Find Academic Supervisors

Tatyana PestovaView profile

Assistant Professor

• Translation initiation in eukaryotes
• Ribosomal scanning
• Initiation codon selection
• +3 more

Tatyana Pestova is an Assistant Professor in the Department of Cell Biology at the State University of New York Downstate Medical Center. Her research focuses on the molecular mechanisms of eukaryotic translation initiation, particularly the roles of eukaryotic initiation factors (eIFs) in ribosomal scanning, initiation codon selection, and subunit joining. PhD in Biochemistry (1992), Moscow State University Doctor of Sciences (D.Sc.) in Molecular Biology (2002), Moscow State University Her work has elucidated the functions of key factors like eIF1, eIF1A, and eIF5B in ensuring translation fidelity. She investigates how viral internal ribosomal entry sites (IRES) co-opt host translation machinery, with implications for understanding protein synthesis regulation and viral RNA strategies. Recent publications highlight her expertise in ribosome-viral RNA interactions, DHX29 helicase activity, and quality control mechanisms during translation. Collaborators include researchers from Harvard Medical School, NIH, EMBL, and international institutions. Lab personnel: Ivan B. Lomakin (Research Scientist), Anett Unbehaun (MD, PhD), and Irina Lomakina (Research Technician).

• Information Theory
• Machine Learning
• Fairness in AI
• +6 more

Changho Suh is a Professor in the Department of Electrical Engineering at Korea Advanced Institute of Science and Technology (KAIST), College of Engineering. His research spans information theory, machine learning, and data science with significant contributions to matrix completion, fairness in AI, and network communications. Dr. Suh's research interests focus on the theoretical foundations of information processing and machine learning. He has pioneered work in matrix completion with graph side information, developing efficient algorithms that leverage hierarchical structures and similarity graphs. His recent work emphasizes fairness in machine learning systems, addressing correlation shifts and developing methods for fair training and generative modeling. He has also made significant contributions to information theory, particularly in interference channels, network coding, and quantum key distribution. Analysis of his recent publications reveals a strong trend toward addressing fairness challenges in AI systems while maintaining theoretical rigor. His work bridges information theory with practical machine learning applications, particularly in recommender systems and community detection. Suh's research demonstrates how graph structures can enhance data recovery and how theoretical insights from information theory can improve modern machine learning systems. Dr. Suh has received recognition for his scholarly contributions through numerous publications in top-tier venues including IEEE Transactions on Information Theory, NeurIPS, ICML, and AAAI. His work has influenced both theoretical understanding and practical implementations in data science. As an academic advisor, Suh has mentored numerous graduate students who have gone on to publish significant research in their own right. His collaborative approach is evident in the diverse range of co-authors across his publications, indicating strong research partnerships both within KAIST and internationally. His laboratory work appears to focus on information-theoretic approaches to machine learning problems, with particular emphasis on structured data analysis, fairness considerations, and efficient algorithm design for large-scale data processing tasks.

Chen YiranView profile

Professor

• Mass Spectrometry
• Proteomics
• Peptidomics
• +7 more

Chen Yiran is a Researcher at the Agricultural Biotechnology Research Center, Academia Sinica , where he has contributed to mass spectrometry , proteomics , and plant immunity . He serves as Chairman of the Taiwan Mass Spectrometry Society and holds Professor positions at National Chung Hsing University (Center for Biotechnology Development), National Taiwan University (Institute of Biotechnology/Systems Biology Program), and National Taiwan Ocean University (Department of Life Science and Biotechnology). His work spans peptidomics , DNA adductomics , and plant-microbe interactions . Chen's research integrates mass spectrometry with bioinformatics to study environmental health risks, plant immune signaling, and disease mechanisms. His team has developed tools like the FeatureHunter software for adduct detection and UniQua signal processor for proteomics. Current projects include CAPE9 peptide characterization for plant immunity and oxidative stress analysis in metabolic disorders. 2025: Outstanding Talent Development Foundation Leap Lecture 2024: Taiwan Mass Spectrometry Society Outstanding Scholar Award 2016: Academia Sinica Young Scholars Research Book Award 2015: Yang Xiangfa Agricultural Sciences Young Scholar Award Laboratory members include doctoral students Ying Guangting , Anciotti , and Jiefan . The lab operates at Academia Sinica's Agricultural Science Building A523 , with equipment for advanced chromatography-mass spectrometry and proteome analysis . Collaborations span National Taiwan University , Stanford , and UC Davis alumni networks.

