Jayashree is an Assistant Professor in the Department of Computer Science and Engineering at the School of Computer Engineering, Manipal Institute of Technology, part of Manipal University in India. She holds a B.E. and M.Tech in Computer Science Engineering and maintains an active research profile with an h-index of 34. Research Interests: Data Mining and Analytics Machine Learning Applications in Healthcare Deep Learning for Medical Imaging Alzheimer's Disease Progression Detection Diabetes Stratification Systems Disaster Assessment via Multimodal Analysis Ayurveda Integration with Clinical Decision Support Recent Research Trends: Her 2023-2025 publications focus on applying deep learning to medical diagnostics (Alzheimer's, diabetes), multimodal social media analysis for disaster response, and computer vision techniques for image segmentation. Key methodologies include neural networks, feature extraction, and thresholding algorithms.
Vijayalaxmi serves as Associate Professor - Senior Scale in the Department of Electrical and Electronics Engineering at Manipal Institute of Technology, Manipal Academy of Higher Education. With an h-index of 66 and 12 research outputs since 2012, her recent scholarly activity shows significant acceleration with five publications in 2023-2024 alone. Her research program bridges artificial intelligence with critical real-world applications: Developing deep learning frameworks for agricultural disease detection (e.g., LeafSpotNet for jasmine plants) Creating computational techniques for poultry health management through machine learning Applying natural language processing to analyze pandemic mental health impacts Designing embedded systems for smartphone sensor stabilization Publication trends from 2023-2024 reveal concentrated expertise in agricultural AI, with four of five papers focusing on plant and poultry disease detection systems. Her work consistently employs computer vision and deep learning methodologies to solve practical problems in sustainable farming, demonstrating strong interdisciplinary impact across electrical engineering and agricultural technology domains. No scientific awards are documented in the available profile information. While her advisory activities and grant funding remain unspecified in the provided materials, her collaborative publication patterns suggest active engagement with researchers across computer science and agricultural domains. Laboratory or team affiliations are not explicitly mentioned in the current profile.
Dr. Ashwitha A. is an Assistant Professor (Senior Scale) in the Department of Information Technology at the School of Computer Engineering, Manipal Academy of Higher Education, Bengaluru. She holds a B.E., M.E., and Ph.D. and has accumulated 10 years of teaching experience. Her academic profile includes an h-index of 6 and 117 Scopus citations. Her primary research domains include: Machine Learning algorithms and applications Artificial Intelligence systems development Deep Learning architectures Internet of Things implementations Recent publications demonstrate applications across environmental sustainability, healthcare technology, agricultural systems, sports analytics, and biomedical engineering, consistently utilizing predictive modeling and neural network approaches.
Raghavendra Achar is an Associate Professor at the School of Computer Engineering , affiliated with Manipal University in Manipal, Karnataka, India. He holds degrees in Computer Science and Engineering, including a PhD, and contributes extensively to research in technology-driven solutions. Education : BE (CSE), MTech (CSE), PhD (CSE) His research spans Cloud Computing , Machine Learning , and Medical Imaging , with a focus on optimizing cloud resources, developing fuzzy logic systems for medical diagnostics, and enhancing autonomous vehicle technologies. Recent works include: 2024: Cross-layer refinement network for autonomous vehicle localization 2023: Fuzzy logic-based OCT image analysis for diabetic macular edema 2020: Cloud provider selection mechanisms and VM placement strategies 2018: Energy-efficient cloud resource provisioning He collaborates across disciplines, particularly in Artificial Intelligence and Healthcare Technology , though no specific awards or grants are highlighted in the provided text.
