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Sunita SarawagiView profile

Professor

• Machine Learning
• Data Analytics
• Databases
• +10 more

Sunita Sarawagi is a Professor at Computer Science and Engineering , IIT Bombay, and a member of AI Labs@CSE . She is also associated with the Center for Machine Intelligence and Data Science (CMInDS), which she founded in 2020. Education: PhD in Computer Science from UC Berkeley (Thesis: Query Processing in Tertiary Memory Databases), BTech in Computer Science from IIT Kharagpur Research Interests span machine learning , data analytics , graphical models , and structured learning , with applications in text segmentation, sequence modeling, domain adaptation, and human-in-the-loop systems. Her publications reveal a strong focus on integrating data mining with database systems , temporal data analysis , and information extraction using probabilistic methods. Professional Activities include serving on the IEEE John Von Neumann Medal committee (2017-), VLDB 2011 Research Track Co-chair , and multiple program committee roles at top conferences like ICML, KDD, and SIGMOD. Labs & Teams : Leads the SS Lab , a research group focused on probabilistic graphical models, sequence modeling, and data integration techniques.

Vineeth N BalasubramanianView profile

Professor

• Deep Learning
• Machine Learning
• Computer Vision
• +8 more

Vineeth N Balasubramanian is a Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Hyderabad, with affiliate faculty status in the Department of Artificial Intelligence. His research focuses on the intersection of deep learning, machine learning, and computer vision, emphasizing explainability, robustness, and real-world applications. He leads Lab 1055, which investigates problems such as Explainable and robust AI/ML systems Lifelong learning in evolving environments Multimodal vision-language models Applications in agriculture, autonomous navigation, and human behavior analysis His recent work includes causal reasoning in transformers, vision-language model capabilities, and drone-based object detection. Funded by organizations like Google, Microsoft, Intel, and DST, he has received multiple awards including the World's Top 2% Scientists (2022-23), INSA/INAE Fellowships, and Best Paper recognitions. Lab 1055 collaborates with institutions like CMU, UBC, and Monash University, contributing to cutting-edge advancements in AI.

Aditya T SiripuramView profile

Associate Professor

• Fourier analysis
• Signal processing
• Machine learning
• +3 more

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.

Kishalay MitraView profile

Professor

• Optimal Control Under Uncertainty
• Bioenergy Supply Chain Design
• Surrogate Multi-Objective Optimization
• +13 more

Kishalay Mitra is a Professor at the Indian Institute of Technology Hyderabad , with affiliations to the Department of Chemical Engineering , Department of Climate Change , and Department of Artificial Intelligence . He also holds visiting professorships at Washington University in St. Louis and University of Washington, Seattle . His work in the Global Optimization & Knowledge Unearthing Laboratory (GOKUL) spans interdisciplinary optimization, machine learning, and their applications in industrial-scale engineering problems. Education : Ph.D. from IIT Bombay. Research Interests : Mitra's research focuses on optimization under uncertainty , surrogate modeling , multi-objective optimization , and integrating machine learning with physics-based models . His work addresses real-world challenges in wind energy , bioenergy supply chains , chemical process control , nanoscience , and environmental modeling (e.g., PM10 spatiotemporal analysis, forest fire prediction, and carbon capture). Article Trends : His recent publications emphasize wind energy systems (layout optimization, yaw control, forecasting), materials science (precipitate growth prediction, polymerization), and industrial processes (crystallization, grinding circuits). Techniques include neural operators , Bayesian optimization , generative adversarial networks (GANs) , and explainable AI .

