جستجوی استاد راهنمای دانشگاهی

Aditya K. Jagannatham is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). With expertise in wireless communications and signal processing, he has established himself as a leading researcher in 5G/6G technologies, MIMO systems, and cognitive radio networks. His educational background includes: PhD in Electrical and Computer Engineering from UC San Diego (2007) M.S. in Electrical and Computer Engineering from UC San Diego (2004) B.Tech. in Electrical Engineering from IIT Bombay (2001) Professor Jagannatham's research primarily focuses on next-generation wireless communication systems, with special emphasis on 5G and 6G technologies. His work spans OTFS modulation, Terahertz communications, Visible Light Communication (VLC), Intelligent Reflecting Surface (IRS) technology, Massive MIMO, mmWave MIMO, Non-Orthogonal Multiple Access (NOMA), and Filter-Bank Multi-Carrier (FBMC) systems. His research integrates theoretical analysis with practical implementation challenges, addressing critical issues in modern wireless networks. His recent publications demonstrate a strong trend toward advanced signal processing techniques for next-generation wireless systems, particularly focusing on Sparse Bayesian Learning approaches for channel estimation, cooperative communication systems with energy harvesting capabilities, and millimeter wave MIMO technologies. His work bridges theoretical communication theory with practical implementation challenges in emerging wireless standards. Professor Jagannatham has received numerous prestigious awards and fellowships: Arun Kumar Endowed Chair Professorship (2019) Qualcomm Innovation Fellowship (2018) P.K. Kelkar Young Faculty Research Fellowship for excellence in research (2015-2018) IEEE Signal Processing Society travel grant to attend ICASSP 2015 Gopal Das Bhandari Memorial Distinguished Teacher Award (2012-13) Cal(IT)2 fellowship for graduate study at UC San Diego As an educator, Professor Jagannatham has received commendation letters from the Director of IIT Kanpur for excellence in teaching courses including EE624 Information and Coding Theory, EE670 Wireless Communications, and EE320 Principles of Communication Systems. His research has attracted significant funding, though specific grant details are not provided in the available information. He likely supervises graduate students working on cutting-edge wireless communication research. Professor Jagannatham is based in the Advanced Centre for Electronic Systems (ACES) at IIT Kanpur, where he leads research in wireless communications. His work appears to be closely connected with the Center for Developing Intelligent Systems (CDIS) and other research centers at IIT Kanpur focused on next-generation communication technologies.

• Wireless Communications
• 5G and 6G Technologies
• OTFS Modulation
• +۹ مورد دیگر

Supratik Chakraborty serves as the Bajaj Group Chair Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. He maintains dual affiliations with the Centre for Formal Design and Verification of Software and the Centre for Liberal Education at IIT Bombay, demonstrating his cross-disciplinary engagement. Professor Chakraborty's research spans formal methods with focus on formal verification, rigorous analysis of system models, and automated synthesis of systems from specifications. His work bridges theoretical foundations with practical applications, particularly in developing mathematically provable guarantees for increasingly complex hardware, software, and intelligent systems. Current research interests include constrained counting and sampling, scalable formal verification of software and hardware systems, automated synthesis of programs and circuits, and applications of automata, logic and finite model theory to practical verification challenges. His publication trajectory shows a significant evolution from traditional hardware and software verification toward addressing verification challenges in machine learning and AI systems. Recent work increasingly focuses on interpretability of black-box models, verification of neural networks, and synthesis techniques applicable to intelligent systems. The research demonstrates strong interdisciplinary connections between formal methods, programming languages, and artificial intelligence. IIT Bombay Excellence in Thesis (CSE) Award 2011 (for Bhargav Gulavani's thesis) IIT Bombay Excellence in Thesis (CSE) Award 2017 (for Abhisekh Sankaran's thesis) Best Paper in Algorithms and Architecture track at IEEE International Conference on Computer Design: VLSI in Computers and Processors, 1998 Professor Chakraborty has successfully supervised 11 doctoral students, with research spanning formal verification techniques, Boolean functional synthesis, constrained counting, and applications to hardware and software systems. His students have gone on to positions at major institutions including Microsoft Research, TCS Research, Georgia Tech, and BARC, reflecting the strong industry and academic impact of his mentorship. Current research directions show increasing emphasis on verification challenges posed by machine learning systems and AI. His research group at IIT Bombay, while not explicitly named in the materials, appears to focus on formal methods with strong connections to the Centre for Formal Design and Verification of Software. The group maintains active collaborations with international researchers including Moshe Y. Vardi at Rice University, and has made significant contributions to verification tools like VeriAbs that bridge theoretical advances with practical applications.

