Find Academic Supervisors

Rahmatullah RocheView profile

Assistant Professor

• Computational Biology
• Applied Machine Learning
• Data Science
• +1 more

Rahmatullah Roche serves as an Assistant Professor in the Department of Computer Science at Columbus State University's TSYS School of Computer Science, joining the tenure-track faculty in Fall 2024. His academic credentials include: Ph.D. in Computer Science and Applications from Virginia Tech (2024) M.S. in Computer Science and Software Engineering from Auburn University (2021) B.S. in Computer Science and Engineering from Bangladesh University of Engineering and Technology (2016) Dr. Roche's research spans Computational Biology , Applied Machine Learning , Data Science , and Human-Computer Interaction , with primary focus on macromolecular predictive modeling for intra- and inter-molecular interactions using cutting-edge AI techniques. His work bridges computer science and biology to solve complex structural bioinformatics challenges. Analysis of his 14 publications (2020-2025) reveals a consistent trajectory in applying deep learning—particularly transformer networks, equivariant graph neural networks, and biological language models—to protein-RNA complex prediction, protein-nucleic acid binding, and protein-protein interaction site identification, published in high-impact journals including Cell Systems and Nucleic Acids Research. Key scientific recognitions include: Pratt Fellowship Award (2023-2024) Turner College Research Award (2025) Professional Development Award for Core Course redesign (2025) Core Course Design Institute Professional Development Award (2024) 3rd place Flash Talk award at VT GPSS Symposium (2024) Best Poster Award at ACM-BCB 2020 YSEA Finalist Travel Award at MCBIOS 2024 Dr. Roche actively recruits undergraduate and graduate students for his research lab while securing resources through NSF ACCESS grants. His teaching portfolio includes Computer Science I, Computer Organization, and Graphical User Interface Development, complemented by service as Discipline Coordinator for Web Development and reviewer for top bioinformatics journals. His research group collaborates with Virginia Tech on advancing biomolecular modeling through interdisciplinary AI applications.

• Artificial Intelligence
• Machine Learning
• Argumentation Theory
• +3 more

Benoît ALCARAZ is a Researcher affiliated with the Department of Computer Science at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM). His work focuses on advancing artificial intelligence and machine learning, particularly in ethical AI frameworks, argumentation systems, and natural language processing. He is based at the Maison du Nombre research facility in Esch-sur-Alzette. Research Interests include developing algorithms for ethical decision-making in AI, optimizing machine learning models through evolutionary techniques, and creating user-centric NLP tools for real-time applications. His work bridges theoretical computer science with practical ethical considerations, as seen in his exploration of bias mitigation in visual learning and argumentation-based reinforcement learning agents. Notable contributions include frameworks like Ajar for ethical reinforcement learning and IRRMA for image-based meeting assistants. While no explicit awards or grants are listed, his publications indicate active involvement in interdisciplinary AI research with a focus on societal impact.

• Cancer Genomics
• Bioinformatics
• Oncology
• +5 more

Prof. Giovanni Tonon is a Full Professor at Vita-Salute San Raffaele University and holds key leadership roles including Director of the Center for Omics Sciences and Head of the Functional Genomics of Cancer Unit at the San Raffaele Scientific Institute in Milan, Italy. His academic journey includes a Medical Degree from the University of Padua (110/110 cum laude) and a PhD in Clinical Methodology from the University of Milan. He has held prestigious positions at institutions like Harvard Medical School and the NIH in the US. His research focuses on genomic and bioinformatics approaches to identify cancer-related genes/pathways, with particular emphasis on multiple myeloma and CAR T-cell therapies. He has pioneered studies on DNA damage responses in cancer and developed novel diagnostic/therapeutic technologies. His work integrates molecular oncology, epigenetics, and precision medicine. Prof. Tonon has secured major awards including the Leukemia & Lymphoma Society Special Fellow Award (2006-2009) and holds 7 patents related to cancer diagnostics and therapies. He actively contributes to teaching, leading courses in Molecular Oncology, Gene Expression Analysis, and Scientific Writing at San Raffaele University. His research group collaborates internationally, driving initiatives like the DigiONE federated learning system for precision oncology. Education: PhD in Clinical Methodology, University of Milan (2002) Medical Degree, University of Padua (1992) Music Professor Certification in Piano, Conservatory of Venice (1989) Key Roles: Director, Center for Omics Sciences (2016-present) Unit Head, Functional Genomics of Cancer (2008-present) Professor of Molecular Oncology (2008-2016) His lab focuses on translating genomic discoveries into clinical applications, with recent work advancing CAR T-cell therapies for colorectal cancer and developing federated learning systems for oncology research. He maintains active participation in doctoral programs in Neurocognitive Sciences and serves on institutional research committees.

