جست‌وجوی استاد و پژوهشگر

Muhammad Ali Babarمشاهده پروفایل

استاد

• Software Security & Privacy
• Big Data Platforms & Architectures
• Empirical Software Engineering
• +۶ مورد دیگر

Muhammad Ali Babar is a Professor in the School of Computer Science at the University of Adelaide. He leads a theme on architecture and platform for security as service in the CyberSecurity Cooperative Research Centre (CSCRC), which has an estimated budget of A$140 Millions over 7 years with A$50 Millions provided by the Australian government. Prof Babar has established CREST (Centre for Research on Engineering Software Technologies), directing the research, education, and engineering activities of more than 25 researchers and engineers. He has attracted more than $12 Millions in funding from industry and government since 2017. Prof Babar's research focuses on Secure Software Systems and Services for emerging technologies including Cloud Computing, Edge Computing, Internet of Things (IoT), and Big Data. His work sits at the intersection of Software Engineering, Artificial Intelligence (ML/NLP), and Cyber Security, employing empirical research methods both qualitative and quantitative. His recent publications demonstrate a strong emphasis on vulnerability prediction, secure microservices management, and applying large language models to security challenges. With over 320 peer-reviewed scientific papers and 17,763 citations (h-index 66 as of January 2025), Prof Babar ranks among the leading Software Engineering researchers in Australia and New Zealand. His research has been recognized with the most influential paper award for the Australasian Software Engineering Conference in 2014 and multiple best paper awards at international conferences. Most influential paper for Australasian Software Engineering Conference (2014) Multiple best paper awards at international conferences Prof Babar obtained his Ph.D. in Computer Science and Engineering from the University of New South Wales, Australia. His research is conducted in collaboration with industry and government partners including DST, ActewAGL, TSS, ATO, Jemena, Cisco, DST Group, Health SA, and Defence SA, as well as key players in the Australian Cyber Security ecosystem such as AustCyber, Data61, DST Group, Oceania Cyber Security Centre, and Australian Cyber Collaboration Centre (AC3). Prof Babar is eligible to supervise Masters and PhD students and has led high-performing R&D teams that have successfully carried out high-quality research in close collaboration with industry. His leadership in the Cyber Security Cooperative Research Centre represents a significant contribution to Australia's cyber security research capabilities and industry engagement.

Amiangshu Bosuمشاهده پروفایل

دانشیار

• Empirical Software Engineering
• Code Reviews
• Software Security
• +۸ مورد دیگر

Amiangshu Bosu is a tenured Associate Professor in the Department of Computer Science at Wayne State University's College of Engineering. Previously, he served as a tenure-track Assistant Professor at Southern Illinois University Carbondale from 2016-2018. His academic journey includes completing his Ph.D. at the University of Alabama in 2015 under Professor Jeffrey Carver, followed by postdoctoral research with Dr. Danfeng Yao at Virginia Tech. His educational background reflects a strong foundation in software engineering research, with his doctoral work focusing on empirical approaches to software development practices. This foundation has enabled his current research trajectory examining human aspects of software engineering. Bosu's research program centers on empirical software engineering with particular emphasis on code review dynamics, toxicity detection in developer communications, and diversity issues in open source communities. His work bridges technical analysis with social science perspectives, investigating how communication patterns affect participation, especially regarding gender dynamics in OSS projects. Recent work increasingly incorporates natural language processing and machine learning techniques to build tools like ToxiCR for automated toxicity detection in code reviews. Analysis of his publication record reveals a clear evolution toward examining social dynamics in software development, with growing emphasis on gender bias, toxicity, and diversity issues. His research consistently applies empirical methods to understand real-world developer experiences while developing practical tools to improve code review processes and community health. His scientific recognition includes the prestigious NSF CAREER award (2024), NSF CRII award (2019), and Wayne State University's College of Engineering Research Excellence award (2025). He maintains senior membership status in both ACM and IEEE, reflecting his standing in the computing community. NSF CRII award (2019) NSF CAREER award (2024) College of Engineering Research Excellence award (2025) Senior Member of ACM Senior Member of IEEE Bosu actively contributes to the software engineering research community through service on program committees for major conferences including ICSE, ASE, ESEC/FSE, and ESEM. His GitHub presence (amiangshu.me) demonstrates active engagement with research tools and datasets, particularly those related to code review analysis and toxicity detection. While specific lab structure isn't detailed in the provided materials, his research group appears focused on empirical studies of software development practices with strong connections to industry through collaborations on projects like Chromium OS security analysis.

