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Radhika JainView profile

Associate Professor

• Open Source Software Development
• Platform Development
• Business Process Integration
• +4 more

Radhika Jain is an Associate Professor at the Paul H. Chook Department of Information Systems and Statistics within Baruch College's Zicklin School of Business (City University of New York). She holds a PhD in Computer Information Systems from Georgia State University, an MS in Computer Engineering from Stevens Institute of Technology, and a BS in Computer Engineering from Pune Institute of Computer Technology. Her research explores: Open Source Ecosystems : Platform development and governance in collaborative environments Global Sourcing : Offshore outsourcing strategies and vendor management Business Process Innovation : Integration methodologies and contextual adaptation Emerging Technologies : Mobile application evolution and AI-driven business transformation Publications demonstrate consistent focus on empirical investigations of technology management, with recent work examining skilled labor impacts (2024) and mobile app feature dynamics (2024). Earlier studies established frameworks for outsourcing communication (2011) and agile development (2006). Awards & Honors: Gender Equity Grant Writing Assistance (Hunter College, 2010) Doctoral Consortium Scholarships at ICEIS (2005) and AMCIS (2005) Academic Leadership: She supervises doctoral dissertations (BUS 90000) and secured multiple PSC-CUNY grants including studies on OSS platform development ($3,498, 2019-2022) and agile methodology transitions ($3,500, 2013-2014). Current courses include Data Visualization (CIS 4170/9655) and Programming (CIS 2300).

Aditya JainView profile

Associate Professor

• Operations Management
• Supply Chain Management
• Retail Operations
• +7 more

Aditya Jain serves as Associate Professor of Operations Management at the Narendra Paul Loomba Department of Management within Baruch College's Zicklin School of Business (City University of New York). His academic appointments include teaching graduate and undergraduate courses in Service Operations Management, Foundations of Predictive Analytics, and Managing Business Operations across multiple semesters through Spring 2025. His educational background includes: Ph.D. in Operations Management, University of Rochester, Simon Business School M.S. in Management Science, University of Rochester, Simon Business School B.S. in Chemical Engineering, Indian Institute of Technology Bombay Professor Jain's research centers on Operations Management with emphasis on stochastic modeling, healthcare operations, and retail supply chains. His work bridges theoretical operations models with empirical applications, particularly in marketplace competition and consumer behavior analysis. Key methodologies include econometric analysis, game-theoretic modeling, and quantitative optimization techniques applied across diverse sectors. His recent publications demonstrate evolving focus from foundational inventory models toward contemporary challenges in digital marketplaces and pandemic-era retail operations. The 15 most recent articles reveal strong concentration in retail marketplace dynamics (40%), healthcare operations (20%), and consumer behavior analytics (25%), with increasing empirical validation through real-world data. Notable recognition includes: Dick Wittink Award (Runner-up, 2021) from James M. Kilts Center for Marketing and UCLA Morrison Center for retail video analytics research Professor Jain has secured multiple PSC-CUNY grants totaling over $14,000 since 2016, including funded projects on pandemic grocery operations and retail marketplaces. His service includes editorial roles for Management Science , Operations Research , and Production and Operations Management Journal , alongside committee positions in Baruch's Management Department and Graduate Curriculum.

Shan LiView profile

Associate Professor

• Data Science
• Healthcare Operations
• Operations Management
• +4 more

Shan Li is an Associate Professor at the Zicklin School of Business , Baruch College, CUNY, focusing on Data Science , Healthcare Operations , and Behavioral Operations Management . She holds a PhD in Operations Research from UC Berkeley and a BS in Computer Science from Shanghai Jiaotong University. Education: PhD, University of California, Berkeley, Operations Research (2010) MS, University of California, Berkeley, Operations Research (2006) BS, Shanghai Jiaotong University, Computer Science (2004) Her research integrates Behavioral Economics into operational decision-making, addressing challenges in Inventory Sharing , Procurement Auctions , and Healthcare Scheduling . She has pioneered studies on Loss-Averse Bidders and Cognitive Biases in Newsvendor Decisions , revealing how psychological factors impact supply chain efficiency. Recent publications analyze Multidimensional Auction Design (2025), Time-Dependent Scheduling (2020-2020), and Behavioral Traps in Retail Inventory (2023-2018). Her work bridges Quantitative Modeling and Organizational Behavior . Scientific Awards: CFO Pinnacle Award (2013) INFORMS Doctoral Colloquium (2009) Marshall-Oliver-Rosenberger Fellowship (2008) She has secured multiple PSC-CUNY grants for projects on Behavioral Mechanisms in Procurement and Inventory Sharing . Active in academic service, she chairs sessions at INFORMS and POMS and serves on editorial boards.