• Formal Methods
• Formal Verification
• Automated Synthesis
• +۷ مورد دیگر

Krishna Jagannathan is a full-time Professor in the Department of Electrical Engineering at the Indian Institute of Technology Madras (IIT Madras), India. He specializes in stochastic modeling, communication networks, information theory, and queuing theory. He obtained his B.Tech from IIT Madras in 2004, followed by S.M. and Ph.D. degrees from MIT in 2006 and 2010, respectively. After post-doctoral positions at Caltech and MIT, he joined IIT Madras in 2011. Education: B.Tech in Electrical Engineering, IIT Madras (2004) S.M. in Electrical Engineering and Computer Science, MIT (2006) Ph.D. in Electrical Engineering and Computer Science, MIT (2010) Research Interests: His research focuses on stochastic modeling and analysis of communication networks , information theory , and queuing theory . He has made significant contributions to understanding network performance, resource allocation, and risk-aware decision-making in complex systems. He leads the Networks and Stochastic Systems lab at IIT Madras, mentoring a large cohort of Ph.D. and M.S. students working on cutting-edge problems in networking, optimization, and stochastic systems. Scientific Awards: Best Paper Award at WiOpt 2013, Tsukuba, Japan Young Faculty Recognition Award for Excellence in Teaching and Research, IIT Madras (2014) Teaching & Mentorship: He has taught a wide range of courses including Probability Foundations , Stochastic Modeling and Queuing Theory , Convex Optimization , and Signals & Systems , consistently receiving high teaching evaluations. He has supervised over 15 Ph.D. and M.S. students to completion and continues to guide several active researchers.

• Stochastic modeling
• Communication networks
• Information theory
• +۳ مورد دیگر

Aditya T Siripuram is an Associate Professor at the Indian Institute of Technology Hyderabad (IITH), holding joint appointments in the Department of Electrical Engineering and the Department of Artificial Intelligence. He completed his PhD at Stanford University and holds B.Tech and M.Tech degrees from IIT Bombay. Education: PhD in Electrical Engineering, Stanford University (2017) - GPA: 4.17/4 M.Tech in Electrical Engineering, IIT Bombay (2009) - GPA: 9.79/10 B.Tech in Electrical Engineering, IIT Bombay (2009) - GPA: 9.79/10 Research Interests: His research spans Fourier analysis, signal processing, machine learning, convex and combinatorial optimization, with applications in AI/ML and applied mathematics. His work particularly focuses on computational aspects of Fourier analysis, including fast DFT computation for structured signals, convolution idempotents, and graph-based signal processing techniques. His recent research directions involve developing efficient algorithms for computing Discrete Fourier Transforms for signals with structured frequency support, investigating relationships between additive structures in frequency domains and computational complexity, and exploring graph learning techniques under spectral constraints. Awards and Recognition: Excellence in Teaching Award, IIT Hyderabad (2019, 2022) Stanford Graduate Fellowship Qualcomm Innovation Fellowship (awarded to his PhD student Charantej Reddy P in 2021) Teaching and Service: He has taught courses including AI1110 Probability and Stochastic Processes, EE5609 Matrix Theory, EE5606 Convex Optimization, and EE5328 Introduction to Submodular Functions. He serves as Departmental Undergraduate Committee Chair for the Department of AI at IITH (2020-present) and was MTech Admissions Coordinator for the same department (2019-2022). Research Group: He currently advises three PhD students working on signal processing based graph learning techniques, DFT computation for structured signals, and coded computing problems.