Tomonari FurukawaView profile

Professor

• Robotics
• Computational Mechanics
• Autonomous Systems
• +3 more

Tomonari Furukawa is a Professor and Zinn Faculty Scholar at the University of Virginia, leading the VICTOR Lab. He holds a B.Eng. in Mechanical Engineering from Waseda University (1990), an M.Eng. in Mechatronic Engineering from the University of Sydney (1993), and a Ph.D. in Quantum Engineering and Systems Science from the University of Tokyo (1996). His research focuses on robotics, computational mechanics, autonomous systems, and advanced sensor technologies. He has published over 300 papers, contributed to editorial boards, and secured grants such as the U.S. DOD DURIP grants for advanced research infrastructure. His work spans topics like autonomous robotic mapping, sensor fusion, and real-time deformation measurement for automotive safety. He has developed systems for tire tread profiling, crash deformation analysis, and 3D road surface reconstruction. Furukawa’s methodologies often integrate Bayesian approaches, neural networks, and multi-sensor data fusion to solve complex engineering challenges. His contributions to the NSF I/UCRC Centre for Tire Research highlight his impact on applied mechanics. Recipient of multiple career and paper awards, Furukawa emphasizes translational research. His VICTOR Lab explores cutting-edge robotics, including compliant bipedal designs for disaster response (e.g., DARPA Robotics Challenge) and autonomous navigation systems. Current projects leverage AI and advanced vision systems for infrastructure monitoring and human-robot collaboration.

• Hardware Design
• VLSI Systems
• Digital Circuit Optimization
• +4 more

Rajkumar Sarma is a Research Fellow at the Department of Computer Science & Information Systems at Lero – the Research Ireland Centre for Software, University of Limerick. His work focuses on hardware design, VLSI systems, and optimization techniques for digital circuits. He specializes in areas such as low-power architectures, floating-point arithmetic, and evolutionary algorithms for automated design. His research emphasizes hardware-software co-design, reliability analysis under PVT (Process, Voltage, Temperature) variations, and efficient implementations of multiply-accumulate (MAC) units critical to digital signal processing and image processing applications. Key technical contributions include the development of the UCM algorithm for delay optimization, grammatical evolution for synthesizable HDL code generation, and novel approaches to reduce power consumption in MAC architectures. His work bridges theoretical algorithmic innovation with practical VLSI implementation challenges, addressing both performance and reliability under extreme operating conditions. Rajkumar’s publications span 2012–2025, with a strong focus on digital circuit design, including hybrid adders, low-power flip-flop implementations, and quantum gate-based reversible circuits. His research also extends to reliability analysis of electronic components like multi-layer ceramic capacitors. He has utilized advanced simulation tools such as Cadence ADE-XL for accelerated PVT analysis, demonstrating expertise in both computational modeling and hardware validation. While no specific awards or grants are listed, his extensive publication record reflects sustained engagement with cutting-edge challenges in computer architecture and VLSI systems design.

Peter RobinsonView profile

Research Fellow

• Computer Science
• Software Verification
• Formal Methods
• +6 more

Dr. Peter J. Robinson is an Honorary Research Fellow at the School of Electrical Engineering & Computer Science, The University of Queensland. His academic career spans over three decades, focusing on foundational research in programming languages, formal methods, and distributed systems. His work includes contributions to Qu-Prolog, a multi-threaded Prolog implementation, and TeleoR, a robotic task programming framework. Research interests include agent-based systems, blockchain security for aerospace applications, software verification, concurrent programming, and education technology. Notable projects include the Pedro publish/subscribe server and MyPyTutor, an interactive Python learning tool. He has collaborated on railway safety protocols and spacecraft control systems using blockchain. Publications span journals like Formal Aspects of Computing and conferences such as IEEE Symposium on Computers and Communications. Technical reports include work on unification algorithms and multi-agent verification frameworks. He has advised on projects involving IoT architectures and swarm intelligence simulations.