• Trustworthy Machine Learning
• Program Synthesis
• Formal Verification
• +۳ مورد دیگر

Osbert Bastani serves as an Associate Professor in the Department of Computer and Information Science at the University of Pennsylvania. He leads the trustml@Penn research group and holds affiliations with the ASSET, PRECISE, and PRiML research centers, as well as PLClub. His academic work centers on developing reliable and interpretable artificial intelligence systems through interdisciplinary approaches combining programming languages, formal methods, and machine learning. He earned his Ph.D. in Computer Science from Stanford University under the guidance of Alex Aiken, followed by a postdoctoral position at MIT working with Armando Solar-Lezama. This foundation in both theoretical computer science and practical systems has shaped his research trajectory. Bastani's primary research areas include Trustworthy Machine Learning (focusing on robustness against adversarial attacks, fairness in algorithmic decision-making, and explainable AI), program synthesis, and formal verification. His recent publications address critical challenges in large language models, such as defending against jailbreaking attacks and ensuring trustworthy retrieval-augmented generation. He also develops methods for conformal prediction under distribution shifts and neurosymbolic program synthesis for complex tasks like web question answering. His teaching portfolio features advanced courses including CIS 7000: Trustworthy Machine Learning and CIS 4190/5190: Applied Machine Learning, where he integrates cutting-edge research into the curriculum. Through his research group, he mentors graduate students on projects spanning neurosymbolic programming, uncertainty quantification, and fairness in sequential decision-making. As an active member of Penn's research ecosystem, Bastani contributes to the ASSET center's mission of building secure systems, PRECISE's work on cyber-physical systems, and PRiML's machine learning initiatives, while collaborating with PLClub on programming language innovations.

Gül Calikliمشاهده پروفایل

دانشیار

• Human aspects in software engineering
• Empirical software engineering
• Cognitive psychology in software development
• +۶ مورد دیگر

Gül Calikli is an Associate Professor (Senior Lecturer) in Software Engineering at the School of Computing Science, University of Glasgow, United Kingdom. She has held academic positions at several prestigious institutions including the University of Zurich as a senior researcher, Chalmers | University of Gothenburg as a lecturer, and postdoctoral fellowships at The Open University (UK) and Ryerson University (Canada). Dr. Calikli earned her Ph.D. in Computer Engineering from Boğaziçi University in Istanbul. Her academic journey reflects a strong commitment to advancing empirical software engineering with a focus on human aspects. Dr. Calikli's research centers on the intersection of software engineering and cognitive psychology, with a particular emphasis on understanding and mitigating cognitive biases in software development practices. Her work explores how human cognitive limitations impact program comprehension, code review, and vulnerability detection. She investigates how to present information effectively to software practitioners considering human cognitive constraints, and develops tools and techniques based on cognitive psychology to enhance decision-making in software development. Her research also incorporates machine learning systems with "human in the loop" approaches, creating joint cognitive systems that extend human intelligence. Analysis of Dr. Calikli's recent publications reveals a consistent focus on human aspects in software engineering, particularly examining cognitive biases like confirmation bias and their impact on software quality. Her work spans multiple domains including code review practices, vulnerability detection, program comprehension, and privacy-aware software development. A notable trend is her methodological approach combining controlled experiments, field studies, and quantitative analysis of system logs to investigate human factors in software engineering. Best Paper Award at ESEM2013 (Industry Track) Chalmers Area of Advance SEED Funding in 2018 ACM SIGSOFT Distinguished Artifact Award at ICSE 2020 ACM Distinguished Paper Award at ICSE 2021 ACM SIGSOFT Distinguished Paper Award at ESEC/FSE'22 Distinguished Reviewer Award at ICSME'23 Distinguished Reviewer Award at ICPC'22 Dr. Calikli actively supervises PhD students working on diverse topics including team dynamics in agile development, eye-tracking for human-AI pair programming, leveraging LLMs for software development/testing, and sustainability in software engineering teams. She has served on numerous program committees for major software engineering conferences including ASE, ICSE, FSE, and ESEC/FSE. Her research has been supported by various funding mechanisms, including the Chalmers Area of Advance SEED Funding. As an active member of the software engineering community, Dr. Calikli contributes to the advancement of the field through her service on editorial boards (including ACM Transactions on Software Engineering and Methodology), participation in the EPSRC Peer Review College, and organization of conference tracks such as the ICPC 2024 ERA Track which she co-chaired.