• Fourier analysis
• Signal processing
• Machine learning
• +۳ مورد دیگر

Shashank Vatedka is an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad . His research focuses on information theory , coding theory , and their applications to data compression , statistical inference , and security . He holds a PhD from IISc, Bengaluru and has postdoctoral experience at Institut Polytechnique de Paris and The Chinese University of Hong Kong . Education : PhD and MSc (Engg) in Electrical Communication Engineering, IISc, Bengaluru (2011-17) Academic Positions : Assistant Professor, IIT Hyderabad (2019-present) Postdoctoral Fellow, Telecom Paris (2018-19) Research Assistant/Postdoctoral Fellow, Institute of Network Coding, CUHK (2016-18) His research spans three main areas: distributed inference (federated learning, wireless sensor networks), compression with locality constraints (local decoding, low-complexity algorithms), and communication in adversarial environments (jamming, list decoding). Recent work includes distributed mean estimation with limited communication and adversarial channel coding with partial information. He has received several honors including the Seshagiri Kaikini Medal for best PhD thesis at IISc in 2017, Best Paper Awards at NCC 2023 and Stanford Compression Workshop 2021, and the TCS Research Fellowship (2014-17). He serves as a Faculty Placement Coordinator at IIT Hyderabad and organizes international conference tracks. His research group advises students across PhD, MTech, BTech , and internships , with alumni pursuing advanced degrees at institutions like UCSD , Columbia University , and TU Delft . Collaborations include theoretical work with colleagues like Yihan Zhang and Sidharth Jaggi .

• Information Theory
• Coding Theory
• Wireless Communication
• +۷ مورد دیگر

R K Bansal is a Professor in the Department of Electrical Engineering at Indian Institute of Technology Kanpur (IIT Kanpur). He has been actively contributing to the fields of Detection Theory and Information Theory for several decades with a strong academic background including a PhD from University of Connecticut (1987). His research interests include: Universal data compression with applications Sequential detection of a change in distribution Robust detection Ergodic theory and large deviation theory applications Stochastic processes Dr. Bansal's recent publications primarily focus on data compression algorithms, particularly variations of the Lempel-Ziv algorithm, and detection theory applications. His work demonstrates a strong theoretical foundation with practical applications in information processing and analysis, showing consistent research activity from the 1980s through 2013. He has received significant recognition for his teaching excellence: Letter of commendation from Director on best teaching (2011) Outstanding tutor for Mathematical Statistics (BSO209) based on student feedback (1998-II) Consistently high teaching evaluations exceeding institute averages Dr. Bansal has advised students and maintained active research in his specialized areas, though specific names of current advisees are not mentioned in the available information. His research has been published in prestigious venues including IEEE Transactions on Information Theory. His laboratory is located in room 202 ACES (Advanced Centre for Electronic Systems) at IIT Kanpur, serving as the base for his research activities in detection theory and information theory applications.

• Detection Theory
• Information Theory
• Universal data compression
• +۵ مورد دیگر

R.K. Shyamasundar is a Professor at the Indian Institute of Technology Bombay , with a focus on Real-Time and Reactive Programming, Logic Programming, Pi-Calculus, and Parallel Programs. Research spans formal verification, concurrency, and distributed systems. Key contributions include RT-CDL semantics, Esterel language extensions, and hybrid system controller synthesis. Scientific awards include JC Bose National Fellow, Fellowships at Indian Academy of Sciences and Indian National Science Academy, and Senior Membership in IEEE. His work involves collaborations with institutions like TCS Group and researchers such as Basant Rajan, N. Raja, and Deepak Kapur.

