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Johannes SoedingView profile

Researcher

• Computational Biology
• Bioinformatics
• Protein Structure Prediction
• +9 more

Johannes Soeding is a Research Group Leader in the Computational Biology department at the Max Planck Institute for Multidisciplinary Sciences in Göttingen, Germany. His work bridges physics, bioinformatics, and molecular biology, focusing on computational methods for biological data analysis. His research interests include computational biology, protein structure and function prediction, metagenomics, transcriptional regulation, and statistical genomics. He develops widely used software tools such as HH-suite, HHpred, MMseqs2, and Foldseek for protein sequence and structure analysis. The recent publications demonstrate a strong focus on high-throughput biological data, particularly in protein structure search (e.g., Foldseek), metagenomic gene discovery (e.g., MetaEuk), and regulatory genomics. His work combines algorithm development with deep biological insights, often published in top-tier journals like Nature Biotechnology , Science , and Nature Methods . He has been involved in significant methodological advances in sequence clustering, contact prediction, and eQTL analysis, showing a consistent trend toward scalable, data-driven approaches in genomics and proteomics. Soeding has contributed to major projects in gene regulatory networks and RNA biology, often in collaboration with experimental groups. His leadership in developing open, efficient bioinformatics tools has had a broad impact on the scientific community. He is affiliated with several graduate programs including IMPRS Physics of Biological and Complex Systems, Biomolecules: Structure - Function - Dynamics, and Genome Science, indicating active participation in training the next generation of scientists.

Krista A. EhingerView profile

Associate Professor

• Computer Vision
• Artificial Intelligence
• Human Vision
• +7 more

Krista A. Ehinger is an Associate Professor and co-lead of the AI group at the University of Melbourne's School of Computing and Information Systems. She holds a PhD from MIT and has held postdoctoral positions at York University and Harvard Medical School. Her research focuses on the intersection of human and computer vision, including scene recognition, visual search, and depth perception. Methodologically, she combines Bayesian models, deep learning, and behavioral experiments like eye tracking. Current projects explore AI applications in space systems (e.g., SpIRIT satellite) and ethical implications of workplace surveillance via computer vision. Recent work emphasizes amodal completion (e.g., reconstructing occluded objects) and AI reasoning systems. She collaborates on medical imaging (TCAM-Diff model), autonomous driving (truck speed detection), and 3D reconstruction. Her lab actively engages in open-source tools like the SUN Database for scene understanding. Professional activities include AI ethics discussions and academic service. She advises students on Masters/PhD projects and contributes to conferences like CVPR and NeurIPS.

• Trustworthy AI
• Software Testing & Verification
• Requirements Engineering
• +5 more

Prof. Lionel C. Briand is a leading academic in software engineering and trustworthy AI, holding appointments at the University of Ottawa (EECS Department, Nanda Laboratory) and the University of Limerick (Lero - National Software Research Centre). He serves as Director of Lero and Scientific Director of the SnT software verification lab in Luxembourg. His research focuses on software testing, model-driven engineering, AI-driven quality assurance, and regulatory compliance. He has held the Canada Research Chair (Tier 1) since 2003 and led major institutions like Simula Research Laboratory (Norway) and Fraunhofer Institute (Germany). Education & Career: Full Professor at Carleton University (2008–2012) Head of Software Quality Engineering at Fraunhofer IESE (2000–2008) Research Scientist at NASA Software Engineering Lab (1990s) Research Interests: His work spans secure AI systems, automated legal compliance (e.g., GDPR), metamorphic testing, search-based software engineering, and safety-critical systems. He emphasizes practical applications, collaborating with industry partners globally. Awards & Recognition: IEEE Fellow (2010), ACM Fellow (2020) Harlan Mills Award (2012), ERC Advanced Grant (2016) Fellowships from Royal Society of Canada (2023) and Academia Europaea (2025) Grants & Labs: PEARL grant from Luxembourg FNR for SnT lab ERC Advanced Grant for software testing research Leadership roles in Lero and Nanda Lab Publications: Over 500+ papers on testing methodologies, AI ethics, and regulatory compliance. Notable tools include CompAI (GDPR compliance) and Teasma (DNN test adequacy).

