prof. Yeow Meng Chee, and has served on technical program committees for conferences such as APWDSIT 2025 and ISIT 2025 . Teaching roles at IIT Hyderabad involve graduate-level courses on Probability and Stochastic Processes , cross-listed with Electrical Engineering.

Ketan P. Detrojaمشاهده پروفایل

دانشیار

• Control Theory
• State Estimation
• Fault Diagnosis
• +۹ مورد دیگر

Ketan P. Detroja is an Associate Professor in the Department of Electrical Engineering at Indian Institute of Technology Hyderabad . With a Ph.D. from IIT Bombay (2006) and a specialization in Multivariable Control, Distributed State Estimation, and AI/ML for Control Applications , his research focuses on ensuring fault-tolerant and economical operation of microgrids , developing distributed Kalman filtering techniques , and applying machine learning to process monitoring and control . Education: B.E., D. D. Institute of Technology, Gujarat, India Ph.D., IIT Bombay, 2006 Research Interests span Advanced Process Control, Fault Detection and Diagnosis, Cooperative Control, Microgrid Optimization and Control , and Hardware-Software Design for Control Systems . His work addresses challenges in data-driven process monitoring , distributed state estimation , and machine learning-based controller design , particularly for large-scale systems. Scientific Contributions include innovative approaches to inverse-free Kalman filters , reinforcement learning-based PI controllers , and data reduction algorithms for fault diagnosis. His publications reflect a focus on control theory, optimization, and machine learning integration , with applications in power systems, wind energy, and fault diagnostics . Scientific Awards: Best Paper Award at ADCONIP - 2011 Best Paper Award at DYCOPS-2013 Advising has been a significant part of his career, with supervision of Ph.D. students working on topics like fault detection in induction motors , microgrid scheduling , and adaptive control using fuzzy logic . His M.Tech students have explored areas such as visual object tracking, battery SOC estimation, and wind farm control , many of whom are now in prominent roles across academia and industry.

Devlina Chatterjeeمشاهده پروفایل

استاد

• Managerial Economics
• Applied Econometrics
• Consumer finance
• +۳ مورد دیگر

Dr. Devlina Chatterjee is a Professor in the Department of Management Sciences at the Indian Institute of Technology Kanpur. With a strong academic background including a PhD in Management Studies from IISc Bangalore and dual MS degrees from Penn State University, she has established herself as a prominent researcher in Managerial Economics and Applied Econometrics. Her primary research interests span Consumer finance, tourism economics, resilience of social systems, and empirical finance. Dr. Chatterjee's work explores critical aspects of financial behavior in Indian contexts, insurance markets, tourism sector vulnerabilities, and stock market dynamics. Her research methodology combines rigorous econometric analysis with practical applications to real-world economic problems. Dr. Chatterjee has published extensively in high-impact journals including Tourism Management Perspectives, International Journal of Bank Marketing, and IIMB Management Review. Her recent work has focused on life insurance behavior in India, tourism economics, and financial decision-making patterns among Indian consumers. She has also contributed significantly to understanding the impact of natural disasters and conflicts on tourism sectors. The Indian Economic Association Medal for the academic year 2010-2011 (for best PhD Thesis) Best paper award at conference 'Forecasting Financial Markets in India', IIT Kharagpur, 2008 Second prize at Consortium of Students in Management Research COSMAR 2008 Green Belt Certification for Six Sigma Implementation at GE Capital Before joining academia, Dr. Chatterjee had substantial industry experience at Antrix Corporation (Department of Space), GE Capital, and Industrial Finance Corporation of India. She has supervised numerous research projects and continues to mentor students in the fields of econometrics and financial economics. Her teaching focuses on Managerial Economics and Econometrics, where she brings real-world applications to classroom learning.