Jingyue Liمشاهده پروفایل

استاد

• Software Engineering
• Software Security
• Software Engineering and AI
• +۲ مورد دیگر

Jingyue Li is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. in Software Engineering from NTNU in 2006 and has extensive industrial experience including positions at IBM and DNV Research and Innovation. Her educational background includes: Ph.D. in Software Engineering from NTNU (2006) Professor Li's research spans several key areas in software engineering with a focus on both theoretical and practical applications. Her work bridges traditional software engineering practices with emerging technologies, particularly in the domain of security and blockchain systems. She has conducted extensive empirical research and applied design science methodologies to develop innovative tools and approaches. Her recent publications demonstrate a strong trend toward blockchain technologies, software security, and the intersection of AI with software engineering. The research shows increasing focus on practical applications of blockchain in decentralized autonomous organizations, consensus protocols, and security vulnerabilities in smart contracts. There's also significant work on integrating security practices into DevOps (DevSecOps) and applying machine learning techniques to software engineering problems. Professor Li has received recognition through her leadership roles in major conferences: General Chair for FSE 2025 (The ACM International Conference on Foundations of Software Engineering) Member of the EASE (International Conference on Evaluation and Assessment in Software Engineering) steering committee In terms of research leadership, Professor Li has served as Principal Investigator (PI) or Key Scientist on numerous research projects including TRACE4EU (2023-2025), PaaSforChain (2020-2023), CyberSmart (2017-2020), and several others focused on blockchain, security, and software engineering. She has also conducted research visits to institutions including University College London, University of Washington, Hiroshima University, and Peking University. Her research group appears to be actively engaged in both theoretical and applied research, with strong industry connections through projects like CyberSmart and SecureCyber that address real-world challenges in cybersecurity and smart city infrastructure.

Yun Linمشاهده پروفایل

دانشیار

• Automatic programming
• Software debugging
• Software testing
• +۸ مورد دیگر

Yun Lin is an Associate Professor and Deputy Head of the Department of Computer Science and Technology at Shanghai Jiao Tong University's School of Computer Science. Prior to joining SJTU, Lin served as a Research Assistant Professor at the National University of Singapore working with Prof. Dong Jin Song. Lin leads the CoPhi ("Code Philia") research group, which focuses on the intersection of Software Engineering, AI, and Security. Lin's research spans three major areas: Automatic Programming (including code editing, software testing, and debugging), Explainable AI (focusing on representation interpretation and training data attribution), and Web Misinformation (particularly phishing and scam detection). The research has resulted in numerous tools including CoEdPilot for code editing recommendation, DeepDebugger for interactive debugging of deep classifiers, and Phishpedia for phishing webpage detection. Lin's recent publications demonstrate a strong trend toward integrating AI techniques, particularly large language models and vision language models, with traditional software engineering and security tasks. The work shows increasing sophistication in understanding project context, handling interactive nature of programming tasks, and addressing security challenges in the age of generative AI. Key themes include consistency-based approaches for anomaly detection, agent-based frameworks for complex tasks, and hybrid models that combine symbolic reasoning with neural approaches. ACM Distinguished Paper Award in ICSE'18 for "Towards Optimal Concolic Testing" Distinguished Reviewer Award in FSE'25 2nd prize Research Prototype Award in ChinaSoft'24 Lin advises a large team of PhD, Master's, and undergraduate students, with several publications co-authored with students appearing in top venues. Current research is supported by collaborations with National University of Singapore, particularly with Prof. Dong Jin Song, and includes projects on code editing, GUI testing, and phishing detection. The CoPhi group maintains active development of multiple research tools and datasets. The CoPhi research group under Lin's leadership focuses on building practical tools that bridge the gap between theoretical advances and real-world programming and security challenges. The group's work spans from fundamental program analysis techniques to applied security solutions, with an increasing emphasis on leveraging AI capabilities while maintaining explainability and reliability.