• Health Economics
• Applied Microeconomics
• Industrial Organization

Assoc Prof Yang Zhang is an Associate Professor in the School of Economics at the National University of Singapore , Department of Economics. He has been affiliated with the university since 2012, progressing from Lecturer (2012-2015) to Senior Lecturer (2016-2021) and currently Associate Professor since 2022. Education: PhD in Managerial Economics and Strategy (Northwestern University, 2011) BA in Economics (Peking University, 2005) Research Interests: Health Economics Applied Microeconomics Industrial Organization Recent Research Trends focus on leveraging deep learning and structural biology tools for protein structure prediction, RNA modeling, and computational drug design. His work integrates advanced algorithms with large-scale metagenomic data to improve accuracy in complex biological system modeling.

Cameron D. SilerView profile

Associate Professor

• Biodiversity Science
• Conservation Biology
• Microbiomics
• +6 more

Cameron D. Siler is an Associate Professor and Associate Curator of Herpetology at the Sam Noble Museum of Natural History, affiliated with the University of Oklahoma's School of Biological Sciences. He holds the Robert Glenn Rapp Foundation Presidential Professorship. His research focuses on evolutionary processes in amphibians and reptiles, combining phylogenetics, microbiomics, and conservation biology. Siler leads field expeditions in Southeast Asia and Oklahoma, emphasizing biodiversity surveys and disease studies. Education: PhD (Honors) in Ecology & Evolutionary Biology from University of Kansas; BS (High Honors) in Ecology & Evolutionary Biology from University of Texas. Research interests include phylogenetic diversification patterns, microbiome-host interactions, and conservation strategies for threatened species. He advises multiple graduate students and leads projects like environmental DNA (eDNA) assays for species detection. Siler collaborates with agencies on wildlife monitoring and has mentored lab members in fieldwork and genomic analyses. His lab's work spans from Oklahoma's Red Slough ecosystems to Philippine crocodile conservation. Recent studies address amphibian disease dynamics, microbial community drivers, and Bayesian phylogenetic methods. Siler has conducted field expeditions with students, documented new species discoveries, and contributed to biodiversity databases. His outreach includes undergraduate training and public education via museum programs.

Fatemeh VafaeeView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Systems Biology
• +5 more

Associate Professor Fatemeh Vafaee is a leading researcher at the University of New South Wales (UNSW) , holding appointments as Associate Professor in the School of Biotechnology and Biomolecular Sciences (BABS) and Deputy Director (Science) of the UNSW AI Institute . She previously served as Deputy Director of the UNSW Data Science Hub (uDASH) and has held academic positions at the University of Toronto and the University of Sydney. PhD in Artificial Intelligence from University of Illinois at Chicago Postdoctoral Fellowships at University of Toronto and University of Sydney Founded the AI-Enhanced Biomedicine Laboratory in 2017 Her research focuses on deploying advanced AI techniques to address biomedical challenges through: Biomarker Discovery for cancer and neurodegenerative diseases Single-Cell Multi-Omics data integration and analysis Computational Drug Repositioning and network pharmacology Multi-Omics Data Fusion and temporal network modeling Recent publications demonstrate expertise in liquid biopsy development , single-cell imaging , and AI-driven cancer diagnostics . Her methodological contributions include novel deep learning architectures for omics data analysis and graph neural networks for drug synergy prediction. Scientific accolades include: Winner, Women in AI Asia-Pacific Health Award (2023) Runner-Up, WAI-APAC Innovator of the Year (2023) Top 10 Women in AI in Asia-Pacific (2023) Australian Bioinformatics and Computational Biology Society Research Excellence Award (2023) She supervises PhD candidates across computational biomedicine and AI in healthcare , with significant grant achievements exceeding $17M in competitive funding, including schemes from ARC Discovery , NHMRC , and Medical Research Future Fund .