Renu JohnView profile

Professor

• Biomedical Imaging
• Optical Coherence Tomography
• Nanoparticles
• +8 more

Renu John is a Professor in the Department of Biomedical Engineering at Indian Institute of Technology Hyderabad . He earned his Ph.D. in Physics (Optics) from IIT Delhi in 2006 and has held postdoctoral positions at Duke University and University of Illinois . He leads the Medical Optics and Sensors Laboratory (MOS) and co-founded the Center for Healthcare Entrepreneurship (CfHE) , focusing on affordable healthcare solutions for India. Research Interests : Biomedical Imaging, Optical Coherence Tomography (OCT), Digital Holography, AI/ML in Diagnostics, Microfluidic Biosensors, 3D Bioprinting, Nanoparticle-based Imaging, Optical Elastography. Awards : Best Paper & Poster Awards at international conferences (2018-2019), Samsung Innovation Award (2018) for smartphone-based oral cancer detection. Grants : Lead investigator for an ICMR Center of Excellence (15.2 Cr funding) in Medical Devices and Diagnostics. Students : Mentored over 20 researchers, including current and alumni Ph.D. candidates working on OCT, microfluidics, AI-driven imaging, and biosensor development. Labs & Innovations : The MOS Lab develops cutting-edge technologies like lensless microscopes, FF-OCT systems, and dual-modality biosensors. His team has filed 18 patents and published 117 international journal articles, with projects spanning from in vivo magnetomotive imaging to organ-on-chip platforms for disease modeling.

Sumohana S ChannappayyaView profile

Professor

• Image and Video Quality Assessment
• Biomedical Image Processing
• Machine Learning
• +1 more

Sumohana S Channappayya is a Professor in the Department of Electrical Engineering at Indian Institute of Technology Hyderabad, leading the Lab for Video and Image Analysis (LFOVIA). His research focuses on image/video quality assessment, biomedical image processing, and machine learning applications. Education Ph.D., Electrical Engineering, The University of Texas Research Interests His work addresses critical challenges in AI-driven image/video analysis, with applications in biomedical imaging and quality assessment. Recent research trends highlight advancements in training-free neural network adapters for multimodal image matching , spanning disciplines like Computer Science , Biomedical Engineering , and Video Analytics . Advising & Collaborations He has co-advised PhD graduate Suresh Kumar Amalapuram and supervised PhD scholar Anuradha Uggi. His lab supports students like Lokesh Badisa, who received the IndiaAI Fellowship. Labs & Teams As founder of the Lab for Video and Image Analysis (LFOVIA), he drives interdisciplinary research in video/image analytics and AI/ML technologies. Contact Office: EE605, Department of Electrical Engineering, IIT Hyderabad Email: firstname@ee.iith.ac.in Phone: (040) 2301 - 6463

Ketan P. DetrojaView profile

Associate Professor

• Control Theory
• State Estimation
• Fault Diagnosis
• +9 more

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.

Surendra Nadh SomalaView profile

Associate Professor

• Machine Learning
• Deep Learning
• Seismic Isolation
• +20 more

Dr. Surendra Nadh Somala is an Associate Professor at the Indian Institute of Technology Hyderabad , affiliated with the Civil Engineering and Heritage Science & Technology departments. He holds a Ph.D. from California Institute of Technology (Caltech) and focuses on interdisciplinary research at the intersection of structural engineering, AI/ML, and heritage conservation. Education: Ph.D., California Institute of Technology (Caltech) His research spans seismic resilience technologies, additive manufacturing for civil infrastructure, and applications of machine learning in structural health monitoring. He also explores high-performance computing (HPC) for multiscale modeling and integrates virtual/augmented reality in design innovation and heritage preservation. Office Address: Room B-304, Academic Block B, Indian Institute of Technology Hyderabad, Kandi-502284, Sangareddy, Telangana, India.

Shruti UpadhyayaView profile

Assistant Professor

• Hydrometeorology
• Remote Sensing
• High-impact weather
• +1 more

Shruti Upadhyaya is an Assistant Professor in the Civil Engineering department. She holds a Ph.D. from IIT Bombay and specializes in hydrometeorology, remote sensing, high-impact weather, and explainable AI/ML (XAI/ML). Her research bridges civil engineering with advanced machine learning techniques to address weather-related challenges.

Jyothi VeduradaView profile

Assistant Professor

• Compilers
• Program Analysis
• High-Performance Computing
• +3 more

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.

Sayantee JanaView profile

Assistant Professor

• Data mining for Big Data
• Spatio-temporal Modelling
• AI/ML in Finance
• +5 more

Sayantee Jana is a Full-time Assistant Professor in the Department of Mathematics at Indian Institute of Technology Hyderabad. She specializes in statistics and machine learning with applications across finance, healthcare, and clinical trials. PhD in Mathematical Statistics (2017) from McMaster University Postdoctoral Fellow at University of Toronto (2017-2018) Research Focus: Combines statistical theory with practical applications including: Big data analysis through data mining techniques Adaptive Gaussian Hermite Quadrature for spatio-temporal modeling Bayesian methods for skewed financial data Clinical trial design optimization Scientific Recognition: Recipient of prestigious Queen Elizabeth Scholarship Fields Institute Research Fellow Florence Nightingale Award winner (2020) Collaborations: Maintains active partnerships with researchers from University of Toronto, University of Ottawa, and IQVIA Germany. Offers funded opportunities for PhD candidates, postdocs, and summer interns.