• Machine Learning
• Artificial Intelligence
• Anomaly Detection
• +3 more

Alessio Mascolini serves as a Research Fellow at the Interuniversity Department of Territorial Sciences, Planning and Policies (DIST) and as an External Lecturer at the Department of Control and Computer Science (DAUIN) at Polytechnic University of Turin. His academic work bridges theoretical machine learning research with practical industrial applications, particularly in manufacturing and engineering contexts. His research interests focus on Machine Learning applications in data-limited scenarios , with specialization in anomaly detection systems , edge computing implementations , and generative modeling approaches . His work demonstrates strong connections between theoretical AI advances and real-world industrial challenges, particularly in semiconductor manufacturing and robotic production lines. Analysis of his recent publications reveals a clear trajectory toward developing resource-efficient AI systems for industrial environments, with increasing sophistication in combining neuro-symbolic approaches with diffusion models. His research consistently addresses the challenge of implementing robust machine learning solutions in resource-constrained edge computing environments. As an educator, Mascolini has served as Course Collaborator for multiple programs since 2020/21, demonstrating consistent engagement with student instruction across various engineering disciplines. His teaching portfolio shows strong alignment with his research interests, particularly in machine learning applications.

• Mathematical Modeling
• Production Planning and Control
• Production Systems
• +3 more

Erica Pastore is a Fixed-term Researcher in the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino , affiliated with the College of Management and Production Engineering . Her work spans mathematical modeling, production planning, and simulation optimization within industrial engineering contexts. Teaching roles: Course Lecturer (2024/25, Management and Production Engineering), Course Collaborator (2025/26, Management Engineering) Sciences: Production Systems , Manufacturing Technologies , Sustainable Operations Her research focuses on mathematical modeling for production planning and optimization , examining variability propagation in manufacturing systems, additive manufacturing time estimation , and circular economy strategies at scheduling levels. Publications address flow line optimization , parallel batching , and healthcare logistics through simulation and analytical modeling . Recent work trends include flow time minimization (2025), additive manufacturing scheduling (2024), idle time reduction (2023), and urban logistics (2022). She has collaborated on 15+ publications since 2012, working with colleagues like Arianna Alfieri , Claudio Castiglione , and Barbara Previtali across production optimization, healthcare systems, and logistics.

Joanna CieślaView profile

Associate Professor

• Biotechnology
• Biochemistry
• Molecular Biology
• +4 more

Joanna Cieśla is an Associate Professor at the Chair of Drug and Cosmetics Biotechnology , Faculty of Chemistry , Warsaw University of Technology . She has held this position since 2010 and previously served as Assistant Professor at the Nencki Institute of Experimental Biology (1983–2013). Her research focuses on enzyme regulation in cancer metabolism , thymidylate synthase mechanisms , and biotechnological applications in drug design. PhD in Biochemistry (Nencki Institute, 2006) Master’s in Biochemistry (Nencki Institute, 1991) Doctorate in Molecular Biology (University of Warsaw, 1983) Her work bridges biochemistry , molecular biology , and biotechnology , with a focus on protein phosphorylation , enzyme inhibition , and structure-based drug design . She has published extensively on thymidylate synthase and CK2 kinase interactions in cancer cells, as well as plant-derived anticancer agents and coffee waste valorization . Over 15 recent articles highlight her expertise in enzyme inhibition (2025–2013), protein phosphorylation mechanisms, and biochemical applications in oncology and microbial fermentation. Her scientific collaborations span institutions in Poland, the USA, and China, with key contributions to thymidylate cycle regulation and biological waste processing .