• Real-Time Programming
• Reactive Programming
• Logic Programming
• +۷ مورد دیگر

Professor Subrahmanya Sastry Challa is affiliated with the Department of Mathematics at Indian Institute of Technology Hyderabad. His academic journey includes a PhD from IIT Kanpur under Prof. P. C. Das, an M.Sc(Tech) from JNT University, and a B.Sc from Hindu College, Machilipatnam. Research Focus: He specializes in Wavelets and Sparse Optimization Theory Frame Theory and Data-driven Learning Methods Applications in Medical Imaging and Signal Processing His recent work explores sparsity-driven optimization techniques with applications in tomography, ECG signal recovery, and machine learning algorithms. Publications & Collaborations: He has contributed to advancements in compressive sensing, inverse problems, and numerical linear algebra through collaborations with researchers like Dr. Phanindra Jampana and Dr. Praveen Pradhan. Key journals include IEEE Transactions on Signal Processing , Inverse Problems , and Neurocomputing . Teaching: Courses taught include Wavelets & Applications, Compressive Sensing, Numerical Linear Algebra, and Mathematics Behind Machine Learning, emphasizing both theoretical and applied aspects. Administrative Roles: Served as Associate HoD/HoD (2010-2014), Chief Vigilance Officer (2015-2019), and participated in policy-drafting committees during IIT Hyderabad's formative years.

• Wavelets
• Sparse Optimization Theory
• Inverse Problems
• +۷ مورد دیگر

Dr. Ajit Kumar Chaturvedi is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), specializing in Communications Theory and Systems. With decades of experience at IIT Kanpur, he has established himself as a leading researcher and educator in wireless communications and information theory. Dr. Chaturvedi earned his B.Tech (1986), M.Tech (1988), and PhD (1995) all in Electrical Engineering from IIT Kanpur, demonstrating his deep institutional commitment. His educational background reflects his dedication to academic excellence at his alma mater. His research focuses on Communications Theory and Systems, with specific expertise in Wireless Communications, Information Theory, and Spread Spectrum Systems. Dr. Chaturvedi's work bridges theoretical foundations with practical applications in modern communication technologies. His contributions have significantly advanced the understanding of signal processing techniques, multiuser detection methods, and error analysis in wireless systems. His research has direct implications for improving the reliability and efficiency of contemporary wireless communication standards. Dr. Chaturvedi's publication record demonstrates consistent contributions to communications engineering, spanning from fundamental signal processing techniques to complex system-level analyses. His work on ISI mitigation, orthogonal sequence design, and error rate analysis shows both theoretical rigor and practical relevance for real-world communication challenges. Distinguished Teacher award of IIT Kanpur (2007) Tan Chin Tuan Fellowship of NTU, Singapore (2008) Supervisor of Best B. Tech Project groups (2002, 2006, 2012) Plenary speaker at the 15th National Conference on Communications (2009) Mentor of IEEE Computer Society International Design Contest winning team (2002) As an educator, Dr. Chaturvedi has supervised numerous award-winning student projects, including three Best B.Tech Project awards. He has mentored teams to international recognition, such as the Microsoft Award for Innovation at the IEEE Computer Society International Design Contest World Finals in 2002. His office is located in ACES 201B at IIT Kanpur, where he continues to contribute to the academic and research mission of the institution.

• Communications Theory
• Wireless Communications
• Information Theory
• +۱ مورد دیگر