Dr. A. Durga is an Assistant Professor in the Department of Metallurgical Engineering and Materials Science at the Indian Institute of Technology Bombay (IIT Bombay), where she has been serving since December 2021. She holds a Ph.D. in Materials Engineering from KU Leuven, Belgium, and a B.Tech. from IIT Madras in Metallurgical and Materials Engineering. Education: Ph.D. in Materials Engineering, KU Leuven, Belgium (2015) B.Tech. in Metallurgical and Materials Engineering, IIT Madras, India (2009) Her research lies at the intersection of computational materials science and advanced manufacturing. She specializes in computational thermodynamics , additive manufacturing , microstructure evolution , and phase transformations . Her work employs phase-field modeling and thermodynamic optimization to understand and predict material behavior during processing. The recent publications reflect a strong focus on predictive modeling in alloy systems, particularly in additively manufactured steels , solder joints , and superalloys . Her research integrates digital tools to accelerate alloy design and microstructure control, contributing to next-generation materials development. Scientific Contributions: Published in high-impact journals such as Scripta Materialia , Acta Materialia , and JOM Invited speaker at international seminars including the MateriAlZ Seminar Series (USA) Active Google Scholar profile with significant citations Dr. Durga has prior industrial and academic research experience at GE Research, Bangalore, and KTH Royal Institute of Technology, Sweden. She advises students in computational and experimental materials science, though specific advisees are not listed. Her work is supported by institutional and potentially external research funding, though specific grants are not detailed. She is part of the active research group within the MEMS department at IIT Bombay, contributing to the department’s vision in advanced materials development and industrial collaboration.
Pushpak Bhattacharyya is a distinguished Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology (IIT) Bombay. He holds the prestigious title of Abdul Kalam National Fellow and is a Fellow of the National Academy of Engineering (FNAE). His academic leadership extends to roles such as Professor Incharge of the IIT Bombay-Monash Australia Academy and Chairman of the MEITY Committee for Indian Language Standards. Professor Bhattacharyya's research spans multiple domains within computational linguistics and artificial intelligence. His work focuses on Natural Language Processing, Computational Linguistics, Machine Learning, Sarcasm Detection, Sentiment Analysis, Multilingual Processing, and Cognitive NLP. He has made significant contributions to Indian language technology, leading NITI Aayog's initiative on creating an Indian Language NLP stack and Virtual Agents. His recent publications reveal a strong focus on multilingual NLP for Indian languages, bias detection in language models, sarcasm and humblebragging detection, mental health applications of NLP, and code generation. His work bridges theoretical advances with practical applications in education, healthcare, and government services. The research demonstrates increasing integration of cognitive aspects with traditional NLP approaches and a growing emphasis on ethical AI considerations like bias detection and cultural competence. FNAE (Fellow of National Academy of Engineering) Abdul Kalam National Fellow Listed among top 10 Machine Learning Researchers in India Listed among most prolific NLP-ML researchers 2012-17 Professor Bhattacharyya has mentored numerous PhD and Masters students who have gone on to make significant contributions in academia and industry. His research has been supported by various grants from government agencies and industry partners, enabling large-scale projects in Indian language technology and NLP. He has led the development of comprehensive NLP resources for Indian languages and has been instrumental in establishing research collaborations between IIT Bombay and international institutions. He leads a vibrant research group at IIT Bombay focused on Natural Language Processing, with active projects in sarcasm detection, multilingual processing, cognitive NLP, and applications of NLP in healthcare and education. His team has developed several notable systems including those for Indian language translation, sarcasm detection, and mental health analysis through text.
Ashutosh Trivedi is an Associate Professor of Computer Science at the University of Colorado Boulder, currently on leave from his position as Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay. He is affiliated with multiple research initiatives including the Centre for Formal Design and Verification of Software (CFDVS) at IIT Bombay, Free and Open Source Software for Education (FOSSEE), and the Indo-French project on Algorithmic Verification of Real-Time Systems (AVeRTS). At CU Boulder, he leads the Programming Languages and Verification (CUPLV) research group focusing on trustworthy AI systems. Trivedi's research centers on bridging formal methods with artificial intelligence to create more trustworthy systems. His work spans formal verification of cyber-physical systems, reinforcement learning with formal guarantees, and developing techniques for ensuring software fairness and accountability. He specializes in using formal languages, automata, and logic to transform vague natural-language instructions into precise specifications for AI systems. His recent projects include developing reinforcement learning algorithms for cardiac pacemaker design based on formal safety requirements, using SAT solvers to ground large language model outputs in logical reasoning, and encoding state representations in reinforcement learning using formal languages. His publication trends reveal a strong focus on neurosymbolic approaches that combine neural networks with symbolic reasoning, particularly for safety-critical applications. Recent work demonstrates increasing integration of formal methods with reinforcement learning, with applications spanning medical devices, tax preparation software, and puzzle-solving AI. His research shows a clear trajectory toward making AI systems more explainable, accountable, and verifiable through principled mathematical frameworks. Distinguished Paper Award at CAV for Regular Reinforcement Learning (2024) NeuS 2025 Disruptive Idea Award for Stochastic Neural Simulation Relations for Transferring Control under Uncertainty ACM Senior Member recognition (2024) Royal Society Wolfson Visiting Fellowship (2024) Trivedi has successfully advised multiple PhD students to completion, including Shadi Tasdighi Kalat (2025), Mateo Perez (2025), John Komp (2024), Vishnu Murali (2024), and Taylor Dohmen (2024). His teaching portfolio includes foundational courses in automata theory, digital logic design, and cyber-physical systems at both IIT Bombay and CU Boulder. He has served on program committees for major conferences including FSTTCS, HSCC, and FORMATS, and organized workshops such as ICLA 2015 and ALC 2015. As leader of the CUPLV research group, Trivedi directs projects focused on formal verification of AI systems, reinforcement learning with safety guarantees, and software fairness. His group collaborates with medical researchers on cardiac device verification and with legal scholars on tax software accountability, reflecting his commitment to applying formal methods to real-world problems with significant societal impact.