Amarendra Kumar Singhمشاهده پروفایل

استاد

• Steel Refining and Casting
• Extractive Metallurgy
• Integrated Computational Materials Engineering
• +۴ مورد دیگر

Professor Amarendra Kumar Singh is a distinguished faculty member in the Department of Materials Science and Engineering at Indian Institute of Technology Kanpur, specializing in process modeling and simulation of metallurgical processes. With over three decades of academic and industrial experience, he has established himself as a leading expert in steel refining, solidification processing, and computational materials engineering. PhD, IIT Kanpur, 2003 PG, IIT Kanpur, 1990 UG, IIT Kanpur, 1987 Dr. Singh's research focuses on Steel Refining and Casting, Extractive Metallurgy, Integrated Computational Materials Engineering, Solidification Processing, and Sustainable Manufacturing. His work bridges fundamental scientific principles with practical industrial applications, particularly in the steel industry. He employs advanced computational techniques to model complex metallurgical processes, enabling optimization of manufacturing parameters and improvement of material quality. His research has significant implications for energy efficiency, environmental sustainability, and cost reduction in metal production. His publication record demonstrates a consistent trajectory of research excellence, with a focus on mathematical modeling of steelmaking processes, solidification phenomena, and computational approaches to materials engineering. The publications span from fundamental studies of macrosegregation and solidification to applied research on ladle refining, electric arc furnaces, and inclusion engineering in steel. Recent work shows increasing integration of data science approaches with traditional materials modeling. Metallurgist of the Year Award, Ministry of Steel, Government of India, 2014 Distinguished Scientist Award, TCS, 2011 AICTE-INAE Distinguished Visiting Professor at IIT Bombay (2009-2012) Multiple Best Paper Awards from Indian Institute of Metals As a faculty member at IIT Kanpur, Dr. Singh has contributed significantly to academic programs, mentoring students, and advancing research in materials engineering. His professional affiliations with The Minerals, Metals and Materials Society (TMS), Indian Institute of Metals (IIM), Materials Research Society of India (MRSI), and Indian Society of Heat & Mass Transfer (ISHMT) reflect his standing in the academic community. His research has practical applications in industrial settings, particularly in the steel manufacturing sector where process optimization is critical for competitiveness.

Preethi Srivathsaمشاهده پروفایل

استادیار

• Computer Architecture
• Internet of Things
• Cyber Security
• +۴ مورد دیگر

Dr. Preethi Srivathsa is an Assistant Professor - Senior Scale in the School of Computer Engineering at Manipal Academy of Higher Education (MAHE), Bengaluru. She holds a B.Tech, M.Tech, and Ph.D. (awarded by Presidency University in 2022). Her academic career includes positions at Presidency University (2019-2023) and East Point College of Engineering (2008-2019). Her research focuses on: Computer architecture and low-power hardware design IoT applications and cyber-physical systems Cryptography and blockchain security Machine learning implementations in hardware FPGA-based accelerators and optimization techniques Her publication portfolio shows strong emphasis on hardware-efficient algorithms, cryptographic systems (especially elliptic curve applications in blockchain), and emerging IoT architectures. Recent work integrates machine learning with hardware acceleration for smart home systems and agricultural technology. Awards and recognitions: Best Paper Award at IEEE iSES-2021 for low-power sorter design Infosys Bronze Partner Faculty (2013) She has developed intellectual property including IoT-based monitoring systems and blockchain educational frameworks. Technical skills include Verilog, FPGA design, IoT platforms (Arduino/Raspberry Pi), and multiple programming languages.