Ana María Sánchez-PérezView profile

Researcher

• Neurobiotechnology
• Neuroscience
• Biodegradation
• +3 more

Ana María Sánchez-Pérez is a Principal Investigator at the Institute of Advanced Materials (INAM), University of Jaume I, Spain. She coordinates the Neurobiotechnology research group (RG8), focusing on developing biotechnological tools for brain-mental health and plastic-degrading enzymes. Education Biology, Valencia University Master's Degree (1993) and PhD (1997), University of Bristol (UK) Her research integrates neurobiotechnology and environmental biotechnology. She investigates: Neuroinflammation and insulin resistance in neurological/psychiatric disorders Synaptic plasticity, memory, and sex-dependent effects of IRS1 signaling Development of AAV-derived particles and DNA nanoparticles for therapeutic applications Encapsulated Abscisic Acid (ABA) to improve bioavailability against neuroinflammation Plastic-degrading enzymes (PETase) for environmental sustainability Her recent work focuses on enhancing PETase biodegradation of textiles using UV ozone pretreatment and alkali pre-treatment for reduced polymer crystallinity. These studies align with her dual expertise in neurobiotechnology and enzymatic degradation of synthetic polymers. The Neurobiotechnology group at INAM, established in 2013, employs in vitro and in vivo platforms to evaluate neuroprotective molecules and dissect neural circuits. Projects include RNA interference studies for ADHD subtypes and ABA-based therapies for Alzheimer's disease models.

Emil Kofod-OlsenView profile

Associate Professor

• Cancer Immunotherapy
• Dendritic Cell Biology
• STING Pathway
• +3 more

Emil Kofod-Olsen , Ph.D., Associate Professor , is affiliated with the Department of Health Science and Technology at Aarhus University 's Faculty of Medicine. His research spans cancer immunotherapy , dendritic cell biology , and STING pathway modulation , combining cholesterol metabolism interference with immune checkpoint inhibitors to enhance therapeutic outcomes. Research Interests: STING-targeted immunotherapy Dendritic cell vaccines Cholesterol pathways in immunity Combination cancer treatments cGAS-STING activation Scientific Awards: Award Date: 1 Jul 2011 Teaching & Leadership: Lectures/case sessions/labs in immunology & microbiology Supervision across 4th-8th semesters + master's theses Board Member & Treasurer, Danish Immunological Society (2017-2023) Scandinavian Society of Immunology member (2016-present) Article Trends: Recent work focuses on cholesterol-binding motifs (2024 Nature Communications ), dendritic cell vaccines with poly(I:C) (2024 Vaccine ), and electroporation-immunotherapy combinations (2024 iScience ), showing strong alignment with cGAS-STING , tumor immunology , and vaccine adjuvants .

• Theoretical quantum physics
• Decoherence theory
• Quantum optomechanics
• +6 more

Professor Klaus Hornberger is a leading theoretical physicist at the University of Duisburg-Essen, Germany, heading the AG Hornberger research group devoted to the quantum physics of complex nanoscale systems. Since 2011 he has held the Chair of Theoretical Physics in the Faculty of Physics, after previously leading a research group at the Max Planck Institute for the Physics of Complex Systems and holding an Emmy Noether grant at LMU Munich. Education & Career: PhD in Quantum Chaos, LMU Munich (2001) Diploma Physics, LMU Munich & MPQ Garching (1997) Post-doctoral fellow, University of Vienna (with Markus Arndt & Anton Zeilinger) Emmy Noether Group Leader, LMU Munich (2004-2009) Research Group Leader, MPI Dresden (2009-2011) Professor of Theoretical Physics, University of Duisburg-Essen (2011–present) Research Focus: His work centres on decoherence theory , matter-wave interferometry , quantum opto- and electro-mechanics , and the quantum-to-classical transition . Ongoing projects explore decoherence and entanglement in nanomechanical systems, molecular matter waves, levitated nanoparticles, and rotational superpositions. The group pursues both foundational tests of quantum mechanics and practical sensing applications, often in close collaboration with leading experimental teams worldwide. Scientific Awards & Honors: Outstanding Referee Award, American Physical Society (2022) Member of the NRW Academy of Sciences & Arts (since 2022) Emmy Noether Grant, German Research Foundation (2004–2009) Otto Hahn Medal, Max Planck Society (2001) Supervision & Grants: He has supervised >15 PhD students, many of whom have themselves received dissertation and poster prizes. His research is funded by the EU Horizon 2020 programme (NANOQUESTFIT, MAQRO), the German Research Foundation (DFG Emmy Noether, Heisenberg, SFB/TRR), and the Wilhelm & Else Heraeus Foundation (workshops & summer schools). Group & Collaborations: The AG Hornberger group occupies rooms MG 480–490 in the Duisburg campus, hosting post-docs, PhD and Master students working on theory closely coupled to experiments at UC Berkeley, University of Vienna, ETH Zürich, Imperial College London, and other leading laboratories.