Yuan YaoView profile

Assistant Professor

• Computer Architecture
• Parallel Computing
• Power and Thermal Management
• +7 more

Yuan Yao serves as an Assistant Professor in the Department of Information Technology at Uppsala University, Sweden. His academic role spans teaching and research within the Computer Systems division, focusing on cutting-edge computer architecture and parallel computing systems. He maintains active collaborations across international institutions, particularly in energy-efficient hardware design and emerging computing paradigms. His educational journey includes: B.S. in Micro-electronics from Northwestern Polytechnical University, China (2009) M.S. in System-on-Chip Design from KTH Royal Institute of Technology, Sweden (2014) Ph.D. in Electrical Engineering and Computer Science from KTH Royal Institute of Technology (2019) Yao's research centers on power and thermal management for chip multi-processors, Network-on-Chips (NoCs), and GPUs. He pioneers hardware/software co-design for high-performance computing, coherency mechanisms for emerging memory technologies, and performance analysis of on-chip networks. Recent work expands into neural network acceleration and battery-less Internet of Things architectures, reflecting a trajectory toward energy-constrained specialized systems. His methodology integrates formal modeling with practical implementation for real-world impact. Publication trends reveal consistent innovation in energy efficiency across parallel architectures. From foundational DVFS techniques for NoCs (2016-2018) to recent breakthroughs in battery-less IoT (2023-2024), his work demonstrates evolutionary progression toward novel computing domains. Key thematic threads include thermal-aware optimization, memory consistency protocols, and hardware acceleration for AI workloads, with applications spanning data centers to embedded systems. Scientific recognition includes: Best paper candidate at IEEE International Symposium on High Performance Computer Architecture (HPCA) 2018 for in-network packet generation research Yao actively supervises graduate researchers and leads collaborative projects in computer architecture. His grant portfolio supports work on battery-less IoT systems and neural network accelerators, though specific funding details aren't publicly enumerated. Current projects emphasize sustainable computing through novel architectures for energy-harvesting environments. He operates within Uppsala University's Computer Systems division, contributing to research groups focused on hardware acceleration, embedded systems, and networked architectures. His lab environment fosters interdisciplinary work bridging computer architecture, energy harvesting, and machine learning for next-generation computing platforms.

Maria SchweigelView profile

Professor

• Artificial Intelligence Algorithms
• Optimization Techniques
• Software Development
• +4 more

Professor Maria Schweigel Prof. Maria Schweigel is a Professor at the Department of Autonomous Systems, Schmalkalden University of Applied Sciences. Her teaching focuses on automation control, electronic control systems, robotics, and embedded systems. She leads the research group 'Eingebettete Diagnosesysteme' (Embedded Diagnostic Systems) and specializes in artificial intelligence algorithms, optimization using genetic and evolutionary methods, and biosignal analysis for anesthesia and sleep studies. Her research spans robotics, embedded systems, image processing, and software development with tools like C/C++, MATLAB/Simulink, and LabView. Key projects include real-time EEG classification for anesthesia monitoring, low-SNR biomedical signal extraction, and SVM-based classification on resource-constrained platforms. She has contributed to international conferences like ECT and IWK TU Ilmenau, focusing on interdisciplinary applications in medical technology and autonomous systems. No scientific awards were explicitly listed in the provided materials. Her advising and grants are not detailed here, but her extensive publication record (2009–2016) demonstrates active involvement in collaborative research with colleagues like Wenzel, Walther, and Baumgart-Schmitt. She co-developed tools such as the Multi-EEG-Viewer and explored wireless biomedical signal transmission for relaxation control systems.

Daryl TrumboView profile

Researcher

• Conservation Biology
• Genetics
• Ecology
• +3 more

Daryl Trumbo is a researcher specializing in conservation genetics, evolutionary biology, and wildlife ecology. His work focuses on understanding how human activities such as hunting, urbanization, and habitat fragmentation impact genetic diversity, population structure, and disease dynamics in wild animal populations. He has conducted extensive studies on large carnivores like pumas and bobcats, examining viral transmission and the genetic consequences of human disturbance. His research also explores invasive species adaptation, such as the cane toad in Australia, and uses cutting-edge genomic tools to model species' responses to environmental pressures. Key themes include the interplay between landscape connectivity, host relatedness, and pathogen spread, as well as the development of novel methods like machine learning for genomic analysis. Research Interests: Conservation genomics, viral evolution in wildlife, urban-wildlife interactions, invasive species adaptation, and genetic connectivity. Methodologies: Integrates genomic data with ecological sampling, landscape genetics, and computational modeling. Trumbo's publications highlight the importance of considering anthropogenic factors in species conservation, particularly for endangered and keystone species. His work bridges ecological and genetic perspectives to inform management strategies aimed at preserving biodiversity in rapidly changing environments.