Abhinav Kumar is a Professor at Indian Institute of Technology Hyderabad , affiliated with the Department of Electrical Engineering, Department of Artificial Intelligence, and Department of Engineering Science. His research bridges Wireless Communication & Networking , Machine Learning , and Green Communication in emerging technologies like V2X , UAVs , and IoT . Education: PhD in Electrical Engineering from IIT Delhi (2013), Dual B.Tech/M.Tech from IIT Delhi (2009) Professional Roles: IEEE Senior Member, Editor of IEEE Transactions on Communications, Reviewer for multiple IEEE journals His research focuses on resource allocation in 5G networks, security in wireless systems, and machine learning applications for UAVs and mmWave radars. Recent projects include funded work on 6G integrated sensing, digital twin networks, and OTFS modems. Students under his guidance explore topics like QoE modeling , drone detection , and energy-efficient IoT protocols . Key publication trends combine machine learning with mmWave radar , VLC , and NOMA systems. He has co-authored over 25 journal articles since 2013, with a focus on 5G/6G , UAV communication , and edge computing . He leads the Wireless Communications and Networking (WiCoN) Laboratory , mentoring 25+ PhD and MTech students on projects ranging from smart triage systems to e-waste battery analysis . His lab has produced multiple IEEE Graduate Congress Best Thesis Award winners.
Konda Reddy Mopuri is an Assistant Professor at the Indian Institute of Technology Hyderabad , leading the Data-Driven Intelligence & Learning Laboratory (DiL) . He holds a PhD from Indian Institute of Science, Bengaluru , where he worked under Prof. R. Venkatesh Babu. His research spans Artificial Intelligence , Deep Learning , Computer Vision , and Optimization , with recent work focusing on coreset selection , fairness in ML , and medical imaging . Awards include the IUPRAI Best Doctoral Dissertation Award and SPCOM Best Doctoral Dissertation Award in 2018, and the Young Alumni Achiever Award from IISc in 2022. Notable publications include work on data-free knowledge distillation , adversarial perturbations , and medical AI applications . He has advised students like Saumyaranjan Mohanty , Nikita Malik , and Naveen George , and teaches courses on Machine Learning and Deep Learning .