Imke Engelhardtمشاهده پروفایل

استاد

• Steel Construction
• Welding Technology
• Fatigue and Fracture
• +۳ مورد دیگر

Prof. Dr.-Ing. Imke Engelhardt serves as a Professor in the Faculty of Civil Engineering and Building Services Engineering at Munich University of Applied Sciences, where she manages the Steel Construction and Welding Technology Division within the Laboratory for Steel and Light Metal Construction. Her expertise centers on fatigue analysis, corrosion engineering, and life extension techniques for steel structures, with significant contributions to offshore wind energy infrastructure. Dr. Engelhardt's research program demonstrates consistent focus on high-frequency hammer peening (HFMI) and related post-weld treatments to enhance fatigue resistance in welded steel joints. Her 15 most recent publications reveal strong thematic continuity in corrosion-fatigue interactions, offshore structural applications, and standardization of life extension methodologies. The work bridges theoretical mechanics with practical engineering solutions, particularly for wind turbine towers and bridges exposed to marine environments. As an active delegate to the European Standardization Committee (ECCS TC 6 "Fatigue and Fracture") and member of key organizations including the International Institute of Welding (IIW), DVS Research Association, and FOSTA, she directly influences industry standards. Her leadership in the IGF-funded project (2015-2017) on corrosion effects in offshore wind energy plants exemplifies her commitment to translating research into practical engineering solutions while managing large-scale structural testing facilities.

• Cognitive Neuroscience
• Visual Perception
• Perceptual Learning
• +۵ مورد دیگر

Professor Caspar M. Schwiedrzik is a Research Professor in the Department of Cognitive Neurobiology at the Faculty of Biology and Biotechnology, Ruhr University Bochum. He serves as a Principal Investigator at the Research Department of Neuroscience, where he leads a research group investigating the neural basis of learning and cognitive flexibility. His research focuses on understanding how organisms adapt to changing environments through perceptual learning mechanisms, with particular emphasis on the visual system. Professor Schwiedrzik employs a comparative approach across species using multimodal techniques including electrophysiology, neuroimaging, and computational modeling to identify fundamental principles of neural adaptation. His work bridges cognitive neuroscience, vision science, and computational approaches to unravel how the brain detects environmental changes and adjusts behavior accordingly. Analysis of recent publications (2015-2024) reveals a consistent research trajectory focused on visual perception, face processing, and learning mechanisms. The work demonstrates increasing methodological sophistication with a shift toward more complex questions about predictive coding, neural plasticity, and cross-species comparisons. Key trends include growing emphasis on top-down processing mechanisms, the role of statistical learning in visual adaptation, and the neural basis of perceptual generalization. Professor Schwiedrzik has established productive collaborations with leading neuroscience institutions, as evidenced by co-authorships with researchers from institutions including New York University. His research program appears well-funded, supporting multiple high-impact publications annually in top neuroscience journals. The lab maintains strong international connections while being firmly rooted in the neuroscience research ecosystem at Ruhr University Bochum. The lab focuses on understanding the brain's capacity for adaptation to environmental changes, particularly through visual learning mechanisms. Current projects investigate how predictions shape visual processing, how perceptual learning generalizes across different effectors, and how neural representations support flexible decision-making. This research provides fundamental insights into both normal cognitive function and potential pathways to maladaptive states when learning mechanisms fail.