Benjamin GängerView profile

Researcher

• Ultracold Quantum Gases
• Atomic Physics
• Quantum Simulation
• +3 more

Dr. Benjamin Gänger serves as a Researcher within the Faculty of Physics at RPTU Kaiserslautern-Landau, leading his own working group under Prof. Artur Widera's research team. His position focuses on experimental quantum physics using ultracold atomic systems. His research centers on Ultracold Quantum Gases and Quantum Simulation, with specific expertise in fermionic lithium systems and Bose-Einstein condensates. He investigates quantum impurities like polarons to model condensed matter phenomena, employing advanced laser cooling techniques and precision quantum gas apparatus. His work bridges atomic physics and condensed matter theory through experimental quantum simulation. Analysis of his publications reveals consistent focus on experimental methodologies for quantum gas manipulation, with emphasis on apparatus design for fermionic systems and quantum impurity studies. His research trajectory demonstrates increasing sophistication in quantum control techniques while maintaining core focus on quantum simulation applications. Editor's Pick for Rev. Sci. Instr. 89, 093105 (2018) Dr. Gänger actively mentors junior researchers within Prof. Widera's laboratory infrastructure, contributing to experimental design and data analysis for quantum gas experiments. His work aligns with RPTU's quantum physics research initiatives as evidenced by recent departmental news coverage of related breakthroughs.

Olivier LévêqueView profile

Researcher

• Information Theory
• Random Matrices
• Stochastic Calculus
• +2 more

Olivier Lévêque is a Senior Scientist at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences. He conducts research at the Laboratory of Information Theory (LTHI) and holds teaching responsibilities in both Communication Systems (SSC) and Computer Science (SIN) sections. Additionally, he contributes to the Interface EPFL-Gymnases initiative. Lévêque obtained his Physics diploma (1995) and PhD in Mathematics (2001) from EPFL, with a visiting lectureship at Stanford University's Electrical Engineering Department in 2005-2006. His research explores fundamental aspects of information theory , random matrices , and stochastic calculus , with applications in wireless communications and network theory. Key interests include capacity scaling laws in ad hoc networks, diversity-multiplexing tradeoffs, and mathematical frameworks for communication systems. Recent publications demonstrate broad interdisciplinary engagement, spanning computational thinking assessment (2022), digital education frameworks (2019), satellite positioning systems (2018), and theoretical advances in probability (2018). His work consistently integrates mathematical rigor with practical communication challenges, particularly in wireless network optimization and information-theoretic security. He has supervised four doctoral students at EPFL and teaches courses including Information, Computation, Communication , Markov Chains and Algorithmic Applications , and Cryptography . Lévêque leads research activities within the Laboratory of Information Theory, focusing on theoretical foundations of modern communication systems.

Wenjie LiView profile

Assistant Professor

• Thermoelectrics
• Materials Science
• Energy Harvesting
• +3 more

Wenjie Li serves as Assistant Professor in the Department of Biochemistry, Chemistry & Physics at Georgia Southern University, joining the institution in 2025. His research spans thermoelectrics, energy harvesting, and advanced materials development with significant contributions to sustainable technology. His primary research interests include: Thermoelectric materials for waste heat recovery and energy conversion Solid-state hydrogen storage systems Ceramic processing (zirconia, yttrium oxide, oxynitrides) Sintering techniques and luminescence properties Multi-source energy harvesting combining piezoelectric and thermoelectric principles Microwave absorption materials for electromagnetic shielding Publication trends reveal intense focus on practical energy solutions, particularly automotive thermoelectric applications and novel hydrogen storage materials. His work demonstrates strong industry relevance with applications in exhaust systems, automotive components, and electromagnetic protection. Research aligns with UN Sustainable Development Goals for clean energy and sustainable industry. Dr. Li has accumulated 2035 citations and an h-index of 27 according to Scopus metrics, with 66 total research outputs showing accelerating productivity (11 publications in 2024, 3 in 2025). Notable works include thermoelectric exhaust recovery systems cited in 16 news outlets and microwave absorption research with significant industry attention.