• Chemistry Education
• Food Safety Systems
• Quality Management
• +3 more

АЛБЕНА ЦОНЕВА ЦОНЕВА serves as a Lecturer at Technical University of Gabrovo, specializing in chemistry education and practical laboratory instruction. Her academic work spans textbook development, international research projects, and specialized publications in food safety systems and quality management. Her research interests center on Chemistry Education methodology , with substantial contributions to laboratory exercise design and curriculum development. Additional expertise includes Food Safety Systems implementation in vinegar production and Quality Management frameworks like ISO 9001 certification and 5S methodology. Her work bridges theoretical chemistry with industrial applications, particularly in food processing safety protocols. The publication analysis reveals consistent focus on educational materials development (14 of 17 publications), with recent expansion into food safety systems (2012-2013). Her chemistry education publications demonstrate evolving complexity from basic test collections (2006) to comprehensive lifelong learning frameworks (2010). The industrial applications work shows practical implementation of quality management systems in Bulgarian manufacturing contexts. She participated as a researcher in the international Leonardo da Vinci program project "Chemistry all around us" (2010), demonstrating engagement with European educational initiatives. Her professional activities include development of laboratory documentation systems, educational testing methodologies, and quality assurance protocols for food production. The work spans both academic instruction tools and industrial application guides, reflecting integration of educational theory with practical industry standards.

David J. ReibsteinView profile

Professor

• Brand Equity
• Marketing Metrics
• Nation Branding
• +5 more

David J. Reibstein serves as the William S. Woodside Professor of Marketing at the University of Pennsylvania's Wharton School, where he also previously held the position of Vice Dean. His academic career spans decades with appointments at Harvard and INSEAD, establishing him as a global authority in marketing strategy and brand management. Professor Reibstein earned his PhD from Purdue University and holds BS/BA degrees from the University of Kansas. His scholarly journey includes extensive consulting with major corporations including Google, Verizon, Shell Oil, Intel, Genentech, and Novartis, along with notable expert testimony in high-profile cases like Apple vs Samsung. His research focuses on brand equity measurement, nation branding frameworks, and the critical linkage between marketing metrics and financial outcomes. Reibstein pioneered the Wharton Consumer Cryptocurrency Confidence Index (c3i) and developed influential frameworks for corporate sociopolitical activism. His work examines how nations position themselves globally through initiatives like the U.S. News Best Countries rankings. Analysis of his recent publications reveals an evolving research trajectory toward integrating emerging technologies with traditional marketing frameworks, particularly examining generative AI's role in business research and the metaverse's impact on brand experiences. His scholarship increasingly addresses societal challenges through corporate responsibility lenses while maintaining rigorous financial performance connections. Global Retail Brand Research Fellow (2025) Lifetime Achievement Award, Woxsen University (2025) Marshall Blume Prizes in Financial Research (2017) Over 30 teaching awards including multiple Wharton Teaching Excellence Awards John S. Day Distinguished Alumni Academic Service Award Named 'Most Favorite Business School Professor' by Fortune magazine Professor Reibstein actively advises major organizations as chairman of Responsible Research in Business & Management (RRBM), former chairman of the American Marketing Association, and executive director of the Marketing Science Institute. He serves on the advisory board of the Center of Environmental Intelligence and consults extensively with global corporations. His executive education programs at Wharton focus on translating complex marketing analytics into actionable business strategies, with particular emphasis on crisis management frameworks developed during the pandemic. Through initiatives like the 'Measured Thoughts' CEO interview series and 'Managing Through a Pandemic' video collection, Reibstein bridges academic research with practical business leadership challenges, maintaining direct engagement with C-suite executives across multiple industries.

• Chemical Engineering
• Nanomaterials
• Carbon Nanotubes
• +8 more

Dr. Marta Mazurkiewicz-Pawlicka serves as an Assistant Professor at the Division of Industrial Process Intensification, Faculty of Chemical and Process Engineering, Warsaw University of Technology. With 90 publications and 3 patents, her research focuses on nanomaterials for energy applications and environmental engineering. PhD (2015), MSc (2009) ORCID: 0000-0002-2520-7476 Scopus h-index: 20 Research Interests: Electrocatalytic materials for fuel cells and hydrogen production Graphene and carbon nanotube composites Nanoparticle synthesis and characterization (XRD/XPS) Supercritical CO2 processing techniques Nanotoxicology and biomedical applications Environmental emission reduction technologies Publication Trends: Recent work emphasizes molybdenum disulfide hybrids for energy systems (2023-2025), TiO2-supported catalysts (2024), and graphene-based materials for photocatalysis and biomedical uses. Earlier studies focus on carbon nanotube functionalization (2012-2015) and fuel cell catalyst optimization. Notable Contributions: Developed supercapacitor materials using MoS2/carbon nanotube composites Innovated engine oil nanoadditives to reduce particulate emissions Studied diamond nanoparticle cytotoxicity across multiple cancer cell lines Investigated Pd catalyst stability in direct formic acid fuel cells Created graphene oxide composites for metal ion removal from water With 21 promoted theses and 2 funded projects, Dr. Mazurkiewicz-Pawlicka has authored 90 publications. Her work has accumulated 3,830 ministry score points and 304.08 CiteScore metrics.