• Machine Learning
• Automated Machine Learning (AutoML)
• Hyperparameter Optimization
• +3 more

Janek Thomas is a researcher actively contributing to the fields of Machine Learning and Automated Machine Learning (AutoML). His work focuses on hyperparameter optimization, multi-objective algorithms, and improving the interpretability of machine learning models. Collaborating with institutions like TU Munich and LMU Munich, he has authored over 35 publications since 2016. Key contributions include the AMLB benchmark suite for AutoML systems and foundational research on multi-objective hyperparameter tuning. His research bridges theoretical advancements with industrial applications, emphasizing robust model verification and scalable optimization techniques.

• Animal Vision
• Color Perception
• Evolutionary Biology
• +3 more

Prof Daniel Colaco Osorio is a Professor of Neuroscience (Ecology and Evolution) at the University of Sussex, affiliated with the School of Life Sciences. He serves as Deputy Head of the School and Director of Taught Programmes. Osorio holds a BA and MA in Natural Sciences from the University of Cambridge (specializing in Zoology) and a PhD in Neurobiology from the Australian National University (ANU), focusing on insect visual physiology. His postdoctoral work spanned Cambridge and ANU before joining Sussex in 1992. His research explores animal vision, particularly color perception and object recognition in species like butterflies, primates, birds, and cephalopods. He also holds a patent for color measurement in images, derived from his theoretical work on animal vision, with potential medical applications. Osorio sits on the Biotechnology and Biological Sciences Research Council’s research committee and contributes to ethical guidelines for cephalopod welfare under EU legislation. He chairs the Ethics Committee for Merlin Entertainments’ aquaria/zoo operations and co-authored guidelines for cephalopod research ethics. Research interests span visual ecology, evolutionary signaling, and the neural mechanisms underlying camouflage and color discrimination. Notable grants include studies on cephalopod visual behavior, avian spectral processing, and the evolution of trichromacy in primates. He organizes courses like 'Receptors and Senses' and 'Seminars in Neuroscience.' Osorio’s recent work bridges biology and technology, applying vision science to medical imaging and legal frameworks. His lab collaborations emphasize interdisciplinary approaches to understanding sensory systems across species.

• Signal Processing
• Machine Learning
• Acoustic Engineering
• +5 more

Manuel Rosa Zurera is a Full Professor at the Universidad de Alcalá, specializing in Signal Theory and Communications. He leads the AES3 research group focused on Acoustic and Electromagnetic Smart Sensor Networks and Signal Processing. His research emphasizes machine learning applications in audio analysis, biomedical signal processing, and passive radar systems. Dr. Rosa holds a PhD from Universidad de Alcalá (1999), supervised by Francisco López Ferreras. Research Interests : Dr. Rosa’s work spans acoustic signal localization, UAV detection, emotion recognition via speech analysis, and evolutionary studies of hominin auditory systems. His innovations include robust detection algorithms for passive radar, energy-efficient anger detection systems, and age/gender classification from speech using neural networks. He has pioneered acoustic sensor networks for urban security and biomedical diagnostics. Key Contributions : Over 150 peer-reviewed articles since 1999 demonstrate his expertise in signal processing for aerospace flutter analysis, real-time violence detection in smart cities, and 3D reconstruction of Neanderthal auditory capacities. His work bridges theoretical signal processing with practical applications in healthcare, surveillance, and evolutionary anthropology. Labs/Teams : Directs the AES3 group and collaborates on EU-funded projects like DVB-T radar systems and acoustic drone detection initiatives. Active in designing microphone arrays for hearing aids and wireless sensor networks.