Liji ShenView profile

Professor

• Operations Management
• Supply Chain Management
• Scheduling Optimization
• +7 more

Liji Shen is Professor of Operations Management and Chairholder at WHU – Otto Beisheim School of Management, Campus Vallendar, Germany. She is affiliated with the Supply Chain Management Group and leads research in scheduling, optimization, and sustainable manufacturing. Her academic journey includes a Ph.D. and Habilitation from Technische Universität Dresden, and she has held visiting scholar positions at institutions including École des Mines de Saint-Étienne and Huazhong University of Science and Technology. Ph.D. (Dr.rer.pol.), summa cum laude, Technische Universität Dresden (2009) Habilitation, Technische Universität Dresden (2015) Master of Business Administration (Dipl.-Kffr.), Technische Universität Dresden (2006) Liji Shen's research focuses on Operations Management , particularly scheduling optimization in manufacturing systems. Her work spans flexible job shops , parallel machine scheduling , energy-efficient production , and sequence-dependent setup times . She applies advanced techniques such as evolutionary algorithms , hybrid metaheuristics , and mathematical programming to solve complex industrial problems. Her recent publications emphasize sustainability through energy-aware scheduling and time-of-use pricing models. The 15 most recent publications highlight a consistent research trajectory in production scheduling , with increasing emphasis on energy efficiency , distributed manufacturing , and real-world constraints like eligibility and delivery times. Her work frequently appears in top journals such as European Journal of Operational Research , IEEE Transactions on Evolutionary Computation , and Computers & Operations Research , often in collaboration with leading researchers like Dauzère-Pérès, Mönch, and Buscher. Scientific Awards: European Journal of Operational Research, Best Paper Award (2021) DFG and TU Dresden, 'Support the Best' Prize for Outstanding Researchers (2013) Dr. Feldbausch-Prize for Best Dissertation, TU Dresden (2010) Scholarship for Young Researchers in Saxony (2006–2009) DAAD Prize for Best Foreign Students (2007) Best Master’s Thesis, German Operations Research Society (2007) Liji Shen has been an active advisor and researcher, leading projects in operations research and industrial optimization. Her editorial role on Operations Research Perspectives underscores her standing in the academic community. She has directed research labs and collaborated internationally, contributing to both theoretical advancements and practical applications in manufacturing and logistics. No specific grants are mentioned, but her sustained publication record and leadership roles indicate strong research support. She leads the Operations Management research group at WHU, focusing on algorithmic solutions for complex scheduling problems. Her team investigates energy-aware production, hybrid flow shops, and distributed systems, aiming to bridge the gap between theoretical models and industrial implementation. The lab collaborates with researchers across Europe and China, fostering a global research network in operations research and supply chain management.

Oleg LashininView profile

Researcher

• Recommender Systems
• Machine Learning
• Artificial Intelligence
• +3 more

Oleg Lashinin is an active researcher in the field of Recommender Systems , with a focus on Machine Learning , Temporal Modeling , and User Behavior Analysis . He has contributed to 15 recent publications spanning 2021–2025, including conference papers at ECIR, SIGIR, RecSys, and workshops like KaRS@RecSys and ORSUM@RecSys. His work explores advanced techniques such as Self-Attention Models , Time-Aware Item Weighting , and Cost-Constrained Recommendations . Key research trends in his publications include Deep Learning for sequential recommendation tasks, Crowdsourcing for explanation evaluation, and Temporal Dynamics in user behavior. Notable projects include the GPT3RecBot Telegram chatbot and the RecBaselines2023 dataset for benchmarking recommender systems.

• Database Systems
• Query Optimization
• Index Tuning
• +7 more

Surajit Chaudhuri is a Researcher at Microsoft , with a career spanning decades in database systems and data management . He has received the prestigious SIGMOD Edgar F. Codd Innovations Award (2011) for his contributions to query optimization , index tuning , and data lakes . Research Interests : His work focuses on database tuning , approximate query processing , fuzzy similarity joins , automated data transformations , and machine learning integration for scalable data systems. Recent Publications : In 2025, his research includes Auto-Test for unsupervised error detection in tables, Esc for budget-aware index tuning, and MMTU for multi-task table understanding benchmarks. Earlier works in 2024–2023 address spreadsheet formula recommendation , low-overhead index filtering , and time-series pattern recognition . Scientific Impact : He has co-authored influential papers in SIGMOD , VLDB , and IEEE Transactions , shaping practices in cloud databases , query optimization , and self-service BI . His collaborations span institutions like Microsoft, MIT, and ETH Zurich.