• Cognitive Neuroscience
• Computational Modeling
• Predictive Coding
• +۴ مورد دیگر

Ryszard Auksztulewicz serves as Visiting Professor and Group Leader of the Prediction and Memory unit within the Department of Education and Psychology at Freie Universität Berlin. Based at Habelschwerdter Allee 45, Room JK 25/220 in Berlin, he leads research at the intersection of cognitive and systems neuroscience. His research focuses on neural mechanisms of prediction, attention, and memory , employing multimodal approaches including EEG, fMRI, MEG, ECoG, TMS, electrophysiology, and calcium imaging. He integrates these with computational modeling (Bayesian models of neural/behavioral data) and multivariate decoding techniques. Key research themes include: Predictive coding frameworks for understanding sensory processing Neural gain modulation in temporal expectation Auditory cortex representations of memory and prediction Task-dependent modulation of sensory predictions Recurrent processing in perceptual awareness Analysis of his 34 publications (h-index: 18) reveals consistent focus on computational neuroscience approaches to memory systems , with recent work emphasizing cross-species auditory processing and neural representation dynamics. His 2022-2018 publications particularly highlight mechanistic distinctions between "what" and "when" predictions in sensory cortex. Teaching responsibilities include: Probabilistic and Statistical Modeling (Lecture) Introduction to Programming (Seminar) Research Colloquium for Qualification Theses

Ralf Klapdorمشاهده پروفایل

استاد

• International Taxation
• Tax Law
• Transfer Pricing
• +۳ مورد دیگر

Prof. Dr. Ralf Klapdor serves as Professor of Business Administration with a focus on International Taxation at Rhine-Waal University of Applied Sciences' Faculty of Society and Economics. Based at the Kleve Campus, he holds office room 02 01 011 and maintains active roles in both academia and public service as a member of the Kleve district council. His research centers on making taxation systems understandable and predictable, with expertise spanning international tax law, treaty design, and corporate tax reform. Key contributions include developing visual learning tools for complex tax concepts and analyzing audit methodologies for fraud detection in cash-intensive industries. Recent publications reveal evolving research trends from foundational work on European tax treaties (PhD thesis: "Efficient taxation through a European model tax treaty?") toward contemporary applications like Bendford's Law analysis in restaurant industry sales data. His scholarship consistently bridges legal frameworks with economic implications. Professional background includes independent tax consultancy since 1999 and project management for international tax firms. As a doctoral researcher at Duisburg under Prof. Volker Breithecker, he established his specialization in cross-border taxation issues. Personal details: Born in Hüls (Krefeld), married with two children. Regular contributor to "Steuer und Wirtschaft" (StuW) and publisher with Otto Schmidt.

Reinhard Schinkeمشاهده پروفایل

پژوهشگر

• Flood Risk Management
• Climate Change Adaptation
• Groundwater Flooding
• +۳ مورد دیگر

Reinhard Schinke is a Research Associate and Project Manager in the Research Area 'Built Environment - Resources and Environmental Risks' at the Leibniz Institute of Ecological Urban and Regional Development (IOER) in Dresden, Germany, a position he has held since 2011. He holds a Doctorate from Brandenburg University of Technology Cottbus and a Diplom-Ingenieur in Civil Engineering from TU Dresden, specializing in structural engineering. His research focuses on flood and groundwater risk analysis, climate change adaptation strategies, vulnerability assessment of built environments, and development of damage simulation models. Key areas include: Flood resilience technologies for buildings and infrastructure GIS-based flood damage estimation for urban and agricultural systems Monetary valuation of flood prevention measures Groundwater inundation impacts and mitigation Schinke has contributed significantly to interdisciplinary projects like INCREASE (social resilience in climate change) and KlimaKonform (municipal climate adaptation). His publication trends show consistent focus on refining flood damage models, developing geospatial risk assessment tools, and evaluating structural adaptation measures across European case studies. Awards: DAAD Research Fellowship (2011) at University of Western Ontario, Faculty of Engineering He actively participates in expert networks including the BWK (German Association for Water, Waste Management and Cultural Building) working group on high groundwater levels, contributing to technical guidelines and flood risk management frameworks.