Brittany Nelson-CheesemanView profile

Professor

• Materials Science and Engineering
• Nanomaterials
• Electronic and Magnetic Materials
• +11 more

Brittany Nelson-Cheeseman is a Professor and Director of Materials Science and Engineering in the Mechanical Engineering Department at the University of St. Thomas' School of Engineering. She holds leadership responsibilities as Director while maintaining an active research program and teaching undergraduate and graduate courses in materials science and engineering. Her educational background includes: PhD in Materials Science and Engineering from University of California, Berkeley (with Designated Emphasis in Nanoscale Science and Engineering) MS in Materials Science and Engineering from University of California, Berkeley BS in Materials Science and Engineering from University of Wisconsin, Madison Nelson-Cheeseman's research focuses on novel composite materials for additive manufacturing, particularly magnetic elastomer smart materials that achieve remote contactless motion for soft robotic applications. Her expertise spans electronic and magnetic materials, nanomaterials, thin films, functional composites, 3D-printing, smart materials, and materials characterization. She has extensive experience utilizing national laboratory facilities across the US, particularly with synchrotron radiation techniques for materials characterization. Her work bridges fundamental materials science with practical applications in soft robotics, medical devices, and energy systems. Analysis of her recent publications reveals a clear research trajectory from fundamental studies of complex oxides and thin film heterostructures toward applied research in magnetic materials for additive manufacturing. Her work demonstrates increasing focus on 3D printed magnetic composites, with particular emphasis on controlling magnetic properties through printing parameters, infill patterns, and magnetic annealing techniques. This evolution shows her ability to translate fundamental materials knowledge into practical engineering applications. Her scientific recognition includes: Editor's Pick selection in AIP Advances (2022) APL Materials Editor's Pick (2014) PRB Editor's Suggestion (2010) Featured in Virtual Journal of Nanoscale Science and Technology (2010 and 2007) Nelson-Cheeseman is actively involved in engineering education, teaching courses including Engineering Materials, Smart Materials, and Materials Engineering. She serves as an advisor for the Senior Design Clinic in Peru, demonstrating her commitment to global engineering education. Her educational background includes postdoctoral research at Argonne National Laboratory and work at the Institut de Ciencia de Materials at the Universitat Autonoma de Barcelona. She has also participated in Semester at Sea, taking liberal arts courses while visiting 11 different countries, reflecting her passion for intercultural learning. Her research group develops novel composite materials for additive manufacturing, focusing on magnetic elastomer smart materials for soft robotic applications inside the human body or vessels. She maintains national and international collaborations and utilizes advanced facilities including oxide molecular beam epitaxy (MBE) at national laboratories.

Adam SiepelView profile

Professor

• Computational biology
• Genomics
• Molecular evolution
• +3 more

Professor Adam Siepel is a prominent computational biologist at Cold Spring Harbor Laboratory (CSHL) , where he has directed the Simons Center for Quantitative Biology since 2014. Holding a Ph.D. in Computer Science from UC Santa Cruz (2005), Siepel bridges computer science, statistics, and genetics to decode evolutionary patterns in genomic data. Key affiliations: CSHL (2014-present), Cornell University (2006-2014), National Center for Genome Resources (1996-2001) Research Focus : His work centers on developing mathematical models and computational methods to analyze genomic evolution. Siepel's lab explores molecular evolution , transcriptional regulation , and population genetics , with applications spanning cancer, plant breeding, and human disease. Recent Research Trends : His team has published extensively on transcription elongation dynamics , ancient human evolution , maize domestication , and cancer metastasis mapping . Articles highlight integration of nascent RNA sequencing , machine learning , and ancestral recombination graphs . Scientific Recognition : Guggenheim Fellowship (2012-2013) Sloan Research Fellowship (2009-2011) Packard Fellowship (2007) NSF CAREER Award (2007) Mentorship & Collaboration : Mentored over 20 graduate and postdoctoral researchers, including Ziyi Mo and Armin Scheben . Collaborates with experimentalists in cancer, neuroscience, and plant biology. Lab Overview : The Siepel Lab unites mathematicians, physicists, and biologists to tackle interdisciplinary problems. Current projects include modeling transcriptional equilibrium , tracking cancer evolution , and analyzing primate genomic constraints .