• Database Systems
• Big Data Analytics
• Cloud Database Systems
• +5 more

Michael J. Franklin is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley's College of Engineering. He has a prolific publication record spanning over three decades with more than 300 publications in top-tier database and systems conferences and journals, demonstrating his continued active research and leadership in the field. Franklin's research spans multiple areas within data management, with a recent focus on time-series analysis, AI-integrated database systems, cloud-native databases, and data quality. His work has evolved from traditional database systems to address modern challenges in big data, machine learning integration, and distributed systems. He has made significant contributions to data cleaning, crowdsourced data management, and stream processing systems. Analysis of his recent publications (2022-2025) reveals a strong trend toward integrating AI/ML capabilities with database systems, particularly in time-series anomaly detection, LLM applications for data management, and resource-adaptive query processing for cloud environments. His work increasingly focuses on practical systems that address real-world data challenges, often involving collaborations with industry partners and other leading academic researchers. Throughout his career, Franklin has mentored numerous PhD students who have become prominent researchers in their own right, including Sanjay Krishnan, Aaron Elmore, and Jiannan Wang. His collaborative research has frequently involved significant funding from NSF and industry partnerships, enabling large-scale systems research with real-world impact. Franklin leads research efforts that bridge theoretical database principles with practical system implementations. His work on projects like Data Station demonstrates his commitment to building trustworthy infrastructure for data sharing and analysis, addressing critical challenges in data privacy, security, and usability in collaborative environments.

• Multimedia Modeling
• Machine Learning
• Computer Vision
• +7 more

Dr. Stevan Rudinac is a Researcher at the University of Amsterdam's Faculty of Economics and Business , Section Business Analytics . His work focuses on interactive learning systems and multimodal data analysis, particularly in urban contexts and multimedia modeling. Education: PhD in Multimedia and Information Retrieval from Delft University of Technology (2013). Research Interests: Stevan specializes in multimedia modeling , hypergraph learning , and interactive video search . He develops frameworks for scalable analysis of social networks, urban imagery, and large multimodal datasets, bridging machine learning with practical applications in city planning and financial social media. Recent Trends: His 2024-2025 publications highlight large language model optimization , diffusion model evaluation , and dynamic graph embedding for meme stocks. Collaborative projects include the CASTLE 2024 dataset and Exquisitor , a system for 100 million image exploration. Labs & Teams: He contributes to the Business Analytics group at UvA, collaborating with Prof. Marcel Worring and Dr. Björn Þór Jónsson. He co-organized the UrbanMM'21 workshop and participates in ACM Multimedia and MMM conferences.

Shruti DevganView profile

Assistant Professor

• Narratives
• Memory Studies
• Media and Technology
• +12 more

Shruti Devgan is an Assistant Professor in the Department of Sociology at Bowdoin College, where she teaches and conducts research on narratives, memory, media, emotions, and transnational flows, with a focus on South Asia and the Sikh diaspora. Her work explores how digital technologies mediate trauma and identity across generations, particularly in relation to the 1984 anti-Sikh violence. Her educational background includes a PhD and MA in Sociology from Rutgers University, an MPhil and MA from Jawaharlal Nehru University, and a BA from Lady Shriram College, University of Delhi. This strong foundation supports her interdisciplinary research at the intersection of sociology, digital media, and postcolonial studies. Dr. Devgan’s research centers on how memory is formed, transmitted, and transformed in digital and diasporic contexts. She investigates the role of digital platforms in shaping counter-narratives of state violence, particularly through the lens of Sikh diasporic communities in North America. Her work emphasizes the emotional and embodied dimensions of identity, trauma, and justice. The trends in her publications reveal a consistent engagement with digital memory, intergenerational trauma, transnational activism, and the politics of representation. Her work spans academic journals, edited volumes, and public intellectual platforms, demonstrating a commitment to both scholarly and public discourse. Digital Crevices: Sikh Diasporic and Digital Memories of the 1984 Violence (2025) The Remains of the Disappeared: Digital Melancholia and Ensaaf (Justice) (2023) ‘Give in, cut your Hair…or it makes you a very strong person’: Diasporic Sikhs, Transnational Racialization and Embodied Identity (2022) Making the Disappeared Appear: Ensaaf’s Archive of Loss and Remains (2020) A Haunted Generation Remembers (2018) While no formal scientific awards are listed, her contributions to memory studies and public scholarship are significant. She has not disclosed specific grants or advising roles, but her publications suggest active mentorship and research leadership. She is engaged in building knowledge through collaborative academic networks and public platforms, contributing to conversations on justice, trauma, and digital culture. Her ongoing book project further solidifies her role as a leading scholar in diasporic memory studies.