Jyothi Veduradaمشاهده پروفایل

استادیار

• Compilers
• Program Analysis
• High-Performance Computing
• +۳ مورد دیگر

Jyothi Vedurada is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IIT Hyderabad). Her research focuses on compilers, program analysis, high-performance computing (HPC), and software engineering. Prior to joining IIT Hyderabad, she was a postdoctoral researcher at Microsoft Research Lab in Bangalore and worked as a Software Engineer at Hewlett Packard in Chennai. Her research spans four major areas: Compiler Optimizations : Developing global compiler optimizations for CPU-GPU heterogeneous systems to enhance performance across varied hardware environments. ML for PL : Leveraging AI to overcome scalability and semantic challenges in program analysis, with applications in bug detection, API misuse recommendation, and algorithm description generation for Jupyter notebooks. Parallelization : Designing efficient GPU algorithms for tasks like Approximate Nearest Neighbour search and subgraph isomorphism optimization, alongside developing the Tensor Transposition Library for GPUs (TTLG). Concurrency Testing : Creating systematic testing frameworks for concurrent systems, including language-agnostic libraries and mock storage systems to validate weak isolation levels in databases. Scientific Awards & Recognition : Distinguished Artifact Award at ECOOP 2025 Google Research exploreCSR Award (2021) Tata Consultancy Services PhD Fellowship ACM SIGAI, SIGPLAN, and IEEE Travel Grants Advising & Collaborations : Supervising 11 PhD and MTech students, including Soumik Kumar Basu and Karthik V, with projects spanning compiler optimizations, HPC, and AI-driven software analysis. Collaborating with institutions like Microsoft Research and IIT Madras.

Dinesh Acharya Uمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Image Processing
• +۴ مورد دیگر

Dinesh Acharya U serves as a Professor in the Department of Computer Science and Engineering at Manipal Institute of Technology, Manipal University. His academic leadership spans both foundational computer engineering and interdisciplinary medical applications, with research output consistently growing since 2006. Current affiliations include active roles at the School of Computer Engineering with verified ORCID profile (0000-0002-0304-4725) and institutional webpage. Research interests prominently feature Machine Learning (68% fingerprint weight), Data Mining (40%), and Medical Informatics applications. His work bridges computer science with healthcare challenges, particularly in neonatal sepsis detection, diabetic complications, and low-resource language processing. The research fingerprint shows strong emphasis on prediction (52%), algorithms (53%), and India -specific healthcare contexts (40%). Publication trends reveal accelerating output since 2018, with 12 papers in 2022 and continued productivity through 2025. Recent work demonstrates interdisciplinary convergence, particularly in Medical AI (neonatal sepsis, diabetic kidney disease) Natural language processing for low-resource languages Transformer-based architectures across domains Notable patterns include increasing clinical collaborations and emphasis on practical implementation tools. Professional recognition includes an h-index of 13 with 596 citations across 71 research outputs. Key distinctions: Scopus profile verification ORCID registration Multi-institutional collaborations evident in co-authorship Academic supervision and grant activity cannot be confirmed from available data, though 15+ recent publications suggest active research teams. Current projects appear focused on Medical diagnostic tool development Low-resource language technology Clinical decision support systems with evident laboratory infrastructure supporting computational healthcare research.

Amrita Bhattacharyaمشاهده پروفایل

دانشیار

• Computational materials science
• Charge and heat transport
• Defects in semiconductors
• +۷ مورد دیگر

Dr. Amrita Bhattacharya is an Associate Professor in the Department of Metallurgical Engineering and Materials Science at the Indian Institute of Technology Bombay (IIT Bombay). She has been a faculty member since December 2017, advancing to Associate Professor in May 2021. Prior to joining IIT Bombay, she held prestigious positions including Max Planck Postdoctoral Scientist at the Fritz Haber Institute in Germany and DST Inspire Faculty at the National Physical Laboratory in New Delhi. Her educational background includes a Ph.D. in Computational Physics from the Indian Association for the Cultivation of Science and an MSc in Physics from Burdwan University. Dr. Bhattacharya's research is focused on computational materials science, with core interests in: Charge and heat transport in thermoelectric materials Defects in semiconductors Magnetic structure in strongly correlated materials Quantum confinement effects in 2D planar nanomaterials (e.g., graphene, silicene, BN sheets) Machine learning applications for predicting physical properties of materials Development of computational methods for analyzing electronic and phononic properties Her recent publications reveal a strong trend toward high-throughput computational screening, machine learning of material properties (such as lattice thermal conductivity and zero-point energy), and the design of efficient thermoelectric materials like half-Heusler alloys and Bi2S3. Her work integrates density functional theory (DFT) with advanced transport models and data science to accelerate materials discovery. She has received several notable awards and recognitions: Max-Planck Postdoctoral Fellowship (2013–2016) DST Inspire Faculty Award (2015) DAAD Travel Grant (2016) Young Scientist Award, Materials Research Society India (2012) Kawazoe Best Poster Award, ACCMS-TM2DS, Bangalore (2012) DST Travel Grant (2011) Dr. Bhattacharya is actively involved in research funding and mentoring. She leads the Ab initio Computational Materials Simulation laboratory and has ongoing projects, including a BRNS-funded project on spin-orbit driven thermoelectric materials. She recruits Junior Research Fellows (JRFs) and postdoctoral researchers, indicating her active supervision of students and early-career scientists. She also contributes to method development in computational materials science, including coding tools for analyzing band structures, phonon properties, and elastic constants. She maintains a strong publication record in high-impact journals such as Physical Review Letters , ACS Applied Materials & Interfaces , Acta Materialia , and Journal of Materials Chemistry C .