Dootika Vats is an Associate Professor in the Department of Mathematics & Statistics at Indian Institute of Technology Kanpur (IIT Kanpur). She earned her PhD in Statistics from the University of Minnesota, Twin-Cities, and her research focuses on advancing Monte Carlo and Bayesian computational methods, especially Markov chain Monte Carlo diagnostics. Education: PhD, Statistics, University of Minnesota, Twin-Cities, Feb 2017 MS, Statistics, University of Minnesota, Twin-Cities, Nov 2016 MS, Statistics, Rutgers University, New Brunswick, May 2012 BA (honors), Mathematics, University of Delhi, Lady Shri Ram College, May 2010 Research Interests: Her work lies at the intersection of computational statistics and Bayesian inference, with core emphases on: Markov chain Monte Carlo (MCMC) methodology Monte Carlo variance estimation and output analysis Bayesian computation and diagnostics Geometric ergodicity and convergence rates of MCMC algorithms Recent Publications Trend: Across her recent articles and preprints, Dr. Vats has consistently tackled open problems in MCMC output analysis, introducing new diagnostics, optimal batch-size selection, and visualization tools that directly impact practical Bayesian computation. Her contributions bridge theoretical rigor—such as proving strong consistency of spectral variance estimators—with immediately applicable software and graphical methods. Awards & Honors: Director’s Award, University of Minnesota School of Statistics, 2016 Graduate Research Partnership Program Fellowship, Summer 2016 Louise T. Dosdall Fellowship for Women in STEM, 2016–2017 School of Statistics Alumni Fellowship, 2015–2016 Martin–Buehler Fellowship in Statistics, Fall 2015 Bernard W. Lindgren Graduate Student Teaching Award, Spring 2014 Lynn Lin Fellowship in Statistics, Summer 2014 Teaching & Mentoring: At IIT Kanpur she continues to teach and mentor within the statistics curriculum. Earlier, at the University of Minnesota, she served as Instructor for STAT 3011 and as a teaching assistant across multiple undergraduate and graduate courses; at Rutgers University she was a part-time lecturer in calculus and pre-calculus. Labs & Collaboration: While no specific lab is named, her research is computational and collaborative; she has worked with James M. Flegal, Galin L. Jones, and other leading MCMC methodologists, and her Google Summer of Code participation demonstrates engagement with the open-source statistics community.

• Markov chain Monte Carlo
• Monte Carlo methods
• Bayesian computation
• +۱ مورد دیگر

Gurunath Gurrala serves as an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Science (IISc), Bangalore. His research focuses on power systems dynamics, high-performance computing applications, and renewable energy integration. He maintains active collaborations with international institutions including Oak Ridge National Lab and Texas A&M University. His research interests center on Power Systems Analysis and Control , with specialization in High Performance Computing Applications, Nonlinear and Intelligent Control, Weak Grid Integration of Renewables, Microgrid Protection, and Smart Grid Stability. His work bridges theoretical control systems with practical power grid challenges, particularly for renewable-rich grids. His recent publications demonstrate a strong interdisciplinary trend, spanning power systems (35%), control theory (25%), renewable integration (20%), and emerging applications in biomedical engineering and environmental systems (20%). Key recurring themes include grid stability under high renewable penetration, advanced protection schemes for microgrids, and computational methods for power system analysis. IEEE Power and Energy Society (PES) Outstanding Engineer Award 2018 Young Engineer Award 2015, Indian National Academy Engineers Best Conference Paper, IEEE PES General Meeting 2015 Best Ph.D Thesis Award (Prof.D.J.Badkas Medal) 2010 Elevated to Senior Member IEEE (2016) Professor Gurrala has secured competitive research funding including the Young Scientist Grant from DST (2015) and International Travel Support from SERB (2017). He actively mentors students through PhD and Master's programs while teaching advanced courses including Power System Dynamics and Control (E4 231), Computer Control of Power Systems (E4 233), and Selected Topics in Integrated Power Systems (E4 237). His research group collaborates with power utilities and international research labs on grid modernization challenges.