SoumyashreeView profile

Assistant Professor

• Machine Learning
• Artificial Intelligence
• High-Performance Computing
• +3 more

Soumyashree is an Assistant Professor at the School of Computer Engineering, Manipal University, with 8 years of experience in academic and research domains. Her work bridges theoretical and applied aspects of Machine Learning, Artificial Intelligence, and Wireless Networks, focusing on solving complex problems in industrial and computational systems. Education: B.E., M.Tech, Ph.D. Research Interests: Machine Learning, AI, 5G Wireless Networks, Energy Efficiency Optimization, and Industrial Monitoring Systems. She has published extensively on topics like graph convolutional networks for resource allocation in 5G, AI-driven energy management in HPC, neural network-based tool wear monitoring, and deep learning architectures for agricultural disease detection. Recent Research Trends: Her publications emphasize applying ML/AI to diverse domains: optimizing wireless networks, enhancing energy efficiency in computing systems, predictive maintenance in manufacturing, plant disease classification, and digital forensics. Keywords include graphs , resources , neural networks , and computer vision . Email: soumya.shree@manipal.edu ORCID: 0000-0001-8988-0021

• Hardware Security
• Cryptography
• Fault Attacks
• +7 more

Sayandeep Saha is an Assistant Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. His research focuses on Hardware Security and Cryptography, with emphasis on Fault Attacks, Side-Channel Attacks, and Post-Quantum Cryptography. He leads the SHarC research group and actively collaborates with international institutions. Education: PhD in Computer Science and Engineering from Indian Institute of Technology Kharagpur Postdoctoral Experience: NTU Singapore (2022-2023), UCLouvain Belgium (2023-2024) His research explores hardware vulnerabilities in cryptographic systems, covering: Fault Attacks on Symmetric and Post-Quantum Cryptosystems Side-Channel Analysis of Power/EM Radiation Microarchitectural Attacks (Spectre/Meltdown variants) Countermeasure Development and Formal Verification Recent research trends include Rowhammer attacks, randomized cache designs, and fault propagation in cryptographic circuits. His work has been recognized in top conferences like ICCAD, USENIX Security, and CHES. Awards: Top Picks in Hardware and Embedded Security 2024 (EUROCRYPT 2020 paper) He is currently hiring Project Research Assistants for the RISC-V-based SISHAM project and supervises PhD students in hardware security research.

Lohithaksha Maniraj MaiyarView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Climate Change
• +4 more

Lohithaksha Maniraj Maiyar is an Assistant Professor and Head in Entrepreneurship and Management at IIT Kharagpur. Their interdisciplinary research bridges AI/ML with critical societal challenges. Education: Ph.D. from IIT Kharagpur Research Interests: Focus areas include Artificial Intelligence , Machine Learning , and applications to Climate Change , Waste Management , and Transportation systems.

Maunendra Sankar DesarkarView profile

Associate Professor

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +10 more

Dr. Maunendra Sankar Desarkar is an Associate Professor at the Computer Science and Engineering Department of Indian Institute of Technology Hyderabad , India, with affiliations to the AI Department. His research spans Natural Language Processing , Information Retrieval , and Machine Learning , focusing on robust, responsible, and culturally-aware AI systems. Education: B.E. (University of Burdwan), M.Tech (IIT Kanpur), Ph.D. (IIT Kharagpur, 2014) Current work emphasizes zero-shot cross-lingual transfer , dialogue interpretability , and ethical NLP (non-toxicity, empathy). Recent articles explore large language model evaluation , hallucination detection , and tokenization for Indic languages . Collaborations include Microsoft and JICA-funded projects. Scientific contributions include: Microsoft India Ph.D. Fellowship Award Yahoo Key Scientific Challenges Honorable Mention (2012) Students include Suvodip Dey (Ph.D. in Dialogue Systems), Aishwarya Maheswaran , Debolena Basak , Kaushal Kumar Maurya , and Maharaj Brahma . Advises on projects involving disaster response systems , generative AI , and multilingual NLP .