Ioana PisicaView profile

Senior Lecturer

• Smart Grids
• Power Systems Analysis and Control
• Machine Learning Applications in Power Systems
• +4 more

Dr Ioana Pisica, Reader (Senior Lecturer) in Power Systems at Brunel University London's Department of Electronic and Electrical Engineering, specializes in smart grids, machine learning applications, and optimization techniques for power systems with distributed generation. Her research bridges ICT infrastructure development, flexible demand management, and renewable energy integration, with leadership roles in the Sustainable Electrical Power MSc program and EPSRC-funded projects. Education : BSc in Information Systems for Power Engineering (NTU Bucharest), MSc in Information Systems (Academy of Economic Studies Bucharest), PhD in Machine Learning for Power Systems (NTU Bucharest) Research Themes : Smart grid operation, AI-driven voltage control, dynamic electricity tariffs, and EV-grid interaction. Articles highlight deep learning for fire detection, multi-objective hydrogen-electricity optimization, and UAV-based infrastructure inspection. Grants : InnovateUK (2019-2021), National Grid ESOC (2018-2020), British Council (2017-2018, 2021-2023), EPSRC (2022) Academic Leadership : Director of Teaching & Learning (PGT) for Electronic and Electrical Engineering, with contributions to Thames Water energy optimization and Horizon 2020 TDX-ASSIST project. Supervises PhD research on AI applications in power systems.

Tibor KovácsView profile

Associate Professor

• Computer Science
• Automation and Robotics
• Industrial Engineering
• +3 more

Tibor Kovács is an Associate Professor at the Budapest University of Technology and Economics, affiliated with the Department of Automation and Applied Informatics. He has contributed extensively to applied informatics, focusing on graph database systems, 3D scanning technologies, industrial process optimization, and noise-resistant algorithms. His work bridges theoretical research with practical implementations in manufacturing, sensor design, and data management. Research Interests: Graph database benchmarking and optimization 3D geometry scanning and curvature adaptation Industrial production network performance analysis Energy efficiency in manufacturing systems Robust line/edge detection algorithms XML tree search methodologies Publication Trends: His recent work emphasizes scalable data systems (2019) and geometric sensor optimization (2018), while earlier studies focus on industrial energy efficiency (2016), technical advisory networks (2010), and foundational computer vision algorithms (2004–1994).

Jin-Bao ZhaoView profile

Professor

• Chemical Energy Storage
• Lithium-ion Battery Technology
• Fuel Cell Materials
• +2 more

Jin-Bao Zhao is a Professor at the College of Chemistry and Chemical Engineering , Xiamen University, leading research in chemical energy storage systems and related materials since 2011. His work focuses on lithium-ion batteries with high capacity density and fuel cell technologies. Education: Bachelor's (1984) and Master's (1987) in Electrochemical and Polymer Engineering from Harbin Institute of Technology PhD (1996) in Polymer Chemistry, Kyoto University Research Interests include: Advanced lithium-ion battery materials Solid-state electrolyte development Thermal stability enhancement in separators Electrocatalyst design for oxygen reduction Functional membrane technology Energy storage system safety Publication Trends show a focus on separator engineering, nanocomposite electrodes, and solvation structure analysis, with collaborations across China and Japan. His Scientific Awards include: 20th China Patent Excellence Award (2018) Xiamen Science and Technology Major Contribution Award (2018) Fujian Province Science and Technology Progress Second Prize (2017) China Aviation Industry Corporation Science and Technology Award (2014) Students have achieved national scholarships and graduated with impactful research. The Chemical Power Sources and Energy Storage Materials Laboratory under his leadership has developed pilot production lines and received multiple industry recognitions.