• Power Systems Analysis and Control
• High Performance Computing Applications
• Nonlinear and Intelligent Control
• +۴ مورد دیگر

Dr. Chinmay Dharurkar is an Assistant Professor in the Department of Humanities and Social Sciences at the Indian Institute of Technology Kanpur. He holds a Ph.D. from IIT Bombay (2018) and specializes in Sanskrit Grammar, Comparative Linguistic theory, and Philosophy of Linguistics. His academic journey includes positions at United International College, Zhuhai (2021-2022) and Central University of Kerala (2013-2020). Education: Ph.D., Indian Institute of Technology (IIT) Bombay, 2018 Dr. Dharurkar's research spans multiple dimensions of linguistic studies with a particular focus on Indian languages. His work bridges classical Indian linguistic traditions with contemporary theoretical frameworks, examining how ancient linguistic thought informs modern linguistic theory. He has made significant contributions to understanding metrical structures in Sanskrit epics, code-mixing phenomena in Indian languages, and the philosophical underpinnings of linguistic analysis. His research demonstrates deep engagement with both traditional Indian linguistic scholarship and modern linguistic frameworks. His publications reveal a consistent focus on the intersection of classical Indian linguistic traditions with contemporary linguistic theory. Dr. Dharurkar has explored metrical structures in Sanskrit epics, code-mixing of English in Indian languages, Nyaya morpho-syntactic analysis, and linguistic studies of quantifiers. His work demonstrates a unique ability to connect traditional Indian linguistic scholarship with modern linguistic frameworks, making him a significant contributor to the field of Indian linguistics. Scientific Awards: UGC-NET JRF in Linguistics (2010) IIT Bombay's Excellence in Thesis Work for PhD thesis (2018) Prof. Yashwant Sumant Memorial Young Research Inspiration Award (2020) Dr. Dharurkar has been actively involved in academic mentorship and research guidance. His professional experience includes teaching and research positions at multiple institutions, contributing to the development of linguistics education in India. He has successfully navigated both traditional academic settings and international collaborations, including a position at United International College in China (though physical relocation was prevented by the pandemic). His academic work represents a valuable bridge between classical Indian linguistic traditions and contemporary linguistic theory, contributing significantly to the understanding of language structure, history, and philosophy in the Indian context.

• Sanskrit Grammar
• Comparative Linguistic theory
• Philosophy of Linguistics
• +۴ مورد دیگر

Professor A. Sameen is a faculty member in the Department of Aerospace Engineering at the Indian Institute of Technology Madras (IIT Madras), where he has served as a Professor since 2018. His academic career is centered on theoretical and computational fluid dynamics, with a focus on complex flow phenomena. Education: Ph.D. from Indian Institute of Science, Bangalore (2005) Research Interests: Professor Sameen's research spans several key areas in fluid dynamics. His primary expertise lies in Stability, Transition and Turbulence and Computational Fluid Dynamics . He investigates vorticity dynamics including vortex breakdown and reconnections, vortex rings, and flow past bluff bodies. His work on turbulence encompasses scale space dynamics, compressible and rarefied flows, thermal convection, rotating and stratified flows, and magnetohydrodynamics. A significant portion of his research focuses on simulations of flow regimes beyond continuum, including solutions to the Boltzmann equation, rarefied flows, and quantum fluids. Publication Trends: Professor Sameen's recent publications (2021-2025) demonstrate a strong focus on advanced fluid dynamics phenomena. His work spans theoretical investigations of flow stability, computational modeling of complex vortex structures, and analysis of flow regimes where continuum assumptions break down. Key themes include vortex dynamics across different flow conditions, shock wave interactions at fluid interfaces, and the behavior of flows in rarefied conditions. His research increasingly integrates high-fidelity numerical methods with fundamental fluid mechanics principles to address challenging problems in aerospace engineering. Scientific Contributions: Development of multiple in-house computational codes for fluid dynamics simulations Contributions to understanding continuum breakdown in compressible flows Advancements in modeling vortex dynamics and breakdown phenomena Advising and Research Leadership: Professor Sameen has guided numerous doctoral students through their research, with recent theses focusing on global linear stability analysis, vortex dynamics, and computational fluid mechanics. He leads the Theoretical and Computational Fluid Dynamics Lab and is affiliated with the Institute of Eminence Center of Excellence - Geophysical Flows Lab at IIT Madras. His collaborative work spans multiple institutions and involves developing advanced numerical methods for fluid flow simulation. Research Infrastructure: Professor Sameen's laboratory utilizes several custom-developed computational tools, including the Unstructured 3D Gas Kinetic Method, Structured 2D Unified Gas Kinetic Method, high-order compact difference schemes, and specialized solvers for multiphase and magnetohydrodynamic flows. These tools enable his team to investigate fluid phenomena across a wide range of conditions, from continuum to rarefied regimes.