Tassilo PellegriniView profile

Professor

• Semantic Web
• Linked Data
• Digital Business
• +4 more

FH-Prof. Mag. Dr. Tassilo Pellegrini is a Professor at the University of Applied Sciences St. Pölten , leading the Institute for Innovation Systems within the Department of Digital Business and Innovation . His work bridges semantic technologies with digital business strategies. Education : Business Economics, Communication Studies, Political Science Research Focus : Semantic Web, Linked Data, Digital Media Economics, Network Neutrality, Data Licensing His publications highlight trends in Semantic Metadata for news production, Linked Data Integration , and Cloud-based Business Models under network neutrality constraints. Recent work explores thesaurus-driven knowledge organization and the economic implications of Big Data. Scientific Awards : Best Paper Award at I-Semantics 2012 Key Projects : ECO-TCO (Digital Data for Sustainability), Corporate Semantic Web initiatives Contact: tassilo.pellegrini@fhstp.ac.at

David WeissView profile

Senior Lecturer

• Developmental Psychology
• Lifespan Psychology
• Age Stereotypes
• +6 more

David Weiss is a Senior Lecturer in Developmental Psychology at the Martin Luther University Halle-Wittenberg, Germany. He leads the Developmental Psychology Section since November 2021 and has held prestigious roles including a Heisenberg Fellowship at the University of Leipzig (2018–2021) and Assistant Professor at Columbia University (2014–2018). Doctorate in Psychology (summa cum laude), Friedrich-Alexander University (2009) Habilitation, Venia legendi, Martin Luther University (2023) His research focuses on developmental lifespan psychology, examining how aging-related changes, negative age stereotypes, and social status dynamics impact physiological and psychological well-being. He employs experimental, longitudinal, and cross-cultural methods to study self-regulatory processes and motivational factors across adulthood. Recent publications analyze subjective aging, social status mobility, and essentialist beliefs about aging. His work appears in top journals like Psychology and Aging , Developmental Psychology , and Social Psychological and Personality Science . Awards include the Karl-Giehrl Award for Best PhD Thesis, Vontobel Award for Age Research, Calderone Award for Junior Faculty Excellence, and the DFG's Heisenberg Fellowship. His research has been cited in media outlets such as The New York Times and PBS Next Avenue . Current projects investigate social-cognitive mechanisms of aging, cross-cultural aging perceptions, and the interplay between social status and well-being. He collaborates with institutions in Switzerland, the USA, and China, and mentors students in experimental psychology and lifespan research.

Stephen AdamoView profile

Assistant Professor

• Visual Perception
• Attention
• Medical Image Perception
• +3 more

Stephen Adamo is an Assistant Professor in the Department of Psychology at the University of Arizona and directs the Attention Detection And Medical Observation (ADAMO) Lab. He holds a joint appointment in Radiology and Imaging Sciences and is a member of the UA Cancer Center. Education: B.S. in Psychology from the University of Arizona, M.A./Ph.D. in Psychology and Neuroscience from Duke University. His research focuses on visual perception, attention, and medical image perception, utilizing behavioral studies, eye-tracking, and EEG to explore topics like satisfaction of search in virtual mammograms, the impact of AI on diagnostic imaging, and differences between 2D and 3D visual search. He investigates attentional limitations such as "subsequent search misses" and "self-induced attentional blink" in radiology and cognitive science contexts. His recent publications examine the intersection of AI, 3D imaging, and cognitive errors in diagnostic workflows, emphasizing human-AI collaboration in visual search tasks. Scientific Awards: NIH National Cancer Institute Grant 5K99CA267163-02. He collaborates with radiologists and cognitive scientists, integrating interdisciplinary methods to improve medical diagnostics through human factors research.