Dr Shiva Ji is Associate Professor of Design at Indian Institute of Technology Hyderabad, with affiliate appointments in the Department of Climate Change (GreenKo School of Sustainability) and Department of Heritage Science & Technology. He also serves as Head of Design and Principal Investigator of the Design for Sustainability Lab and Digital Heritage Lab. Education PhD in Design, IIT Guwahati (2015-2020) – MHRD Design Innovation Center Fellow Master of Design (PGDPD), National Institute of Design, Ahmedabad (2005-2007) Bachelor of Architecture, Government College of Architecture (now FoA, APJAKTU), Lucknow (1999-2004) MBA, Indira Gandhi National Open University (2011) Certificate Course in Sustainability in Practice, University of Pennsylvania (2014) Professional Certificate in Environment & Sustainable Development, CEPT University (2011) Research Interests Dr Ji’s work converges architecture, sustainability, and digital technologies . His major thrust areas include Design for Sustainability integrating Life-Cycle Assessment (LCA) and system-design thinking, Digital Heritage using AR/VR/MR for architectural documentation and immersive reconstruction, and Climate-Responsive Design Innovation addressing micro-habitation, urban sprawl, and sustainability in the face of climate change. He also investigates vernacular and bio-architecture , leveraging indigenous knowledge for contemporary sustainable solutions, and explores industrial/product design for new-age services and circular-economy products. Publication Trends Since 2016 he has authored 25+ peer-reviewed works spanning urban analytics, digital heritage, sustainable architecture, and socio-cultural studies . Recent publications emphasize data-driven heritage documentation (photogrammetry, space-syntax, visibility graphs) and environmental performance evaluation of built environments, highlighting an interdisciplinary blend of design, computation, and sustainability science. Scientific Awards & Recognition 3rd Winner – Click! Japan Photo Contest 2020 (Embassy of Japan & Japan Foundation) JICA Travel Grant for Japan Universities visit Ford Foundation Scholarship NID Scholarship MHRD Design Innovation Center Fellowship All-India Rank 36 – CEED 2005 NASA Design Competition Citation 2002 Student Supervision & Funding Currently supervising 5 ongoing PhD and 4 ongoing Master’s students, with 14 Masters theses/dissertations already completed. He is Principal Investigator on DST-Govt. of India funded project and India partner for EU LeNSin project (Politecnico di Milano), mobilising international collaborations on sustainable product-service systems. Laboratories & Teams Dr Ji leads two flagship labs: • Design for Sustainability Lab – focuses on LCA, circular design, and strategic sustainable solutions for local to global challenges. • Digital Heritage Lab – pioneers AR/VR/MR applications for immersive heritage visualization and digital twins of architectural assets. Each lab runs multiple sponsored projects with interdisciplinary student teams, industry partners, and international collaborators.
Soumya Jana is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad. His research spans interdisciplinary domains at the intersection of technology and societal challenges. Research Interests: Biomedical Image and Signal Analysis, Air Quality Analysis, Network Information Theory, Computer Vision, Artificial Intelligence, and Climate Change.
Tushar Sandhan serves as an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), one of India's premier technical institutions. He maintains his office in room 205-B of the Electrical Engineering department building on the IIT Kanpur campus in Kanpur 208016. Dr. Sandhan earned his PhD from Seoul National University in South Korea, indicating substantial international research experience prior to joining IIT Kanpur's faculty. His educational background reflects a strong foundation in advanced technical disciplines. His research expertise spans three rapidly evolving and interconnected fields: computer vision , which focuses on enabling machines to interpret visual information; machine learning , which develops algorithms that allow computers to learn from data; and robotics , which integrates these capabilities into physical systems. These research areas have significant applications across multiple industries including autonomous vehicles, medical imaging, industrial automation, and consumer electronics. While specific research projects aren't detailed in the available information, his work likely contributes to both theoretical advancements and practical implementations in these cutting-edge domains. As an Assistant Professor at IIT Kanpur, Dr. Sandhan is actively involved in teaching electrical engineering courses while pursuing research in his specialized areas. His position suggests he is in the early to mid-career stage of his academic journey, building his research program and contributing to the academic community at one of India's most prestigious technical institutions.
Nikunj Arunkumar Bhagat serves as an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur, with a joint appointment in the Department of Biological Sciences and Biosciences. His research focuses on neural engineering, rehabilitation technologies, and biomedical instrumentation. Dr. Bhagat's research interests include Neural & Bio-signal processing, Medical Instrumentation, Brain-machine interfaces, Functional Electrical Stimulation, and Rehabilitation Engineering. His work bridges electrical engineering with neuroscience and rehabilitation medicine, developing technologies to assist individuals with neurological impairments. His publication portfolio shows a strong focus on brain-machine interfaces, rehabilitation robotics, and neural decoding techniques. The research spans from fundamental neural signal processing to practical applications in stroke rehabilitation, tetraplegia assistance, and hand movement restoration. His most recent work (2023) continues to advance state-space control approaches for neuromuscular stimulation and object detection applications for hand rehabilitation. Dr. Bhagat has established collaborative research with prominent institutions and researchers in the field of neurorehabilitation and brain-computer interfaces, as evidenced by his publications in high-impact journals such as IEEE Transactions on Human-Machine Systems, NeuroImage: Clinical, and Frontiers in Neuroscience. His academic journey includes a Ph.D. in Electrical Engineering from the University of Houston (2017), an M.Tech in Electrical Engineering from IIT Bombay (2011), and a B.E. in Electronics Engineering from Sardar Patel College of Engineering, University of Mumbai (2007).