• Aerospace Engineering
• Fluid Dynamics
• Computational Fluid Dynamics
• +۴ مورد دیگر

Dhananjay Dhamdhere is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay (IIT Bombay). He has maintained an active research and teaching career since at least the 1980s, with current involvement in course instruction and academic initiatives. Research Interests: Optimizing Compilers and Partial Redundancy Elimination Operating Systems and Distributed Systems Detection of Data Races and Atomicity Violations Safety issues in Dynamic Software Updating Debugging of Optimized Programs His research demonstrates a consistent focus on practical compiler optimizations, evolving from foundational work in data flow analysis to contemporary challenges in dynamic software updating. The publications show particular expertise in making theoretical compiler concepts implementable in real-world systems, with significant contributions to partial redundancy elimination techniques. Research Funding: Department of Electronics research grant on Optimizing Compilers (1985) Grants from Tandem Computers (1995), Intel (1998), Microsoft Research (2001, 2002), and Sun Microsystems (2001, 2002) Professor Dhamdhere has successfully transferred technology to industry through his Gensat system, a generator for static analysis tools. He actively contributes to academic culture improvement through the Forum for Academic Culture (FAC), which he co-founded in 2013 to address student motivation, teaching methodologies, and large class challenges at IIT Bombay.

• Optimizing Compilers
• Partial Redundancy Elimination
• Operating Systems
• +۷ مورد دیگر

Suman Saurabh serves as an Assistant Professor in the Department of Management Sciences at the Indian Institute of Technology Kanpur (IIT Kanpur), specializing in Finance and Accounting. His academic journey reflects a strong foundation in both engineering and business disciplines, transitioning from Electrical Engineering to advanced financial studies. Dr. Saurabh holds a PhD (FPM) from IIM Ahmedabad (2012-2018), a Master of Business Economics from the University of Delhi (2010-2012), and a Bachelor of Technology in Electrical Engineering from IIT(BHU) Varanasi (2003-2007). This diverse educational background enables him to approach financial problems with both technical precision and business acumen. His research spans multiple critical areas of finance including Corporate Finance, Asset Pricing, Behavioral Finance, Mergers and Acquisitions, and Financial Derivatives. Recent work demonstrates increasing focus on emerging technologies' impact on finance, particularly blockchain applications in SME financing and receivables management. His publications reveal a strong connection between theoretical finance frameworks and practical Indian market contexts, especially regarding corporate distress prediction post-Insolvency and Bankruptcy Code implementation. Dr. Saurabh has received multiple teaching and research recognitions including the Excellence-in-Teaching Award (2023) from IIT Kanpur, Best Paper Awards at international conferences in 2022 and 2023, and a Senate Citation for Teaching Excellence. His scholarly contributions include publications in journals such as Review of Corporate Finance, Journal of Economics and Finance, and Managerial Finance, along with book chapters published by Edward Elgar and Springer. Within IIT Kanpur, Dr. Saurabh has held significant service roles including Department Under-Graduate Committee Convener (2023-24), Warden in-charge of Hall of Residence-V (2022-24), and Department Online Programmes Convener (2022-23). His professional service extends to serving as Program Co-Chair for international conferences and as a reviewer for journals including Qualitative Research in Financial Markets and Vikalpa: The Journal for Decision Makers.

• Finance
• Accounting
• Corporate Finance
• +۴ مورد دیگر