• Probability Theory
• Random Walks
• Random Algorithms
• +5 more

Quirin Thomas Simon Vogel is a Senior Lecturer at the University of Klagenfurt , located within the Department of Statistics . Before joining Klagenfurt, he held post-doctoral positions at the Technical University of Munich and New York University Shanghai , and served as Interim Professor at Ludwig-Maximilians University of Munich . His research lies at the intersection of probability theory and statistical mechanics . Specifically, he investigates random walks , random algorithms , and loop-based models arising from physical systems. Key themes include: Loop percolation and interacting Bose gases Large deviations and critical phenomena Randomised algorithms for communication networks Mathematical models of cancer dynamics and immune response Across his 2020-2025 publications, Vogel consistently applies probabilistic techniques to high-dimensional statistical-physics models, neural-network theory, and wireless-protocol design, evidencing a broad yet cohesive research portfolio. Contact details: Email: quirin.vogel@aau.at Office: N.0.01, Main Building, North Wing West, Level 0 Phone: +43 463 2700 3156

Oliver T JohnsonView profile

Professor

• Information Theory
• Probability Theory
• Statistics
• +4 more

Professor Oliver T Johnson is Head of the School of Mathematics at the University of Bristol. His research spans probability theory, statistics, and information theory, with both theoretical and applied focuses. Develops theoretical frameworks for entropy properties in limit theorems (Central Limit Theorem, Poisson convergence) Works on group testing algorithms and their information-theoretic capacities Applies information theory to communication systems (interference alignment, spectrum sensing) His research outputs include foundational work on discrete analogues of entropy inequalities and converse bounds for inference problems. Current projects explore efficient algorithms for change-point detection and information geometry of graphs. He actively supervises PhD students and engages in public outreach through media appearances and educational talks. Recent collaborative projects include: Interdisciplinary work with Electrical Engineering and Computer Science Investigations into discrete transport equations and Shepp-Olkin conjectures Applications of group testing to spectrum sensing and epidemic modeling

• Cognitive Psychology
• Developmental Psychology
• Temporal Processing
• +3 more

Stefan Pichelmann is a Senior Lecturer at the Department of Psychology , University of Fribourg , affiliated with the Faculty of Letters and Human Sciences. His academic work spans cognitive, developmental, and temporal processing research. Contact: stefan.pichelmann@unifr.ch | +41 26 300 7652 | RM 01 bu. C-2.110, Rue PA de Faucigny 2, 1700 Fribourg Research Focus: Pichelmann investigates cognitive mechanisms in spatial perspective-taking, time perception, and sensory integration. His work applies psychometric and experimental methods to analyze how numerical values, spatial tasks, and sensory modalities influence temporal judgments. Key Trends in Publications: Recent studies (2013–2023) emphasize spatial cognition , temporal processing , sensory integration , and cognitive workload . Articles on digit magnitude effects, mental rotation, and multisensory timing highlight interdisciplinary intersections with neuroscience and psycholinguistics. Departmental Affiliation: Active in the Department of Psychology, his research aligns with teams like Cognitive Development and Clinical Psychology, contributing to foundational and applied psychological sciences.

• Embedded Systems
• Cyber-Physical Systems
• Performance Engineering
• +3 more

Jeroen Voeten is a Full Professor in the Electronic Systems group of the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). He also holds a position as a Research Fellow at the Embedded Systems Institute in Eindhoven and is a Senior Scientist and Scientific Advisor to TNO-ESI since 2017. Academic Background: MSc in Mathematics and Computing Science (1991, TU/e) PhD in Electrical Engineering (1997, TU/e) Voeten's research focuses on formal methodologies for hardware/software system specification, design, and implementation. His work spans computer architectures, embedded systems, performance modeling, and cyber-physical systems. He is currently leading the Carm 2G project with ASML to enhance model-based engineering environments for wafer scanner control systems. His recent publications emphasize advancements in global scheduling, fault-tolerant real-time systems, and hybrid performance modeling. These studies address critical areas like latency reduction, schedulability improvements, and data age analysis in multi-rate task chains. Scientific Awards: Best Paper Award, Forum on Specification and Design Languages (FDL 2005) Best Paper Award, Property-Preserving Synthesis for Unified Control and Data-Oriented Models (2005) Voeten has contributed to 87 conference reports, 13 academic reports, 11 book chapters, and 11 journal articles, reflecting his extensive involvement in both academic and industrial research. Labs and Collaborations: He is affiliated with the Model-Based Design Lab and the High Tech Systems Center at TU/e, collaborating with institutions like TNO-ESI and industry leaders such ASML. His work aligns with the UN Sustainable Development Goals (SDGs) through applications in embedded systems and high-tech manufacturing.