Amit Mitraمشاهده پروفایل

استاد

• Statistical Signal Processing
• Time Series Analysis
• Financial Econometrics
• +۳ مورد دیگر

Amit Mitra is a Professor in the Department of Mathematics & Statistics at the Indian Institute of Technology Kanpur (IIT Kanpur), India. He has held academic positions at IIT Kanpur since 2005, progressing from Assistant Professor (2005-2007) to Associate Professor (2008-2012) and Professor (2012-present). Prior to this, he served as an Assistant Professor at IIT Bombay (2002-2005) and held research roles at the Reserve Bank of India (1996-2002). His international collaborations include visiting positions at Uppsala University (Sweden) and universities in Australia and Cyprus. His educational qualifications include: Ph.D. in Statistics from IIT Kanpur (1996) M.Sc. in Statistics from IIT Kanpur (1991) B.Sc. (Honors) in Statistics from the University of Calcutta (1988) Professor Mitra's research centers on statistical signal processing with emphasis on parameter estimation for nonlinear time series models, particularly chirp signals, and data mining of financial/economic time series. His work develops robust algorithms for signal model estimation using techniques like genetic algorithms, M-estimators, and wavelet filtering, with applications in radar, sonar, finance, and image processing. He has pioneered methods for 1D/2D chirp signal analysis and volatility modeling in econometrics. His 15 most recent publications (2018-2023) reveal a sustained focus on advanced parameter estimation for chirp and sinusoidal models, with increasing attention to computational efficiency and real-world applicability. Key trends include the development of robust M-periodogram approaches, asymptotic analysis of quantile estimators, and extensions to multidimensional signal processing—particularly for image applications through nonnegative matrix factorization. His scientific awards include: Excellence in Teaching Award (2019, IIT Kanpur) Distinguished Teacher Award (2010, IIT Kanpur) M. N. Murthy Award from the Indian Statistical Institute (2002) Postdoctoral award from Swedish Foundation for Strategic Research (2000) Research award from National Board for Higher Mathematics (1992) Professor Mitra has supervised 67 students including 3 PhD candidates (1 completed), 4 M.Tech students, and 59 Masters students across Mathematics, Economics, and Statistics programs. His applied work includes consultancy projects with Politis (Cyprus) on market data modeling, Retailzoom (Cyprus) on retail analytics, and QuantLink Solutions (USA) on data mining software development for financial applications. No specific research labs or teams are mentioned in the provided text, though his patent in image processing (US Patent 9,940,868) indicates collaborative work with engineers on real-time display systems.