Rameshwar PratapView profile

Associate Professor

• Algorithms in Machine Learning
• Theoretical Computer Science
• Sketching and Dimensionality Reduction
• +5 more

Rameshwar Pratap is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IIT Hyderabad). Previously, he served as an Assistant Professor at the School of Computing and Electrical Engineering, IIT Mandi for three years. Education: Ph.D. in Theoretical Computer Science, Chennai Mathematical Institute Research Interests: His research lies at the intersection of theory and practice, focusing on extremely simple yet practical approximation algorithms with provable guarantees . Key themes include: Sketching and dimensionality reduction algorithms for tensors and similarity measures Improving speed, scalability, and accuracy of existing sketching methods Applications in machine learning: node embedding in large-scale networks, itemset mining, model compression He extensively employs techniques from matrix and tensor algebra, sampling, random projection, and randomized hashing . Publications Overview: Across 2021–2025 his work has appeared in top venues such as IEEE Globecom, Theoretical Computer Science, Acta Informatica, Information Processing Letters, Algorithmica, UAI, ICALP, Machine Learning, TKDE, and ACML. Recurring themes are randomized sketching, locality-sensitive hashing, compressed matrix multiplication, variance reduction, and subspace approximation , demonstrating both theoretical depth and practical impact. Awards & Honors: Early Career Research Grant (PM-ECRG) 2025, Anusandhan National Research Foundation (ANRF) Best Paper Award, COCOON 2020 Students & Funding: First Ph.D. student: Bhisham Dev Verma (co-advised with Prof. Manoj Thakur) graduated June 2025 MS by Research student: Punit Pankaj Dubey graduated October 2022 Currently hiring 1 Junior Research Fellow for the PM-ECRG project “Improving Similarity Search in Practice” Labs & Teams: Works within the Algorithms & Theory group at IIT Hyderabad, collaborating with national and international researchers. Erdös number is 3.

Francesca PianosiView profile

Associate Professor

• Water Resource Management
• Hydrology
• Environmental Modelling
• +5 more

Dr Francesca Pianosi is an Associate Professor in Water & Environmental Engineering at the University of Bristol 's School of Civil, Aerospace and Design Engineering. She contributes to the Cabot Institute for the Environment and leads research on data analysis, mathematical modelling, and uncertainty quantification for hydrology and water engineering. Specialises in simulation and optimisation methods for water resource management Focuses on uncertainty propagation in natural hazard models Developed the open-source SAFE Toolbox for sensitivity analysis Research Trends Her recent publications (2023-2025) demonstrate expertise in: Groundwater flow and recharge in data-scarce regions Digital Twin applications for watershed management Climate change impact on landslides and droughts Multi-objective optimisation for reservoir operations Integration of machine learning with hydrological models Scientific Awards Arne Richter Award for Outstanding Young Scientists (2015) Best Research Oriented Paper - Journal of Water Resources Planning and Management (2024) Early Career Research Excellence (ECRE) award (2014) Francesca leads the Water Management and Adaptation based on Watershed Digital Twins project (2024-2027) and contributes to the USARIS project on uncertainty quantification for infrastructure systems (2023-2025).

Alex KreitView profile

Associate Professor

• Drug Law
• Cannabis Policy
• Criminal Justice Reform
• +3 more

Professor Alex Kreit is an Associate Professor of Law and Director of the Center on Addiction Law & Policy at Northern Kentucky University's Salmon P. Chase College of Law. He is a leading expert in illegal drug and cannabis law , with a focus on federal-state conflicts, criminal justice reform, and public health approaches to addiction policy. Kreit has authored multiple casebooks and over twenty law review articles, frequently appearing in media outlets like The New York Times and WIRED as a policy commentator. Education : Juris Doctor from University of Pennsylvania, Bachelor of Arts from Hampshire College His research spans drug law , cannabis policy , and criminal justice reform , with particular emphasis on safe injection sites , drug-induced homicide statutes , and pretextual stops in marijuana enforcement. Kreit's work systematically analyzes the legal tensions between state-level legalization efforts and federal prohibition frameworks. As a National Law Journal Trailblazer in Cannabis Law (2019) , Kreit has received grants from the Hayek Fund and Institute for Humane Studies. He serves on Kentucky Governor Andy Beshear's Medical Cannabis Advisory Committee and previously chaired San Diego's Medical Marijuana Task Force . Scientific Awards : National Law Journal Trailblazer in Cannabis Law (2019) Hayek Fund for Scholars Grant (2019) Institute for Humane Studies Faculty Partnership Grant (2015) San Diego Daily Transcript Top Attorneys in Academics (multiple years) San Diego News Network 35 Under 35 Community Leader (2010) Kreit maintains active practice as a court-appointed attorney with Appellate Defenders Inc. in California and has taught as visiting faculty at Boston College and Ohio State University. He has presented research at over 40 academic conferences and symposia globally, including in China, Canada, and the UK.