• Infrared Thermography
• Non-Destructive Testing
• Image Processing
• +4 more

Xavier Maldague is a Professor in the Department of Electrical and Computer Engineering at Université Laval's Faculty of Science and Engineering, with over 35 years of research in infrared thermography and non-destructive testing methodologies. His work spans theoretical algorithm development to practical industrial applications across aerospace, cultural heritage, medical diagnostics, and infrastructure inspection domains. Dr. Maldague's research interests focus on advanced thermal imaging techniques, sensor fusion systems, and machine learning applications for defect detection and material characterization. His work has evolved from fundamental thermographic algorithms in the 1990s to current research integrating deep learning, drone-based platforms, and multi-sensor fusion systems for industrial inspection. Key areas include pulsed thermography, line-scan techniques, coplanar capacitive sensing, and hyperspectral infrared imaging. Analysis of his 15 most recent publications reveals a strong emphasis on deep learning integration with traditional thermographic methods, particularly for defect detection in composite materials, cultural heritage objects, and infrastructure components. His recent work shows increasing focus on multi-modal data fusion, drone-enabled inspection platforms, and synthetic data generation for training machine learning models. The research spans both theoretical algorithm development and practical implementation across diverse application domains. Dr. Maldague has maintained a highly productive research trajectory with consistent publication output, particularly in high-impact journals such as Sensors, IEEE Access, and Remote Sensing. His work demonstrates strong international collaboration, with numerous co-authors from European institutions alongside his primary Canadian research team. His research group appears to focus on developing practical inspection systems that bridge theoretical image processing with real-world industrial applications, with recent emphasis on automation, deep learning integration, and multi-sensor approaches to enhance detection capabilities and reliability in non-destructive testing scenarios.

Diego Borro YagüezView profile

Professor

• Computer Graphics
• Virtual Reality
• Augmented Reality
• +6 more

Diego Borro is a Full Professor (Catedrático) in Computer Science and Artificial Intelligence at TECNUN, Technological Campus of the University of Navarra , where he has been part of the faculty since 2004. He is a leading researcher at CEIT since 2003, focusing on Robotics, Virtual/Augmented Reality, Computer Vision, and Artificial Intelligence. His academic credentials include a PhD in Computer Science (2003) and an MS in Computer Science (2000) from the University of Navarra and University of Basque Country respectively. His research spans from 3D tracking and haptics to industry 4.0 applications and medical robotics, with over 34 journal papers and 65 conference articles. He has supervised 14 doctoral theses and participated in 55+ research projects. His leadership roles include heading CEIT's Simulation Unit (2012-2016) and Vision and Robotics (V&R) research line (2016-2022), currently serving as main researcher at Intelligent Systems for Industry 4.0 group (SS4I4). Accredited as Full Professor (Catedrático) by ANECA (3 sexenios) Member of IEEE, ACM, and Eurographics societies Key projects: STEPbySTEP exoskeleton benchmark, WARM AR maintenance systems, and inner ear drug delivery research

• Virology
• Herpes Simplex Virus (HSV-1 and HSV-2)
• Human Herpesvirus 6 (HHV-6)
• +7 more

Minas Arsenakis is a Professor at the Department of Biology, Aristotle University of Thessaloniki (AUTH), Greece. With a career spanning over four decades, he has made significant contributions to the fields of virology, molecular biology, and infectious diseases. His research has focused extensively on herpesviruses, particularly herpes simplex virus types 1 and 2 (HSV-1 and HSV-2), human herpesvirus 6 (HHV-6), and Epstein-Barr virus (EBV). He has also explored the development of viral vectors for gene therapy, antiviral compounds, and microbial resistance mechanisms. His work has been published in numerous high-impact journals, covering a wide range of topics from viral glycoprotein function and gene regulation to antimicrobial resistance and cyanobacterial bioactivity. Notable areas of investigation include: Regulation of HSV gene expression by the α4 regulatory protein. Construction of recombinant HSV vectors for foreign gene expression. Antiviral activity of natural compounds like isoborneol and essential oils. Prevalence of resistance genes in oral and environmental microbiota. Development of diagnostic assays for viral infections and autoimmune diseases. Studies on cyanobacteria and their bioactive metabolites. Professor Arsenakis has collaborated extensively with national and international research groups, contributing to the advancement of virology and molecular medicine. His research has implications for vaccine development, antiviral therapy, and public health surveillance.