Renuka Prabhuمشاهده پروفایل

استاد

• Computer Engineering
• Embedded Systems Security
• Automotive Cybersecurity
• +۳ مورد دیگر

Renuka Prabhu serves as a Professor in the School of Computer Engineering at Manipal Academy of Higher Education, where she maintains an active research profile with 31 publications and an h-index of 9 according to Scopus metrics. Her work bridges theoretical computer engineering with practical security applications in embedded systems. Her research specializes in: Automotive cybersecurity including car hacking simulation testbeds Object detection optimization for resource-constrained devices like Raspberry Pi Steganography and data security techniques In-vehicle network protocol analysis Recent publications (2024-2025) demonstrate a strong trajectory toward real-world embedded security solutions, particularly in automotive threat landscape evaluation and robotics vision systems. Her work consistently leverages Raspberry Pi platforms to develop accessible, practical implementations of complex security frameworks. No scientific awards were documented in the source material. Similarly, details regarding student advising relationships, research grants, or laboratory infrastructure were not provided in the available information.

Soumen Chakrabartiمشاهده پروفایل

استاد

• Graph Neural Networks
• Knowledge Graphs
• Natural Language Processing
• +۳ مورد دیگر

Soumen Chakrabarti is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. His work bridges graph theory, natural language processing, and knowledge representation, focusing on scalable solutions for complex information retrieval problems. He has held visiting positions at Carnegie-Mellon University and Google. Education: B.Tech from IIT Kharagpur, PhD from UC Berkeley Key research areas: Graph Neural Networks, Knowledge Graphs, Code-Switched Text Analysis, Temporal Reasoning His recent publications emphasize neural graph matching , code-switched NLP , and multi-modal QA systems , often integrating symbolic reasoning with deep learning. Awards include the WWW 1999 Best Paper Award and ECML/PKDD 2008 Best Student Paper . He leads projects like CRUSH4SQL for text-to-SQL parsing and CSAW for annotated web search. His lab collaborates with IBM and Google on graph representation learning and temporal knowledge graph completion.

Abir Deمشاهده پروفایل

استادیار

• Machine Learning
• Graph Neural Networks
• Data-efficient Learning
• +۳ مورد دیگر

Abir De is an Assistant Professor at the Department of Computer Science and Engineering, Indian Institute of Technology Bombay. His research focuses on designing machine learning models for structured objects like graphs and sets, emphasizing data-efficient learning and human-machine collaboration. Academic Rank: Assistant Professor Institution: Indian Institute of Technology Bombay Department: Computer Science and Engineering Research Interests : Differentiable surrogates for combinatorial graph algorithms (e.g., subgraph isomorphism detection) Data-efficient machine learning through strategic subset selection Neural models for submodular set functions Human-in-the-loop machine learning Information diffusion with capacity constraints Scientific Awards : Qualcomm Innovation Fellowship Winner (2022) and Superwinner (2023) Indian National Academy of Engineering Young Engineer Award (2021) Prof. Krithi Ramamritham Award for Creative Research (2020) Google India PhD Fellowship (2013) Advising and Community Contributions : Co-advising PhD students Indradyumna Roy and N Lokesh Program Co-chair of IndoML 2023 Co-organizer of CSE Research Symposium (2023) and SubSetML workshop (2021) Tutorial creator at AIML Systems Conference (2021) and AAAI (2022) Serving on Senior PC at AAAI (2022-2024), PC member at NeurIPS (2016-2023), and ICLR (2018-2023)