Michael Finkelمشاهده پروفایل

استاد

• High-Voltage Engineering
• Power Systems
• Smart Grids
• +۵ مورد دیگر

Prof. Dr.-Ing. Michael Finkel is a full Professor at Augsburg University of Applied Sciences in the Faculty of Electrical Engineering, where he serves as Academic Advisor for International Industrial Engineering, Member of the Faculty Council, and Chair of the Examination Board. His professional affiliations include memberships in CIGRE, IEEE, VDE, and the EMC Project Group of FNN. He received the Bavarian Certificate of Higher Education Teaching in 2009 and multiple research awards including ETG Literature Prizes and Young Author Awards. Professor Finkel's research focuses on High-Voltage Engineering, Power Systems, and Smart Grid technologies. His work addresses critical challenges in renewable energy integration, grid stability, and distributed energy resources. Key research areas include: Island grid operation and emergency power systems Smart grid digitalization and control strategies Electric vehicle integration in urban networks Power system stability and frequency control Renewable energy forecasting and grid integration His recent publications demonstrate strong focus on converter-dominated grids, renewable integration, and smart grid solutions. Research trends show increasing emphasis on real-time grid monitoring, AI applications in power systems, and hybrid energy solutions. Collaborative projects frequently involve industry partnerships and international research networks. Significant scientific recognitions include: ETG Literature Prize 2024 for heat pump load modeling Young Author Award 2025 for hydropower island grid research HSA_transfer Award 2022 for technology transfer Multiple best paper awards at international conferences Professor Finkel actively supervises doctoral candidates in power systems research and leads projects funded by industry and public grants. Current initiatives include developing emergency power solutions for critical infrastructure and advanced monitoring systems for distribution networks. His research group collaborates extensively with the Technology Transfer Centers of Augsburg University and industry partners in the energy sector.

• Liver cancer
• Cirrhosis
• Hepatology
• +۷ مورد دیگر

Dr. Tamar H. Taddei is Professor of Medicine (Digestive Diseases) at Yale School of Medicine and Chief of Gastroenterology at VA Connecticut Healthcare System. She also serves as Vice Chief of Faculty Development in the Digestive Diseases section at Yale. Her work spans clinical care, research, and education with a focus on liver diseases and cancer. Dr. Taddei directs the Liver Cancer Program at VA Connecticut Healthcare System and founded a VA regional tumor board serving Connecticut, Massachusetts, Rhode Island, and Vermont. She is actively involved with the Yale Cancer Center and multiple research programs including Cancer Prevention and Control. Professor of Medicine (Digestive Diseases), Yale School of Medicine Chief, Digestive Diseases, VA Connecticut Healthcare System Vice Chief of Faculty Development (Digestive Diseases), Yale School of Medicine Co-Principal Investigator, Veterans Outcomes and Costs Associated with Liver disease (VOCAL) study group Co-Principal Investigator, Statins and Cirrhosis - Reducing Events of Decompensation (SACRED) clinical trial Co-Principal Investigator, PREventing Liver Cancer Mortality through Imaging with Ultrasound vs. MRI (PREMIUM) clinical trial Dr. Taddei's research focuses on outcomes and clinical trials in cirrhosis and liver cancer. She is particularly interested in developing systems for multidisciplinary care for liver cancer patients and improving early detection methods. Her work bridges clinical practice with research to enhance patient outcomes in hepatology and gastroenterology. Her recent publications demonstrate strong activity in liver cancer risk prediction, outcomes in cirrhosis, steatotic liver disease, and hepatocellular carcinoma. These works reflect her commitment to advancing the field through rigorous clinical research and data-driven approaches that address critical questions in liver disease management. Scientific Awards and Recognition Alvan R. Feinstein Award (2017) Digestive Diseases Fellowship Teaching Award (2011) Best Teacher – YNHH Hospitalist Service (2010) Samuel Kushlan Award for Clinical Excellence in Fellowship (2007) Dr. Taddei is deeply committed to education and mentoring, having received multiple teaching awards for her dedication to the education and career advancement of medical students, residents, and fellows. She directs liver cancer roundtable meetings at both Smilow Cancer Hospital at Yale New Haven and the VA Connecticut Healthcare System, fostering collaborative, team-based approaches to patient care that integrate expertise from multiple specialties.