Chandraprakash Chindam is an Associate Professor in the Department of Mechanical Engineering at the Indian Institute of Technology (IIT) Kanpur. He joined IIT Kanpur as a Visiting Assistant Professor in 2017, became an Assistant Professor from 2018-2024, and was promoted to Associate Professor in 2024. His academic journey includes a PhD in Engineering Science and Mechanics from Pennsylvania State University, an M.Tech in Product Design from IIT Madras, and a B.Tech in Mechanical Engineering also from IIT Madras. Prior to his academic career, he worked as a Project Officer at the Centre for Non-Destructive Evaluation at IIT Madras and as a Technical Manager at TATA Motors' Engineering Research Centre. Education: 2017: PhD in Engineering Science and Mechanics, Pennsylvania State University 2010: M.Tech in Product Design, Mechanical Engineering, IIT Madras 2008: B.Tech in Mechanical Engineering, IIT Madras Dr. Chindam's research focuses on the intersection of wave mechanics, thermal diffusion, and material characterization. His primary research interests include acoustic metamaterials, thermal nondestructive evaluation, soft robotics, multifunctional materials, instrumentation, and computer vision. His work combines computational approaches with experimental techniques to develop innovative materials and characterization methods. He has pioneered research in phononic crystals, acoustic foams, and advanced surface characterization techniques, with applications in noise control, structural health monitoring, and sustainable materials development. His recent publications demonstrate a strong trend toward interdisciplinary research combining materials science, acoustics, computer vision, and sustainable engineering. He has made significant contributions to the understanding of phononic crystals for sound absorption, development of biodegradable acoustic materials from agricultural waste, and computer vision applications for non-destructive evaluation. His work bridges fundamental material properties with practical engineering applications, particularly in the areas of noise control and structural health monitoring. Scientific Awards: Best PhD thesis award 2017 Distinguished Teaching Fellow 2015-16 during PhD Dr. Chindam teaches several courses at IIT Kanpur including ME222A (Nature and properties of materials), ME321A (Advanced mechanics of solids), ME698E (Fabrication and mechanics of thin films), ME621A (Introduction to solid mechanics), ME683A (Techniques in non-destructive evaluation), and ME723A (Wave propagation in solids). His teaching approach integrates theoretical concepts with practical applications, particularly in the areas of material characterization and wave mechanics. While specific grant information isn't detailed in the provided text, his research output suggests involvement in projects related to acoustic metamaterials, non-destructive evaluation techniques, and sustainable material development. His laboratory work focuses on developing advanced characterization techniques for materials, particularly in the areas of acoustic metamaterials and thermal nondestructive evaluation. His team appears to work at the intersection of computational mechanics, experimental characterization, and sustainable materials development, with emphasis on practical applications for noise control and structural health monitoring.
K S Venkatesh is a Professor in the Department of Electrical Engineering at Indian Institute of Technology Kanpur (IIT Kanpur). His research spans multiple areas of signal and image processing with applications in computer vision and robotics. Education: PhD from IIT Kanpur M.Tech from IIT Kanpur B.E. from Bangalore University Professor Venkatesh's research focuses on signal processing, image and video processing, computer vision with applications in robotics, and signal and system theory . His work bridges theoretical foundations with practical applications, particularly in the domain of visual perception systems. He has made significant contributions to areas such as object occlusion handling, gesture recognition under challenging lighting conditions, image enhancement techniques, and efficient stereo depth computation. His recent publications demonstrate a strong focus on computer vision problems with practical applications. The research shows progression from fundamental signal processing techniques to more complex vision systems capable of operating in real-world conditions. Several of his papers have received recognition, including Best Paper Awards at prominent conferences. Scientific Awards: Best Paper Award at Second Michael Faraday IET India Summit 2013 Best Paper Award at IEEE INDICON, IIT Bombay, December 2013 Professor Venkatesh maintains active research collaborations, as evidenced by his co-authored publications with researchers from various institutions. His work appears in prestigious international conferences including IJCAI, IEEE INDICON, and specialized computer vision conferences. His office is located in room 207-A/ACES at the Department of Electrical Engineering, IIT Kanpur, where he leads research activities in signal and image processing.