Giridhar Madrasمشاهده پروفایل

استاد

• Reaction Engineering
• Catalysis
• Environmental Applications
• +۸ مورد دیگر

Giridhar Madras is a Professor in the Department of Chemical Engineering at the Indian Institute of Technology Hyderabad. He earned his B.E. (1988) from Annamalai University, M.Tech (1990) from IIT Madras, and Ph.D. (1994) from Texas A&M University. His research focuses on reaction engineering , catalysis , and novel materials for energy and environmental applications , particularly in supercritical fluids , photocatalysts , and polymer science . Developed catalysts for PET plastic recycling , CO2 conversion , and water purification . Collaborated on drug delivery , tissue engineering , and electromagnetic shielding materials. His 580+ peer-reviewed publications have been cited over 25,555 times (h-index 80), with multiple papers exceeding 100 citations. He has led 38 sponsored projects totaling 22 crores , including a J.C. Bose Fellowship (2015-2020). As an administrator, he served as Chairman of interdisciplinary centers, convened admissions committees, and reformed undergraduate admission procedures at IISc. Scientific Awards : S.S. Bhatnagar Prize (2009), J.C. Bose National Fellow (2015-2020), Santappa Memorial Award (2017), and multiple academy fellowships (INSA/INAE/IASc/NASI). Editorial Leadership : Editor of Advanced Powder Technology (2013-2023) and Journal of Supercritical Fluids (2019-2023). His 53 Ph.D. graduates include faculty members at IITs, IISERs, and NITs. He has advised 11 M.Sc. (Engg.) and 32 M.E. students, many receiving best thesis awards . His work bridges industrial applications (wastewater treatment, LPG sensors) with fundamental research on reaction mechanisms and material design.

Praveen Tammanaمشاهده پروفایل

استادیار

• Systems and Networking
• Network Security
• Software-Defined Networking
• +۷ مورد دیگر

Dr. Praveen Tammana is an Assistant Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Hyderabad , where he leads the NetX lab focusing on systems, networks, and security research. He completed his PhD from University of Edinburgh (2013-2018) and holds a Masters from IIT Madras (2009-2011). Education: Ph.D in Computer Science, University of Edinburgh, UK (2013-2018) Masters in Computer Science, IIT-Madras, India (2009-2011) B.E. in Computer Science, Vasavi College of Engineering, Osmania University (2005-2009) Research Focus: His research spans systems and networking , network security , software-defined networking (SDN) , machine learning for networks , wireless communication , high performance computing , and cybersecurity . His lab specializes in programmable data planes using technologies like P4, eBPF, DPUs, and PISA switches. Research Applications: His recent work demonstrates strong focus on AI infrastructure systems , including distributed AI learning and serving, networked robotics, GPU-centric packet processing, and edge cloud applications for autonomous systems. His research bridges the gap between networking infrastructure and AI workloads. Recent Publications Trend: His 2021-2025 publications show significant contributions to network security , programmable switches , edge computing , and AI systems integration . Key themes include securing traffic control systems, AI workload optimization, malicious traffic detection, and real-time applications for autonomous vehicles. Current Funding: Actively funded by industry partners including Mondee (systems for AI workloads), Marvell Technology (data acceleration offload), and ZF India (efficient load-balancer for edge applications). Lab and Team: Leads NetX lab at IIT Hyderabad, actively recruiting full-time research candidates for exciting projects in AI infrastructure, networked systems, and programmable networks. The lab focuses on building next-generation systems for AI workloads and secure network architectures.

Sobhan Babuمشاهده پروفایل

دانشیار

• Big Data Analytics
• Graph Theory
• Algorithms
• +۴ مورد دیگر

Dr. Sobhan Babu is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IIT Hyderabad). His research focuses on Big Data Analytics, Graph Theory, Algorithms, and Applied Machine Learning. He obtained his Ph.D. and MTech from IIT Bombay, and his BE from the University of Madras. Education Ph.D. in Computer Science, IIT Bombay MTech in Computer Science, IIT Bombay BE in Computer Science, University of Madras Diploma in Computer Engineering, AANM&VVRSR Polytechnic Research Interests His work bridges theoretical and applied Computer Science. In Graph Theory, he investigates structural graph properties, subdivisions, and directed graph algorithms. In AI/ML, he explores optimization techniques for VLSI design and power-efficient testing. His Big Data Analytics focus includes developing algorithms for efficient data processing and modeling. Publications His publications span VLSI optimization, algorithmic game theory, and graph theory. Key themes include power minimization in scan testing, market equilibrium algorithms, and graph structural conditions. Recent accepted works extend existing research on cycles and unicyclic graphs, indicating sustained theoretical contributions. Contact Email: sobhan@iith.ac.in Office: Room CS-307, Computer Science Building, IIT Hyderabad, Telangana, India.