• RNA Biology
• Computational Biology
• Hematologic Neoplasms
• +۵ مورد دیگر

Toma Tebaldi is an Assistant Professor Adjunct in the Medical Oncology and Hematology department at Yale School of Medicine and a member of the Yale Cancer Center. His interdisciplinary work bridges computational biology and cancer research, with a focus on RNA mechanisms in hematologic malignancies. Dr. Tebaldi maintains affiliations with multiple research programs including Genomics, Genetics, and Epigenetics, and Internal Medicine at Yale. Dr. Tebaldi's educational background includes a PhD in Information and Communication Technology from the University of Trento (2010), an MSc in Biotechnologies - Bioinformatics from University of Milano Bicocca (2006), and a BSc in Biotechnologies from the same institution (2003). His training includes postdoctoral fellowships at University of Trento, EMBO Short Fellowship at University of Edinburgh, and international internships at Harvard Medical School, University of Edinburgh, and University of Sheffield. His research focuses on RNA molecular mechanisms underlying disease dysregulation, combining experimental and computational approaches. Key areas include alternative splicing, non-coding RNA binding, mutant RNA binding proteins, RNA modifications (epitranscriptome), translation dynamics, and single-cell expression data. This work has significant implications for understanding and treating hematologic cancers. Dr. Tebaldi's publication record shows consistent output in high-impact journals from 2022-2025, with research spanning cancer biology, RNA mechanisms, and computational approaches. His work demonstrates increasing sophistication in integrating single-cell technologies with traditional molecular biology techniques to address complex questions in cancer biology. Italian National Scientific Qualification as Associate Professor in Applied Biology (2021) Italian National Scientific Qualification as Associate Professor in Molecular Biology (2020) Yale YCCEH Pilot and Feasibility Program Award (2018) RNA Society Travel Award: RNA2016, Kyoto (2016) EMBO Travel Grant Award: Protein synthesis and translational control (2015) Dr. Tebaldi serves as Associate Editor for Frontiers in Genetics - Computational Biology and as a reviewer for PRIN 2020 MIUR. His membership in the Yale Center for Biomedical Data Science and Yale Cancer Center provides access to extensive collaborative networks and resources. His research program benefits from interdisciplinary connections between computational biology, cancer genomics, and clinical hematology/oncology. Through his Italian Society of Yale Students and Affiliates board membership and Visiting Professor appointments at University of Trento, Dr. Tebaldi maintains strong international connections that enrich his research program and provide opportunities for student exchanges and collaborative projects across continents.

Nuttida Rungratsameetaweemanaمشاهده پروفایل

استادیار

• Neural computations
• Cognitive neuroscience
• Computational neuroscience
• +۶ مورد دیگر

Nuttida Rungratsameetaweemana is an Assistant Professor in the Department of Biomedical Engineering at Columbia University's Fu Foundation School of Engineering and Applied Science. She also serves as a Provost Research Fellow at Columbia University, demonstrating her significant research contributions early in her academic career. NuttidaLab, her research group, focuses on integrating computational and experimental approaches to investigate the neural computations underlying complex cognitive functions in both health and disease. The lab's research spans several key areas including learning mechanisms, decision-making processes, and social behavior, with particular emphasis on understanding how these cognitive functions become disrupted in neurological and neuropsychiatric disorders. The lab has developed several important computational neuroscience tools including NeuralDecoder for representational similarity analysis, state_space_analysis for modeling neural dynamics, MARLAX for multi-agent reinforcement learning, and dynamax for state space modeling. These tools reflect the lab's commitment to developing robust analytical frameworks that can be widely adopted by the neuroscience community. NuttidaLab maintains an active GitHub presence with multiple repositories that demonstrate the lab's focus on open science and reproducible research. The lab's work combines cutting-edge computational approaches with experimental neuroscience to develop a deeper understanding of brain function. The lab actively seeks talented students and researchers interested in interdisciplinary work at the intersection of engineering, neuroscience, and computational science. Professor Rungratsameetaweemana's research represents an important bridge between theoretical computational models and experimental neuroscience, with significant potential for advancing our understanding of both healthy brain function and neurological disorders.